diff --git a/.Rbuildignore b/.Rbuildignore index 4f507d5..7898fca 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -5,3 +5,4 @@ ^LICENSE\.md$ ^revdep$ ^cran-comments\.md$ +^.github$ diff --git a/DESCRIPTION b/DESCRIPTION index 0ca7384..3c5ba98 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,18 +1,22 @@ Package: BIGr -Title: Breeding Insight Genomics Functions for Polypoid and Diploid Species +Title: Breeding Insight Genomics Functions for Polypoid and Diploid + Species Version: 0.5.0 Author: Alexander M. Sandercock, Cristiane H. Taniguti, Josue Chinchilla-Vargas, Shufen Chen, Manoj Sapkota, Meng Lin, Dongyan Zhao, and Breeding Insight Team Maintainer: Alexander M. Sandercock -Description: Functions developed within Breeding Insight to analyze diploid and polyploid - breeding and genetic data. 'BIGr' provides the ability to filter VCF files, extract SNPs from the DArT MADC file, - and manipulate genotype data for both diploid and polyploid species. It also serves - as the core dependency for the 'BIGapp' Shiny app, which provides a user-friendly interface for performing routine genotype analysis tasks - such as dosage calling, filtering, PCA, GWAS, and Genomic Prediction. +Description: Functions developed within Breeding Insight to analyze + diploid and polyploid breeding and genetic data. 'BIGr' provides the + ability to filter VCF files, extract SNPs from the DArT MADC file, and + manipulate genotype data for both diploid and polyploid species. It + also serves as the core dependency for the 'BIGapp' Shiny app, which + provides a user-friendly interface for performing routine genotype + analysis tasks such as dosage calling, filtering, PCA, GWAS, and + Genomic Prediction. +License: Apache License (>= 2) URL: https://github.com/Breeding-Insight/BIGr BugReports: https://github.com/Breeding-Insight/BIGr/issues -License: Apache License (>= 2) Depends: R (>= 4.4.0) Imports: @@ -24,6 +28,7 @@ Imports: methods, parallel, pwalign, + quadprog, Rdpack (>= 0.7), readr (>= 2.1.5), reshape2 (>= 1.4.4), @@ -33,7 +38,7 @@ Imports: utils, vcfR (>= 1.15.0) Suggests: - testthat (>= 3.0.0) + testthat (>= 3.0.0) RdMacros: Rdpack Encoding: UTF-8 diff --git a/NAMESPACE b/NAMESPACE index 414dd6c..2474c50 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,30 +1,27 @@ # Generated by roxygen2: do not edit by hand -export(add_ref_alt) +export(allele_freq_poly) export(calculate_Het) export(calculate_MAF) export(capture_diversity.Gmat) export(check_ped) -export(compare) -export(create_VCF_body) export(dosage2vcf) export(dosage_ratios) export(filterVCF) export(flip_dosage) export(get_OffTargets) export(get_countsMADC) -export(get_ref_alt_hap_seq) export(imputation_concordance) -export(loop_though_dartag_report) export(madc2vcf) export(merge_MADCs) -export(merge_counts) +export(solve_composition_poly) export(updog2vcf) import(doParallel) import(dplyr) import(foreach) import(janitor) import(parallel) +import(quadprog) import(tibble) import(tidyr) import(vcfR) @@ -37,6 +34,7 @@ importFrom(pwalign,pairwiseAlignment) importFrom(readr,read_csv) importFrom(reshape2,dcast) importFrom(reshape2,melt) +importFrom(stats,cor) importFrom(stats,lm) importFrom(stats,qt) importFrom(stats,sd) diff --git a/R/breedtools_functions.R b/R/breedtools_functions.R index 75c7b14..a7bd41b 100644 --- a/R/breedtools_functions.R +++ b/R/breedtools_functions.R @@ -1,12 +1,35 @@ #' Computes allele frequencies for specified populations given SNP array data #' -#' @param geno matrix of genotypes coded as the dosage of allele B {0, 1, 2, ..., ploidy} +#' @param geno matrix of genotypes coded as the dosage of allele B \code{{0, 1, 2, ..., ploidy}} #' with individuals in rows (named) and SNPs in columns (named) #' @param populations list of named populations. Each population has a vector of IDs #' that belong to the population. Allele frequencies will be derived from all animals #' @param ploidy integer indicating the ploidy level (default is 2 for diploid) #' @return data.frame consisting of allele_frequencies for populations (columns) for #' each SNP (rows) +#' @references Funkhouser SA, Bates RO, Ernst CW, Newcom D, Steibel JP. Estimation of genome-wide and locus-specific +#' breed composition in pigs. Transl Anim Sci. 2017 Feb 1;1(1):36-44. +#' +#' @examples +#' # Example inputs +#' geno_matrix <- matrix( +#' c(4, 1, 4, 0, # S1 +#' 2, 2, 1, 3, # S2 +#' 0, 4, 0, 4, # S3 +#' 3, 3, 2, 2, # S4 +#' 1, 4, 2, 3),# S5 +#' nrow = 4, ncol = 5, byrow = FALSE, # individuals=rows, SNPs=cols +#' dimnames = list(paste0("Ind", 1:4), paste0("S", 1:5)) +#' ) +#' +#'pop_list <- list( +#' PopA = c("Ind1", "Ind2"), +#' PopB = c("Ind3", "Ind4") +#' ) +#' +#' allele_freqs <- allele_freq_poly(geno = geno_matrix, populations = pop_list, ploidy = 4) +#' print(allele_freqs) +#' #' @export allele_freq_poly <- function(geno, populations, ploidy = 2) { @@ -37,16 +60,20 @@ allele_freq_poly <- function(geno, populations, ploidy = 2) { } -# Performs whole genome breed composition prediction. -# -# @param Y numeric vector of genotypes (with names as SNPs) from a single animal. -# coded as dosage of allele B {0, 1, 2} -# @param X numeric matrix of allele frequencies from reference animals -# @param p numeric indicating number of breeds represented in X -# @param names character names of breeds -# @return data.frame of breed composition estimates -# @import quadprog -# @export +#' Performs whole genome breed composition prediction. +#' +#' @param Y numeric vector of genotypes (with names as SNPs) from a single animal. +#' coded as dosage of allele B \code{{0, 1, 2, ..., ploidy}} +#' @param X numeric matrix of allele frequencies from reference animals +#' @param p numeric indicating number of breeds represented in X +#' @param names character names of breeds +#' @return data.frame of breed composition estimates +#' @import quadprog +#' @importFrom stats cor +#' @references Funkhouser SA, Bates RO, Ernst CW, Newcom D, Steibel JP. Estimation of genome-wide and locus-specific +#' breed composition in pigs. Transl Anim Sci. 2017 Feb 1;1(1):36-44. +#' +#' @noRd QPsolve <- function(Y, X) { # Remove NAs from Y and remove corresponding @@ -90,7 +117,7 @@ QPsolve <- function(Y, X) { #' batch of animals. #' #' @param Y numeric matrix of genotypes (columns) from all animals (rows) in population -#' coded as dosage of allele B {0, 1, ..., ploidy} +#' coded as dosage of allele B \code{{0, 1, 2, ..., ploidy}} #' @param X numeric matrix of allele frequencies (rows) from each reference panel (columns). Frequencies are #' relative to allele B. #' @param ped data.frame giving pedigree information. Must be formatted "ID", "Sire", "Dam" @@ -107,6 +134,37 @@ QPsolve <- function(Y, X) { #' @return A data.frame or list of data.frames (if groups is !NULL) with breed/ancestry composition #' results #' @import quadprog +#' @references Funkhouser SA, Bates RO, Ernst CW, Newcom D, Steibel JP. Estimation of genome-wide and locus-specific +#' breed composition in pigs. Transl Anim Sci. 2017 Feb 1;1(1):36-44. +#' +#' @examples +#' # Example inputs for solve_composition_poly (ploidy = 4) +#' +#' # (This would typically be the output from allele_freq_poly) +#' allele_freqs_matrix <- matrix( +#' c(0.625, 0.500, +#' 0.500, 0.500, +#' 0.500, 0.500, +#' 0.750, 0.500, +#' 0.625, 0.625), +#' nrow = 5, ncol = 2, byrow = TRUE, +#' dimnames = list(paste0("SNP", 1:5), c("VarA", "VarB")) +#' ) +#' +#' # Validation Genotypes (individuals x SNPs) +#' val_geno_matrix <- matrix( +#' c(2, 1, 2, 3, 4, # Test1 dosages for SNP1-5 +#' 3, 4, 2, 3, 0), # Test2 dosages for SNP1-5 +#' nrow = 2, ncol = 5, byrow = TRUE, +#' dimnames = list(paste0("Test", 1:2), paste0("SNP", 1:5)) +#' ) +#' +#' # Calculate Breed Composition +#' composition <- solve_composition_poly(Y = val_geno_matrix, +#' X = allele_freqs_matrix, +#' ploidy = 4) +#' print(composition) +#' #' @export solve_composition_poly <- function(Y, X, diff --git a/R/breedtoos_functions.R b/R/breedtoos_functions.R deleted file mode 100644 index a288e84..0000000 --- a/R/breedtoos_functions.R +++ /dev/null @@ -1,164 +0,0 @@ -#' Computes allele frequencies for specified populations given SNP array data -#' -#' @param geno matrix of genotypes coded as the dosage of allele B {0, 1, 2, ..., ploidy} -#' with individuals in rows (named) and SNPs in columns (named) -#' @param populations list of named populations. Each population has a vector of IDs -#' that belong to the population. Allele frequencies will be derived from all animals -#' @param ploidy integer indicating the ploidy level (default is 2 for diploid) -#' @return data.frame consisting of allele_frequencies for populations (columns) for -#' each SNP (rows) -#' @export -allele_freq_poly <- function(geno, populations, ploidy = 2) { - - # Initialize returned df - X <- matrix(NA, nrow = ncol(geno), ncol = length(populations)) - - # Subset geno into different populations - for (i in 1:length(populations)) { - - # Get name of ith item in the list (population name) - pop_name <- names(populations[i]) - - # Subset geno to only include genotypes of IDs in pop - pop_geno <- geno[rownames(geno) %in% populations[[i]], ] - - # Calculate allele frequencies - al_freq <- colMeans(pop_geno, na.rm = TRUE) / ploidy - - # Add to X - X[, i] <- al_freq - } - - # Label X with populations and SNPs - colnames(X) <- names(populations) - rownames(X) <- colnames(geno) - - return(X) -} - - -# Performs whole genome breed composition prediction. -# -# @param Y numeric vector of genotypes (with names as SNPs) from a single animal. -# coded as dosage of allele B {0, 1, 2} -# @param X numeric matrix of allele frequencies from reference animals -# @param p numeric indicating number of breeds represented in X -# @param names character names of breeds -# @return data.frame of breed composition estimates -# @import quadprog -# @export -QPsolve <- function(Y, X) { - - # Remove NAs from Y and remove corresponding - # SNPs from X. Ensure Y is numeric - Ymod <- Y[!is.na(Y)] - Xmod <- X[names(Ymod), ] - - # Determine properties from X matrix - the number of parameters (breeds) p - # and the names of those parameters. - p <- ncol(X) - names <- colnames(X) - - # perfom steps needed to solve OLS by framing - # as a QP problem - # Rinv - matrix should be of dimensions px(p+1) where p is the number of variables in X - Rinv <- solve(chol(t(Xmod) %*% Xmod)) - - # C - the first column is a sum restriction (all equal to 1) and the rest of the columns an identity matrix - C <- cbind(rep(1, p), diag(p)) - - # b2 - This should be a vector of length p+1 the first element is the value of the sum (1) - # the other elements are the restriction of individual coefficients (>) - # so a value 0 produces positive coefficients - b2 <- c(1, rep(0, p)) - - # dd - this should be a matrix NOT a vector - dd <- (t(Ymod) %*% Xmod) - - qp <- solve.QP(Dmat = Rinv, factorized = TRUE, dvec = dd, Amat = C, bvec = b2, meq = 1) - beta <- qp$solution - rr <- cor(Ymod, Xmod %*% beta)^2 - result <- c(beta, rr) - names(result) <- c(names, "R2") - return(result) -} - - -#' Compute genome-wide breed composition -#' -#' Computes genome-wide breed/ancestry composition using quadratic programming on a -#' batch of animals. -#' -#' @param Y numeric matrix of genotypes (columns) from all animals (rows) in population -#' coded as dosage of allele B {0, 1, ..., ploidy} -#' @param X numeric matrix of allele frequencies (rows) from each reference panel (columns). Frequencies are -#' relative to allele B. -#' @param ped data.frame giving pedigree information. Must be formatted "ID", "Sire", "Dam" -#' @param groups list of IDs categorized by breed/population. If specified, output will be a list -#' of results categorized by breed/population. -#' @param mia logical. Only applies if ped argument is supplied. If true, returns a data.frame -#' containing the inferred maternally inherited allele for each locus for each animal instead -#' of breed composition results. -#' @param sire logical. Only applies if ped argument is supplied. If true, returns a data.frame -#' containing sire genotypes for each locus for each animal instead of breed composition results. -#' @param dam logical. Only applies if ped argument is supplied. If true, returns a data.frame -#' containing dam genotypes for each locus for each animal instead of breed composition results. -#' @param ploidy integer. The ploidy level of the species (e.g., 2 for diploid, 3 for triploid, etc.). -#' @return A data.frame or list of data.frames (if groups is !NULL) with breed/ancestry composition -#' results -#' @import quadprog -#' @export -solve_composition_poly <- function(Y, - X, - ped = NULL, - groups = NULL, - mia = FALSE, - sire = FALSE, - dam = FALSE, - ploidy = 2) { - - # Functions require Y to be animals x SNPs. Transpose - Y <- t(Y) - - # SNPs in Y should only be the ones present in X - Y <- Y[rownames(Y) %in% rownames(X), ] - - # If ped is supplied, use QPsolve_par to compute genomic composition using - # only animals who have genotyped parents (by incorporating Sire genotype). - if (!is.null(ped)) { - mat_results <- lapply(colnames(Y), - QPsolve_par, - Y, - X, - ped, - mia = mia, - sire = sire, - dam = dam) - - mat_results_tab <- do.call(rbind, mat_results) - return (mat_results_tab) - - # Else if groups supplied - perform regular genomic computation - # and list results by groups - } else if (!is.null(groups)) { - - # When using regular genomic computation - adjust dosage based on ploidy - Y <- Y / ploidy - - grouped_results <- lapply(groups, QPseparate, Y, X) - return (grouped_results) - - # If neither using the ped or grouping option - just perform normal, unsegregated - # calculation - } else { - - # Adjust dosage based on ploidy - Y <- Y / ploidy - - results <- t(apply(Y, 2, QPsolve, X)) - return (results) - } -} - - - diff --git a/R/check_ped.R b/R/check_ped.R index 7900e31..58d8e49 100644 --- a/R/check_ped.R +++ b/R/check_ped.R @@ -15,6 +15,7 @@ #' #' @param ped.file path to pedigree text file. The pedigree file is a #' 3-column pedigree tab separated file with columns labeled as id sire dam in any order +#' @param return.output logical. If TRUE, the function will return a list of dataframes with the error types found. #' @return A list of dataframes of error types, and the output printed to the console #' @examples #' ##Get list with a dataframe for each error type @@ -32,7 +33,7 @@ #' @importFrom utils read.table #' @export #### Function to check for hierarchical errors missing parents and repeated ids #### -check_ped <- function(ped.file) { +check_ped <- function(ped.file, return.output = FALSE) { set.seed(101919) #### read in data #### data = utils::read.table(ped.file, header = T) @@ -129,11 +130,14 @@ check_ped <- function(ped.file) { missing_parents <- results$missing_parents messy_parents <- results$messy_parents errors <- results$dependencies + # Adding the dataframes as an output list + output.results <- list() #### Print errors and cycles #### # Print repeated ids if any if (nrow(repeated_ids) > 0) { cat("Repeated ids found:\n") print(repeated_ids) + output.results$repeated_ids <- repeated_ids } else { cat("No repeated ids found.\n") } @@ -141,6 +145,7 @@ check_ped <- function(ped.file) { if (nrow(messy_parents) > 0) { cat("Ids found as male and female parent:\n") print(messy_parents) + output.results$messy_parents <- messy_parents } else { cat("No ids found as male and female parent.\n") } @@ -148,6 +153,7 @@ check_ped <- function(ped.file) { if (nrow(missing_parents) > 0) { cat("Missing parents found:\n") print(missing_parents) + output.results$missing_parents <- missing_parents } else { cat("No missing parents found.\n") } @@ -160,4 +166,8 @@ check_ped <- function(ped.file) { } else { cat("No dependencies found.\n") } + + if (return.output) { + return(output.results) + } } diff --git a/R/get_OffTargets.R b/R/get_OffTargets.R index 4fa23d0..6849ff0 100644 --- a/R/get_OffTargets.R +++ b/R/get_OffTargets.R @@ -4,8 +4,12 @@ #' @param botloci path to file containing the target IDs that were designed in the bottom strand #' @param hap_seq path to haplotype DB fasta file #' @param rm_multiallelic_SNP logical. If TRUE, SNP with more than one alternative base will be removed. If FALSE, check `multiallelic_SNP_dp_thr` specs -#' @param multiallelic_SNP_dp_thr nnumerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold `multiallelic_SNP_dp_thr` combined with minimum number of samples `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites. -#' @param multiallelic_SNP_sample_thr numerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold combined with minimum number of samples `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites. +#' @param multiallelic_SNP_dp_thr nnumerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold `multiallelic_SNP_dp_thr` combined +#' with minimum number of samples `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic +#' aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites. +#' @param multiallelic_SNP_sample_thr numerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold combined with minimum number of +#' samples `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, +#' the marker is discarded. This is likely to happen to paralogous sites. #' @param n.cores number of cores to be used in the parallelization #' @param out_vcf output VCF file name #' @param verbose print metrics on the console @@ -83,7 +87,7 @@ get_OffTargets <- function(madc = NULL, #' #' @import parallel #' -#' @export +#' @noRd loop_though_dartag_report <- function(report, botloci, hap_seq, n.cores=1, verbose = TRUE){ hap_seq <- get_ref_alt_hap_seq(hap_seq) @@ -139,7 +143,7 @@ loop_though_dartag_report <- function(report, botloci, hap_seq, n.cores=1, verbo #' @param hap_seq haplotype DB #' @param nsamples number of samples #' -#' @export +#' @noRd add_ref_alt <- function(one_tag, hap_seq, nsamples) { # Add ref and alt @@ -195,7 +199,7 @@ add_ref_alt <- function(one_tag, hap_seq, nsamples) { #' @importFrom Biostrings DNAString reverseComplement #' @importFrom pwalign pairwiseAlignment nucleotideSubstitutionMatrix #' -#' @export +#' @noRd compare <- function(one_tag, botloci){ cloneID <- one_tag$CloneID[1] @@ -293,7 +297,7 @@ compare <- function(one_tag, botloci){ #' #' @param hap_seq haplotype db #' -#' @export +#' @noRd get_ref_alt_hap_seq <- function(hap_seq){ headers <- hap_seq$V1[grep(">",hap_seq$V1)] headers <- gsub(">", "", headers) @@ -320,14 +324,19 @@ get_ref_alt_hap_seq <- function(hap_seq){ #' #' @param csv CSV file generated by loop_though_dartag_report #' @param rm_multiallelic_SNP logical. If TRUE, SNP with more than one alternative base will be removed. If FALSE, check `multiallelic_SNP_dp_thr` specs -#' @param multiallelic_SNP_dp_thr numerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold `multiallelic_SNP_dp_thr` combined with minimum number of samples `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites. -#' @param multiallelic_SNP_sample_thr numerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold `multiallelic_SNP_dp_thr` combined with minimum number of samples `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites. +#' @param multiallelic_SNP_dp_thr numerical. If `rm_multiallelic_SNP` is FALSE, set a minimum +#' depth by tag threshold combined with minimum number of samples (`multiallelic_SNP_dp_thr` + `multiallelic_SNP_sample_thr`) +#' to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker +#' is discarded. This is likely to happen to paralogous sites. +#' @param multiallelic_SNP_sample_thr numerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold `multiallelic_SNP_dp_thr` combined +#' with minimum number of samples `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic +#' aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites. #' @param n.cores number of cores to be used in the parallelization #' @param verbose print metrics on the console #' #' @import parallel #' -#' @export +#' @noRd create_VCF_body <- function(csv, rm_multiallelic_SNP = TRUE, multiallelic_SNP_dp_thr = 2, @@ -400,10 +409,14 @@ create_VCF_body <- function(csv, #' #' @param cloneID_unit one item of csv file split by cloneID #' @param rm_multiallelic_SNP logical. If TRUE, SNP with more than one alternative base will be removed. If FALSE, check `multiallelic_SNP_dp_thr` specs -#' @param multiallelic_SNP_dp_thr numerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold combined with minimum number of samples `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites. -#' @param multiallelic_SNP_sample_thr numerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold `multiallelic_SNP_dp_thr` combined with minimum number of samples `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites. +#' @param multiallelic_SNP_dp_thr numerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold combined with minimum number of samples +#' `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker +#' is discarded. This is likely to happen to paralogous sites. +#' @param multiallelic_SNP_sample_thr numerical. If `rm_multiallelic_SNP` is FALSE, set a minimum depth by tag threshold `multiallelic_SNP_dp_thr` combined +#' with minimum number of samples `multiallelic_SNP_sample_thr` to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic +#' aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites. #' -#' @export +#' @noRd merge_counts <- function(cloneID_unit, rm_multiallelic_SNP = FALSE, multiallelic_SNP_dp_thr = 0, multiallelic_SNP_sample_thr = 0){ #Get counts for target SNP diff --git a/R/imputation_concordance.R b/R/imputation_concordance.R index a52f7a3..022dc84 100644 --- a/R/imputation_concordance.R +++ b/R/imputation_concordance.R @@ -9,11 +9,12 @@ #' @param missing_code Optional input to consider missing data to exclude in concordance calculation. #' @param snps_2_exclude Optional input to exclude specific markers from concordance calculation. Single column of marker ids. #' @param output Optional input to assign the output dataframe to a specific variable name. Default is "imputation_concordance" +#' @param verbose Optional input to print the concordance summary. #' @import dplyr #' @return 2 outputs: 1) A data frame with sample IDs and concordance percentages. 2) A summary of concordance percentages. #' @export #' -imputation_concordance <- function(reference_genos, imputed_genos, missing_code = NULL, snps_2_exclude = NULL, output = "imputation_concordance") { +imputation_concordance <- function(reference_genos, imputed_genos, missing_code = NULL, snps_2_exclude = NULL, output = "imputation_concordance", verbose = FALSE) { # Find common IDs common_ids <- intersect(imputed_genos$ID, reference_genos$ID) @@ -48,16 +49,23 @@ imputation_concordance <- function(reference_genos, imputed_genos, missing_code Concordance = paste0(round(percentage_match * 100, 2), "%") ) - # Assign the result dataframe to the output variable - assign(output, result_df, envir = .GlobalEnv) - # Print mean concordance summary_concordance <- summary(percentage_match, na.rm = TRUE) * 100 names(summary_concordance) <- c("Min", "1st Qu.", "Median", "Mean", "3rd Qu.", "Max") - cat("Concordance Summary:\n") - for (name in names(summary_concordance)) { - cat(name, ":", round(summary_concordance[name], 2), "%\n") + if (verbose) { + message("Concordance Summary:\n") + for (name in names(summary_concordance)) { + cat(name, ":", round(summary_concordance[name], 2), "%\n") + } } + + # Assign the result dataframe to the output variable + if (!is.null(output)) { + assign(output, result_df, envir = .GlobalEnv) + } else { + return(result_df) + } + } diff --git a/R/merge_MADCs.R b/R/merge_MADCs.R index a0cd34c..a7bb084 100644 --- a/R/merge_MADCs.R +++ b/R/merge_MADCs.R @@ -16,6 +16,43 @@ ##' ##' @import dplyr ##' +##' @examples +##' # First generating example MADC files +##' temp_dir <- tempdir() +##' file1_path <- file.path(temp_dir, "madc1.csv") +##' file2_path <- file.path(temp_dir, "madc2.csv") +##' out_path <- file.path(temp_dir, "merged_madc.csv") +##' +##' # Data for file 1: Has SampleA and SampleB +##' df1 <- data.frame( +##' AlleleID = c("chr1.1_0001|Alt_0002", "chr1.1_0001|Ref_0001", "chr1.1_0001|AltMatch_0001"), +##' CloneID = c("chr1.1_0001", "chr1.1_0001", "chr1.1_0001"), +##' AlleleSequence = c("GGG", "AAA", "TTT"), +##' SampleA = c(10, 8, 0), +##' SampleB = c(5, 4, 9), +##' stringsAsFactors = FALSE, +##' check.names = FALSE +##' ) +##' write.csv(df1, file1_path, row.names = FALSE, quote = FALSE) +##' +##' # Data for file 2: Has SampleA (duplicate name) and SampleC, different rows +##' df2 <- data.frame( +##' AlleleID = c("chr1.1_0001|Alt_0002", "chr1.1_0001|Ref_0001", "chr1.1_0001|AltMatch_0001"), +##' CloneID = c("chr1.1_0001", "chr1.1_0001", "chr1.1_0001"), +##' AlleleSequence = c("GGG", "AAA", "TTT"), +##' SampleA = c(11, 7, 20), +##' SampleC = c(1, 2, 6), +##' stringsAsFactors = FALSE, +##' check.names = FALSE +##' ) +##' write.csv(df2, file2_path, row.names = FALSE, quote = FALSE) +##' +##' # 2. Run the merge function +##' # Use default suffixes (.x, .y) for the duplicated "SampleA" +##' merge_MADCs(madc_list = list(file1_path, file2_path), +##' out_madc = out_path) +##' +##' ##' @export merge_MADCs <- function(..., madc_list=NULL, out_madc=NULL, run_ids=NULL){ diff --git a/inst/.DS_Store b/inst/.DS_Store new file mode 100644 index 0000000..3df67aa Binary files /dev/null and b/inst/.DS_Store differ diff --git a/inst/check_ped_test.txt b/inst/check_ped_test.txt new file mode 100644 index 0000000..ae7bc08 --- /dev/null +++ b/inst/check_ped_test.txt @@ -0,0 +1,16 @@ +id sire dam +off1 sire1 dam1 +off2 sire2 dam2 +off3 sire3 dam3 +off4 sire4 dam4 +off5 sire5 dam5 +sire1 off1 grandmother1 +sire2 grandfather2 grandfather2 +sire3 grandfather3 grandfather3 +sire4 grandfather4 grandmother4 +sire5 grandfather5 grandmother5 +dam1 grandfather6 grandmother6 +dam2 grandfather7 grandmother7 +dam3 grandfather8 grandmother8 +dam4 0 0 +dam5 0 0 \ No newline at end of file diff --git a/inst/example_MADC_FixedAlleleID.csv b/inst/example_MADC_FixedAlleleID.csv new file mode 100644 index 0000000..f92b839 --- /dev/null +++ b/inst/example_MADC_FixedAlleleID.csv @@ -0,0 +1,52 @@ +AlleleID,CloneID,AlleleSequence,Sample_1,Sample_2,Sample_3,Sample_4,Sample_5,Sample_6,Sample_7,Sample_8,Sample_9,Sample_10 +chr1.1_000194324|AltMatch_0001,chr1.1_000194324,CGAAATAATAACCCAAGTTCTGCCAGTTTATGTTAAAACTTTTTTTACAAGGTACAAGTTCGGTGACAAC,0,139,135,185,90,69,54,54,40,129 +chr1.1_000194324|Alt_0002,chr1.1_000194324,CGAAATAATAACCCAAGTTCTGCCAGTTTATGTTAAAACTTTTCTTACAAGGTACAAGTTCGGTGACAACTTAACAAGTAA,44,1,0,59,37,109,41,1,68,0 +chr1.1_000194324|Ref_0001,chr1.1_000194324,CGAAATAATAACCCAAGTTCTGCCAGTTTATGTTAAAACTTTTCTTACATGGTACAAGTTCGGTGACAACTTAACAAGTAA,152,171,160,0,71,60,95,147,49,163 +chr1.1_000309952|AltMatch_0001,chr1.1_000309952,TGGTATTGTATTAGATGAGATATTCTAACTTGTAAGGTAGAAATCTTGACCACTTATAAACACATATTCA,43,82,63,48,34,5,0,95,0,110 +chr1.1_000309952|Alt_0002,chr1.1_000309952,TGGTATTGTATTAGATGAGATATTCTAACTTGTAAGATTGAGATCTTGACCACTTATAAACACATATTCATATCATATGTA,0,0,0,0,0,0,0,0,0,0 +chr1.1_000309952|RefMatch_0001,chr1.1_000309952,TGGTATTGTATTAGATGAGATATTCTAACTTGTAAGGTGGAGATCTCGACGACTTATAAACACATATTCA,40,5,11,16,36,12,23,17,20,0 +chr1.1_000309952|Ref_0001,chr1.1_000309952,TGGTATTGTATTAGATGAGATATTCTAACTTGTAAGATTGAGATCTCGACCACTTATAAACACATATTCATATCATATGTA,0,0,0,0,0,0,0,0,0,0 +chr1.1_000452961|Alt_0002,chr1.1_000452961,TTACGAGATCGCGAAGTTCGTTCCTTTCTTTATCTTTCTTCTCTTTTACCCGACCGGCTCCCTGCAGACCAGAAAGCCCAA,0,0,0,0,0,0,0,0,0,0 +chr1.1_000452961|Ref_0001,chr1.1_000452961,TTACGAGATCGCGAAGCTCGTTCCTTTCTTTATCTTTCTTCTCTTTTACCCGACCGGCTCCCTGCAGACCAGAAAGCCCAA,0,0,0,0,0,0,0,0,0,0 +chr1.1_000532584|RefMatch_0001,chr1.1_000532584,CAACGGAACATATAAAGATATCCACTTCTCTTGGAGCTTGATAATACTTATAATGTTGGGGATTTGTGTT,0,0,0,157,0,197,0,0,0,0 +chr1.1_000532584|RefMatch_0002,chr1.1_000532584,CAACGGAACATATAAAGATATCCACTTCTCTTGGGGCTTGATAATACTTATAATGTTGGGGATTTGTGTT,0,0,0,0,0,0,0,0,143,0 +chr1.1_000532584|RefMatch_0003,chr1.1_000532584,CAACGGAACATATAAAGATATCCACTTTTCTCGGAGCTTGATAATACTTATAATGTTGGGGATTTGTGTT,0,0,0,0,0,0,0,0,1,0 +chr1.1_000532584|Ref_0001,chr1.1_000532584,CAACGGAACATATAAAGATATCCACTTCTCTTGGAGCTTGATGATACTTATAATGTTGGGGATTTGTGTTTTGCAGGATTT,653,236,176,0,199,410,473,216,177,1 +chr1.1_000735393|Alt_0002,chr1.1_000735393,GACTCTTGGAAGGAAAATGGTTTTTCTAGGTAATTAAACTTCAATCAAAGTTACATATTTGACTCACTTCACTATTCTAAA,248,91,74,0,70,0,174,73,165,5 +chr1.1_000735393|Ref_0001,chr1.1_000735393,GACTCTTGGAAGGAAAATGGTTTTTCTAGGTAGTTAAACTTCAATCAAAGTTACATATTTGACTCACTTCACTATTCTAAA,76,278,164,188,168,202,53,197,170,225 +chr1.1_000837330|Alt_0002,chr1.1_000837330,CCTCTATCTAATAGAGAATATTGATTGGCTGAATGTTGACCATATTCCATGTACCCACTAGGGTTACCCCGTGGAGTCCAA,0,0,0,78,0,90,0,0,176,0 +chr1.1_000837330|Ref_0001,chr1.1_000837330,CCTCTATCTAATAGAGAATATTGATTGGCTGAATGTTGACCATATTCCCTGTACCCACTAGGGTTACCCCGTGGAGTCCAA,364,344,348,229,285,265,270,345,147,339 +chr1.1_000915014|Alt_0002,chr1.1_000915014,CCAGGCTTCTATATATACAATGATCAGATATGTTAAACCTAAGCTGCTCAGTGCTCCTTAACCCTAAGACACACAGAACCT,1,0,1,0,0,3,1,0,0,0 +chr1.1_000915014|Ref_0001,chr1.1_000915014,CCAGGCTTCTATATATACAATGATCAGATATGTTAAACCTAAGCTGCTCGGTGCTCCTTAACCCTAAGACACACAGAACCT,271,465,342,177,486,122,265,377,103,542 +chr1.1_001169609|AltMatch_0001,chr1.1_001169609,CAATGATCTCTGCGCAACTGCACCTTTAAAATCTTCCTGCCTACATAGTACTTTTGGTTTTTGGAACCC,304,292,218,149,254,314,247,148,127,0 +chr1.1_001169609|Alt_0002,chr1.1_001169609,CAATGATCTCTGCGCAACTGCACCTTTAAAATCTTCCTGCCTGACATAGTACTTTTGGTTTTTGGAACCCAAGTACCGTAT,2,0,0,0,1,0,0,0,1,0 +chr1.1_001169609|RefMatch_0002,chr1.1_001169609,CAATGATCTCTGCGCAACTGCACCTTTTAAATCTTCCTGCCTGACAAAGTACTTTTGGTTTTTGGAACCC,0,284,214,564,0,0,0,272,229,243 +chr1.1_001169609|Ref_0001,chr1.1_001169609,CAATGATCTCTGCGCAACTGCACCTTTTAAATCTTCCTGCCTGACATAGTACTTTTGGTTTTTGGAACCCAAGTACCGTAT,593,300,196,254,486,571,419,508,451,705 +chr1.1_001494903|Alt_0002,chr1.1_001494903,TTGGTGCAGTGTTGATAGTAGCTGGACTATACTTTGTGTTGTGGGGTAAAAGTGAAGAGAAGAAATTATTTGCAAAGGAAC,22,21,9,5,10,5,24,18,7,11 +chr1.1_001494903|Ref_0001,chr1.1_001494903,TTGGTGCAGTGTTGATAGTAGCTGGACTATACTTTGTGCTGTGGGGTAAAAGTGAAGAGAAGAAATTATTTGCAAAGGAAC,5,17,7,18,13,14,3,6,22,12 +chr1.1_001590881|Alt_0002,chr1.1_001590881,CTGTGAGAAGCACTTCATCTGAATTAAGCAATCCTTTTCCCGTAAGTAAGAGTTTGTAATAGGTATTATCAAACATTCTTG,9,10,5,2,6,6,1,15,6,16 +chr1.1_001590881|Ref_0001,chr1.1_001590881,CTGTGAGAAGCACTTCATCTGAATTAAGCAATCCTTTTCCCCTAAGTAAGAGTTTGTAATAGGTATTATCAAACATTCTTG,27,6,12,3,8,9,21,5,11,0 +chr1.1_001938036|AltMatch_0003,chr1.1_001938036,CAGTGTTATCAGCCACACATGTAAATTGATGCTTTTATCTGGACTTGTTAAGTATACTGACAGCTTATC,0,0,0,27,0,25,0,0,2,0 +chr1.1_001938036|Alt_0002,chr1.1_001938036,CAGTGTTATCAGCCACACATGTAAATTGATGCTTTTCTCTGGACTTGTTTAAGTATACTGACAGCTTATCATGTCTGTTGG,0,48,39,82,30,71,0,0,32,0 +chr1.1_001938036|Ref_0001,chr1.1_001938036,CAGTGTTATCAGCCACACATGTAAATTGATTCTTTTCTCTGGACTTGTTTAAGTATACTGACAGCTTATCATGTCTGTTGG,149,101,122,0,98,38,92,178,99,153 +chr1.1_002111756|Alt_0002,chr1.1_002111756,GGTAGATAAATTTTACAGATGCTTAAAAGGTTTGCTAAATGGAATTCTGAGTATTGATCCTAAGAAAATCCATGTATAGAT,2,11,5,2,1,4,0,18,11,7 +chr1.1_002111756|Ref_0001,chr1.1_002111756,GGTAGATAAATTTTACAGATGCTTAAAAGGTTTGTTAAATGGAATTCTGAGTATTGATCCTAAGAAAATCCATGTATAGAT,115,176,163,149,179,242,136,61,167,56 +chr1.1_002341138|Alt_0002,chr1.1_002341138,GACTGTTGGAGTAATTTGCATATCAAAATATCTATATGTGATCACAGGGTTCTTTAAACAGAACATGGAGATTTTGACTTA,0,0,0,10,0,0,0,0,3,0 +chr1.1_002341138|Ref_0001,chr1.1_002341138,GACTGTTGGAGTAATTTGCATATCAAAATATCTATATGTGATCACAGGGTACTTTAAACAGAACATGGAGATTTTGACTTA,19,28,27,7,28,12,17,23,6,36 +chr1.1_002432574|Alt_0002,chr1.1_002432574,ATACATCCTTCCTATCCTGGATTATCACTGACCAGTTTTCAGGGATGTTTCATCAACAAAATCCTGTCTTATATTACATTC,519,411,331,668,420,405,462,247,216,0 +chr1.1_002432574|Ref_0001,chr1.1_002432574,ATACATCCTTCCTATCCTGGATTATCACTGACCACTTTTCAGGGATGTTTCATCAACAAAATCCTGTCTTATATTACATTC,289,332,203,92,268,223,230,368,448,479 +chr1.1_002703089|Alt_0002,chr1.1_002703089,CAACCACTTTGCAACCTTGCATGAAACTTTTATTTTCATCTGATATCCTAAACCCACCATTCGCACTGTAGAACCCACAAT,0,202,179,202,81,155,60,124,200,165 +chr1.1_002703089|Ref_0001,chr1.1_002703089,CAACCACTTTGCAACCTTGCATGAAACTTTTATCTTCATCTGATATCCTAAACCCACCATTCGCACTGTAGAACCCACAAT,306,172,119,44,177,120,117,167,145,120 +chr1.1_002798325|Alt_0002,chr1.1_002798325,TAGAAGTGTATTATATATATCTAACCTAGTATGTTATTTGCATTTGGACAAATTTGTAAAGGCATGGAGAAATTGGAAGGA,0,12,8,0,9,9,8,0,4,8 +chr1.1_002798325|Ref_0001,chr1.1_002798325,TAGAAGTGTATTATATATATCTAACCTAGTATTTTATTTGCATTTGGACAAATTTGTAAAGGCATGGAGAAATTGGAAGGA,8,17,10,13,5,8,4,19,5,17 +chr1.1_003103125|Alt_0002,chr1.1_003103125,CAGTGATAGCTTATCTCAAGTGATGTAGTTAATTTTTGTTCTCAAACTTTAATAGTAATGGTATTTAAAGTTCTACTTTGA,34,34,62,94,38,26,39,8,0,0 +chr1.1_003103125|Ref_0001,chr1.1_003103125,CAGTGATAGCTTATCTCAAGTGATGTAGTTAATTTTTGTTCTCAAACTATAATAGTAATGGTATTTAAAGTTCTACTTTGA,48,79,99,35,80,171,34,162,138,183 +chr1.1_003243094|Alt_0002,chr1.1_003243094,AAGGTAAGAACACAACCATTAATGTTATGTTTTTCTGTTTTGTCTTAATGTTTTTATTGATTAGTTACATAATGTCCCATA,9,4,4,16,5,18,8,4,0,0 +chr1.1_003243094|Ref_0001,chr1.1_003243094,AAGGTAAGAACACAACCATTAATGTTATGTTATTCTGTTTTGTCTTAATGTTTTTATTGATTAGTTACATAATGTCCCATA,8,12,12,0,10,11,7,17,16,17 +chr1.1_003329439|Alt_0002,chr1.1_003329439,GAACTAAGACCAACGTTTAAATACTAAGTTTATACTAATTAGGGTTTATTTTCTGGTTTGTAACACTGCATGTAAAAGTTA,1,1,0,0,3,6,1,5,5,8 +chr1.1_003329439|Ref_0001,chr1.1_003329439,GAACTAAGACCAACGTTTAAATACTAAGTTTATCCTAATTAGGGTTTATTTTCTGGTTTGTAACACTGCATGTAAAAGTTA,14,18,18,10,14,10,7,14,0,2 +chr1.1_003491884|Alt_0002,chr1.1_003491884,GAGGAAATCGACACTTTAGTTGATTATCTCATTAGCCGTGGTTTTGGCAAGAACTAATTATTAAGAGGTGATATACGATCA,0,138,95,0,167,37,71,0,209,63 +chr1.1_003491884|RefMatch_0002,chr1.1_003491884,GAGGAAATCGACACTTTAGTTGATTATCTCCTTAGCCATGGTTTTGGCAAGAACTAATTATTAAGAGGTG,0,0,0,0,0,0,0,1,0,0 +chr1.1_003491884|Ref_0001,chr1.1_003491884,GAGGAAATCGACACTTTAGTTGATTATCTCCTTAGCCGTGGTTTTGGCAAGAACTAATTATTAAGAGGTGATATACGATCA,219,142,116,201,0,169,88,311,66,161 +chr1.1_003613850|Alt_0002,chr1.1_003613850,CATGATCAACCACCAAGGAGGCAAACCCTTGATCAGATTGGATCTGGCGTGAACAGTGTTACAATGAGTGACCGTTCTGTA,2,0,0,636,0,0,0,2,330,0 +chr1.1_003613850|Ref_0001,chr1.1_003613850,CATGATCAACCACCAAGGAGGCAAACCCTTGATCAGATTGGATCTGGTGTGAACAGTGTTACAATGAGTGACCGTTCTGTA,1646,1541,992,593,1244,1149,1359,1970,846,1120 \ No newline at end of file diff --git a/inst/example_MADC_to_merge.csv b/inst/example_MADC_to_merge.csv new file mode 100644 index 0000000..1bb2e56 --- /dev/null +++ b/inst/example_MADC_to_merge.csv @@ -0,0 +1,36 @@ +AlleleID,CloneID,AlleleSequence,Sample_11,Sample_12,Sample_13,Sample_14,Sample_15,Sample_16,Sample_17,Sample_18,Sample_19,Sample_20 +chr1.1_001590881|Ref_0001,chr1.1_001590881,CTGTGAGAAGCACTTCATCTGAATTAAGCAATCCTTTTCCCCTAAGTAAGAGTTTGTAATAGGTATTATCAAACATTCTTG,0,0,0,20,9,17,16,14,6,5 +chr1.1_001938036|AltMatch_0003,chr1.1_001938036,CAGTGTTATCAGCCACACATGTAAATTGATGCTTTTATCTGGACTTGTTAAGTATACTGACAGCTTATC,48,0,0,34,36,33,0,26,0,0 +chr1.1_001938036|Alt_0002,chr1.1_001938036,CAGTGTTATCAGCCACACATGTAAATTGATGCTTTTCTCTGGACTTGTTTAAGTATACTGACAGCTTATCATGTCTGTTGG,39,0,0,0,75,42,83,0,76,35 +chr1.1_001938036|Ref_0001,chr1.1_001938036,CAGTGTTATCAGCCACACATGTAAATTGATTCTTTTCTCTGGACTTGTTTAAGTATACTGACAGCTTATCATGTCTGTTGG,35,149,134,145,37,75,52,106,66,95 +chr1.1_002111756|Alt_0002,chr1.1_002111756,GGTAGATAAATTTTACAGATGCTTAAAAGGTTTGCTAAATGGAATTCTGAGTATTGATCCTAAGAAAATCCATGTATAGAT,5,24,24,8,19,11,11,4,6,4 +chr1.1_002111756|Ref_0001,chr1.1_002111756,GGTAGATAAATTTTACAGATGCTTAAAAGGTTTGTTAAATGGAATTCTGAGTATTGATCCTAAGAAAATCCATGTATAGAT,55,62,53,167,68,89,164,124,106,113 +chr1.1_002341138|Alt_0002,chr1.1_002341138,GACTGTTGGAGTAATTTGCATATCAAAATATCTATATGTGATCACAGGGTTCTTTAAACAGAACATGGAGATTTTGACTTA,6,0,0,0,14,0,0,0,6,0 +chr1.1_002341138|Ref_0001,chr1.1_002341138,GACTGTTGGAGTAATTTGCATATCAAAATATCTATATGTGATCACAGGGTACTTTAAACAGAACATGGAGATTTTGACTTA,3,35,33,16,22,34,40,16,29,34 +chr1.1_002432574|Alt_0002,chr1.1_002432574,ATACATCCTTCCTATCCTGGATTATCACTGACCAGTTTTCAGGGATGTTTCATCAACAAAATCCTGTCTTATATTACATTC,634,0,1,386,419,430,674,313,398,216 +chr1.1_002432574|Ref_0001,chr1.1_002432574,ATACATCCTTCCTATCCTGGATTATCACTGACCACTTTTCAGGGATGTTTCATCAACAAAATCCTGTCTTATATTACATTC,73,466,530,274,293,264,106,177,254,433 +chr1.1_002703089|Alt_0002,chr1.1_002703089,CAACCACTTTGCAACCTTGCATGAAACTTTTATTTTCATCTGATATCCTAAACCCACCATTCGCACTGTAGAACCCACAAT,0,151,172,120,125,1,56,1,0,107 +chr1.1_002703089|Ref_0001,chr1.1_002703089,CAACCACTTTGCAACCTTGCATGAAACTTTTATCTTCATCTGATATCCTAAACCCACCATTCGCACTGTAGAACCCACAAT,193,127,129,257,289,294,178,200,275,198 +chr1.1_002798325|Alt_0002,chr1.1_002798325,TAGAAGTGTATTATATATATCTAACCTAGTATGTTATTTGCATTTGGACAAATTTGTAAAGGCATGGAGAAATTGGAAGGA,9,2,0,9,8,0,0,0,6,2 +chr1.1_002798325|Ref_0001,chr1.1_002798325,TAGAAGTGTATTATATATATCTAACCTAGTATTTTATTTGCATTTGGACAAATTTGTAAAGGCATGGAGAAATTGGAAGGA,3,10,10,11,7,13,18,20,5,15 +chr1.1_003103125|Alt_0002,chr1.1_003103125,CAGTGATAGCTTATCTCAAGTGATGTAGTTAATTTTTGTTCTCAAACTTTAATAGTAATGGTATTTAAAGTTCTACTTTGA,35,0,0,29,60,40,40,39,15,22 +chr1.1_003103125|Ref_0001,chr1.1_003103125,CAGTGATAGCTTATCTCAAGTGATGTAGTTAATTTTTGTTCTCAAACTATAATAGTAATGGTATTTAAAGTTCTACTTTGA,82,188,163,73,85,91,109,118,109,90 +chr1.1_003243094|Alt_0002,chr1.1_003243094,AAGGTAAGAACACAACCATTAATGTTATGTTTTTCTGTTTTGTCTTAATGTTTTTATTGATTAGTTACATAATGTCCCATA,2,0,5,18,6,27,0,12,8,3 +chr1.1_003243094|Ref_0001,chr1.1_003243094,AAGGTAAGAACACAACCATTAATGTTATGTTATTCTGTTTTGTCTTAATGTTTTTATTGATTAGTTACATAATGTCCCATA,21,38,17,8,11,6,25,5,8,13 +chr1.1_003329439|Alt_0002,chr1.1_003329439,GAACTAAGACCAACGTTTAAATACTAAGTTTATACTAATTAGGGTTTATTTTCTGGTTTGTAACACTGCATGTAAAAGTTA,6,6,3,3,3,4,1,1,3,2 +chr1.1_003329439|Ref_0001,chr1.1_003329439,GAACTAAGACCAACGTTTAAATACTAAGTTTATCCTAATTAGGGTTTATTTTCTGGTTTGTAACACTGCATGTAAAAGTTA,1,5,3,16,15,13,21,22,7,5 +chr1.1_003491884|Alt_0002,chr1.1_003491884,GAGGAAATCGACACTTTAGTTGATTATCTCATTAGCCGTGGTTTTGGCAAGAACTAATTATTAAGAGGTGATATACGATCA,108,69,56,113,81,59,151,39,88,85 +chr1.1_003491884|RefMatch_0002,chr1.1_003491884,GAGGAAATCGACACTTTAGTTGATTATCTCCTTAGCCATGGTTTTGGCAAGAACTAATTATTAAGAGGTG,0,0,0,0,0,0,0,1,1,1 +chr1.1_003491884|Ref_0001,chr1.1_003491884,GAGGAAATCGACACTTTAGTTGATTATCTCCTTAGCCGTGGTTTTGGCAAGAACTAATTATTAAGAGGTGATATACGATCA,50,178,217,135,151,143,57,165,128,131 +chr1.1_003613850|Alt_0002,chr1.1_003613850,CATGATCAACCACCAAGGAGGCAAACCCTTGATCAGATTGGATCTGGCGTGAACAGTGTTACAATGAGTGACCGTTCTGTA,496,1,946,0,0,1,0,0,319,749 +chr1.1_003613850|Ref_0001,chr1.1_003613850,CATGATCAACCACCAAGGAGGCAAACCCTTGATCAGATTGGATCTGGTGTGAACAGTGTTACAATGAGTGACCGTTCTGTA,555,1491,872,1422,1346,1464,1089,812,951,695 +chr1.1_003712477|Alt_0002,chr1.1_003712477,TGATTTTAGAGCTTACCACAAATTATAGCATGTGAATAAATTTCACTCATTTCGAATGCACAAACTTTCCTGTAATATCTA,47,43,28,63,49,66,0,49,37,25 +chr1.1_003712477|Ref_0001,chr1.1_003712477,TGATTTTAGAGCTTACCACAAATTATAGCATGTGAATAAATTTCACTCATTTTGAATGCACAAACTTTCCTGTAATATCTA,16,27,33,42,39,23,59,9,23,13 +chr1.1_003898103|Alt_0002,chr1.1_003898103,GTCCGAAAGAAGAAAAAGTGTCATGTAAAGCTTTGTGATCAATCGTCTTATCCAAATTCTGCACAACCAACAACAGCATAA,35,61,51,67,63,24,126,36,28,46 +chr1.1_003898103|Ref_0001,chr1.1_003898103,GTCCGAAAGAAGAAAAAGTGTCATGTAAAGCTTTGTGATCAATTGTCTTATCCAAATTCTGCACAACCAACAACAGCATAA,72,70,38,87,35,101,48,133,56,26 +chr1.1_004102347|AltMatch_0001,chr1.1_004102347,GACTTTGCTTCACAAGATTGGTACATACTGTTATATTTCATGAACTTTTTGTTAGAATGTATTCCATTTG,37,22,71,0,80,30,53,0,36,32 +chr1.1_004102347|Alt_0002,chr1.1_004102347,GACTTTGCTTCACAAGATTGGTACATACTGTTATATTTCATGAACTTTTTGTTTGAATGTATTCCATTTGTCTCTTGTCAG,0,0,0,0,0,0,0,0,0,0 +chr1.1_004102347|RefMatch_0002,chr1.1_004102347,GACTTTGCTTCACAAGATTGGTACATACTGTTATATTTCATGAACTTTCTGCTTGAATGTATTCCATTTG,0,0,0,0,67,0,0,0,0,0 +chr1.1_004102347|RefMatch_0001,chr1.1_004102347,GACTTTGCTTCACAAGATTGGTACATACTGTTATATTTCATGAACTTTCTGTTAGAATGTATTCCATTTG,20,0,37,0,1,55,0,0,35,57 +chr1.1_004102347|Ref_0001,chr1.1_004102347,GACTTTGCTTCACAAGATTGGTACATACTGTTATATTTCATGAACTTTCTGTTTGAATGTATTCCATTTGTCTCTTGTCAG,19,109,49,195,56,96,81,139,91,79 +chr1.1_004315961|Alt_0002,chr1.1_004315961,GATGGAGTATGGAGAAGAAGTTAATTAAGGGCACTTTGGCTTTCCCTTAGAGTTCTTCATGTCCCTATAGCAAGGGCACTC,0,0,0,0,0,0,0,0,0,0 \ No newline at end of file diff --git a/inst/example_SNPs_DArTag-probe-design_f180bp.botloci b/inst/example_SNPs_DArTag-probe-design_f180bp.botloci new file mode 100644 index 0000000..bd923fb --- /dev/null +++ b/inst/example_SNPs_DArTag-probe-design_f180bp.botloci @@ -0,0 +1,101 @@ +chr1.1_000194324 +chr1.1_000309952 +chr1.1_000452961 +chr1.1_001169609 +chr1.1_001590881 +chr1.1_001938036 +chr1.1_002111756 +chr1.1_002341138 +chr1.1_002432574 +chr1.1_002703089 +chr1.1_003103125 +chr1.1_003243094 +chr1.1_003329439 +chr1.1_003491884 +chr1.1_003613850 +chr1.1_004436755 +chr1.1_004538231 +chr1.1_004964967 +chr1.1_005027893 +chr1.1_005509457 +chr1.1_005850336 +chr1.1_006342913 +chr1.1_006491042 +chr1.1_006927231 +chr1.1_007233177 +chr1.1_007349949 +chr1.1_007830610 +chr1.1_008362856 +chr1.1_009175857 +chr1.1_009654615 +chr1.1_009788520 +chr1.1_010059811 +chr1.1_010182954 +chr1.1_010513693 +chr1.1_010654139 +chr1.1_010740435 +chr1.1_011053888 +chr1.1_011550587 +chr1.1_011602715 +chr1.1_012607158 +chr1.1_012952616 +chr1.1_013166244 +chr1.1_013536075 +chr1.1_014100127 +chr1.1_014207906 +chr1.1_014290088 +chr1.1_014788595 +chr1.1_015044468 +chr1.1_015424890 +chr1.1_016006885 +chr1.1_016221768 +chr1.1_016563045 +chr1.1_016976894 +chr1.1_017863839 +chr1.1_018083264 +chr1.1_018128065 +chr1.1_018362099 +chr1.1_018698343 +chr1.1_018789059 +chr1.1_019009023 +chr1.1_019232221 +chr1.1_019387175 +chr1.1_019780298 +chr1.1_020310833 +chr1.1_020548930 +chr1.1_020860458 +chr1.1_021161903 +chr1.1_023241568 +chr1.1_024489859 +chr1.1_024760634 +chr1.1_025688638 +chr1.1_025728959 +chr1.1_026050142 +chr1.1_026502181 +chr1.1_026940687 +chr1.1_027461652 +chr1.1_027966972 +chr1.1_028084165 +chr1.1_028687110 +chr1.1_028857948 +chr1.1_028955804 +chr1.1_029326140 +chr1.1_029584457 +chr1.1_030458048 +chr1.1_030744456 +chr1.1_030969636 +chr1.1_031360007 +chr1.1_031442927 +chr1.1_031907509 +chr1.1_032107042 +chr1.1_032180745 +chr1.1_034284365 +chr1.1_034579746 +chr1.1_034663420 +chr1.1_035085053 +chr1.1_035253375 +chr1.1_035606739 +chr1.1_035758205 +chr1.1_036130046 +chr1.1_036517797 + diff --git a/inst/example_allele_db.fa b/inst/example_allele_db.fa new file mode 100644 index 0000000..6be6c1c --- /dev/null +++ b/inst/example_allele_db.fa @@ -0,0 +1,1184 @@ +>chr1.1_000194324|AltMatch_0001 +CGAAATAATAACCCAAGTTCTGCCAGTTTATGTTAAAACTTTTTTTACAAGGTACAAGTTCGGTGACAACTTAACAAGTAA +>chr1.1_000194324|Alt_0002 +CGAAATAATAACCCAAGTTCTGCCAGTTTATGTTAAAACTTTTCTTACAAGGTACAAGTTCGGTGACAACTTAACAAGTAA +>chr1.1_000194324|Ref_0001 +CGAAATAATAACCCAAGTTCTGCCAGTTTATGTTAAAACTTTTCTTACATGGTACAAGTTCGGTGACAACTTAACAAGTAA +>chr1.1_000309952|AltMatch_0001 +TGGTATTGTATTAGATGAGATATTCTAACTTGTAAGGTAGAAATCTTGACCACTTATAAACACATATTCATATCATATGTA +>chr1.1_000309952|Alt_0002 +TGGTATTGTATTAGATGAGATATTCTAACTTGTAAGATTGAGATCTTGACCACTTATAAACACATATTCATATCATATGTA +>chr1.1_000309952|Ref_0001 +TGGTATTGTATTAGATGAGATATTCTAACTTGTAAGATTGAGATCTCGACCACTTATAAACACATATTCATATCATATGTA +>chr1.1_000452961|Alt_0002 +TTACGAGATCGCGAAGTTCGTTCCTTTCTTTATCTTTCTTCTCTTTTACCCGACCGGCTCCCTGCAGACCAGAAAGCCCAA +>chr1.1_000452961|Ref_0001 +TTACGAGATCGCGAAGCTCGTTCCTTTCTTTATCTTTCTTCTCTTTTACCCGACCGGCTCCCTGCAGACCAGAAAGCCCAA +>chr1.1_000532584|Alt_0002 +CAACGGAACATATAAAGATATCCACTTCTCTTGGAGCTTGATGATACTTGTAATGTTGGGGATTTGTGTTTTGCAGGATTT +>chr1.1_000532584|RefMatch_0001 +CAACGGAACATATAAAGATATCCACTTCTCTTGGAGCTTGATAATACTTATAATGTTGGGGATTTGTGTTTTGCAGGATTT +>chr1.1_000532584|RefMatch_0002 +CAACGGAACATATAAAGATATCCACTTCTCTTGGGGCTTGATAATACTTATAATGTTGGGGATTTGTGTTTTGCAGGATTT +>chr1.1_000532584|RefMatch_0003 +CAACGGAACATATAAAGATATCCACTTTTCTCGGAGCTTGATAATACTTATAATGTTGGGGATTTGTGTTTTGCAGGATTT +>chr1.1_000532584|Ref_0001 +CAACGGAACATATAAAGATATCCACTTCTCTTGGAGCTTGATGATACTTATAATGTTGGGGATTTGTGTTTTGCAGGATTT +>chr1.1_000735393|Alt_0002 +GACTCTTGGAAGGAAAATGGTTTTTCTAGGTAATTAAACTTCAATCAAAGTTACATATTTGACTCACTTCACTATTCTAAA +>chr1.1_000735393|Ref_0001 +GACTCTTGGAAGGAAAATGGTTTTTCTAGGTAGTTAAACTTCAATCAAAGTTACATATTTGACTCACTTCACTATTCTAAA +>chr1.1_000837330|Alt_0002 +CCTCTATCTAATAGAGAATATTGATTGGCTGAATGTTGACCATATTCCATGTACCCACTAGGGTTACCCCGTGGAGTCCAA +>chr1.1_000837330|RefMatch_0001 +CCTCTATCTAATAGAGAATATTGATTGGCTGAATGTTGACCATATTCCCTATACCCACTAGGGTTACCCCGTGGAGTCCAA +>chr1.1_000837330|Ref_0001 +CCTCTATCTAATAGAGAATATTGATTGGCTGAATGTTGACCATATTCCCTGTACCCACTAGGGTTACCCCGTGGAGTCCAA +>chr1.1_000915014|Alt_0002 +CCAGGCTTCTATATATACAATGATCAGATATGTTAAACCTAAGCTGCTCAGTGCTCCTTAACCCTAAGACACACAGAACCT +>chr1.1_000915014|Ref_0001 +CCAGGCTTCTATATATACAATGATCAGATATGTTAAACCTAAGCTGCTCGGTGCTCCTTAACCCTAAGACACACAGAACCT +>chr1.1_001169609|AltMatch_0001 +CAATGATCTCTGCGCAACTGCACCTTTAAAATCTTCCTGCCTACATAGTACTTTTGGTTTTTGGAACCCAAGTACCGTATT +>chr1.1_001169609|Alt_0002 +CAATGATCTCTGCGCAACTGCACCTTTAAAATCTTCCTGCCTGACATAGTACTTTTGGTTTTTGGAACCCAAGTACCGTAT +>chr1.1_001169609|RefMatch_0001 +CAATGATCTCTGCGCAACTGCACCTTTTAAATCTTCCTACCTGACATAGTACTTTTGGTTTTTGGAACCCAAGTACCGTAT +>chr1.1_001169609|RefMatch_0002 +CAATGATCTCTGCGCAACTGCACCTTTTAAATCTTCCTGCCTGACAAAGTACTTTTGGTTTTTGGAACCCAAGTACCGTAT +>chr1.1_001169609|RefMatch_0003 +CAATGATCTCTGCGCAACTGCACCTTTTAAATCTTCCTGCCTGACATAATACTTTTGGTTTTTGGAACCCAAGTACCGTAT +>chr1.1_001169609|Ref_0001 +CAATGATCTCTGCGCAACTGCACCTTTTAAATCTTCCTGCCTGACATAGTACTTTTGGTTTTTGGAACCCAAGTACCGTAT +>chr1.1_001494903|Alt_0002 +TTGGTGCAGTGTTGATAGTAGCTGGACTATACTTTGTGTTGTGGGGTAAAAGTGAAGAGAAGAAATTATTTGCAAAGGAAC +>chr1.1_001494903|Ref_0001 +TTGGTGCAGTGTTGATAGTAGCTGGACTATACTTTGTGCTGTGGGGTAAAAGTGAAGAGAAGAAATTATTTGCAAAGGAAC +>chr1.1_001590881|Alt_0002 +CTGTGAGAAGCACTTCATCTGAATTAAGCAATCCTTTTCCCGTAAGTAAGAGTTTGTAATAGGTATTATCAAACATTCTTG +>chr1.1_001590881|Ref_0001 +CTGTGAGAAGCACTTCATCTGAATTAAGCAATCCTTTTCCCCTAAGTAAGAGTTTGTAATAGGTATTATCAAACATTCTTG +>chr1.1_001938036|AltMatch_0001 +CAGTGTTATCAGCCACACATGTAAATTGATGCTTTTATCTGGACTTGTTAAGTAATACTGACAGCTTATCATGTCTGTTGG +>chr1.1_001938036|AltMatch_0002 +CAGTGTTATCAGCCACACATGTAAATTGATGCTTTTCTCTGGACTTGTTAAGTAATACTGACAGCTTATCATGTCTGTTGG +>chr1.1_001938036|Alt_0002 +CAGTGTTATCAGCCACACATGTAAATTGATGCTTTTCTCTGGACTTGTTTAAGTATACTGACAGCTTATCATGTCTGTTGG +>chr1.1_001938036|Ref_0001 +CAGTGTTATCAGCCACACATGTAAATTGATTCTTTTCTCTGGACTTGTTTAAGTATACTGACAGCTTATCATGTCTGTTGG +>chr1.1_002111756|Alt_0002 +GGTAGATAAATTTTACAGATGCTTAAAAGGTTTGCTAAATGGAATTCTGAGTATTGATCCTAAGAAAATCCATGTATAGAT +>chr1.1_002111756|Ref_0001 +GGTAGATAAATTTTACAGATGCTTAAAAGGTTTGTTAAATGGAATTCTGAGTATTGATCCTAAGAAAATCCATGTATAGAT +>chr1.1_002341138|Alt_0002 +GACTGTTGGAGTAATTTGCATATCAAAATATCTATATGTGATCACAGGGTTCTTTAAACAGAACATGGAGATTTTGACTTA +>chr1.1_002341138|Ref_0001 +GACTGTTGGAGTAATTTGCATATCAAAATATCTATATGTGATCACAGGGTACTTTAAACAGAACATGGAGATTTTGACTTA +>chr1.1_002432574|AltMatch_0001 +ATACATCCTTCCTATCCTGGATTATCACTGACCAGTTTTCGGGGATGTTTCATCAACAAAATCCTGTCTTATATTACATTC +>chr1.1_002432574|Alt_0002 +ATACATCCTTCCTATCCTGGATTATCACTGACCAGTTTTCAGGGATGTTTCATCAACAAAATCCTGTCTTATATTACATTC +>chr1.1_002432574|Ref_0001 +ATACATCCTTCCTATCCTGGATTATCACTGACCACTTTTCAGGGATGTTTCATCAACAAAATCCTGTCTTATATTACATTC +>chr1.1_002703089|Alt_0002 +CAACCACTTTGCAACCTTGCATGAAACTTTTATTTTCATCTGATATCCTAAACCCACCATTCGCACTGTAGAACCCACAAT +>chr1.1_002703089|RefMatch_0001 +CAACCACTTTGCAACCTTGCATGAAACTTTTATCATCATCTGATATCCTAAACCCACCATTCGCACTGTAGAACCCACAAT +>chr1.1_002703089|RefMatch_0002 +CAACCACTTTGCAACCTTGCATGAAACTTTTATCTTCACCTGATATCCTAAACCCACCATTCGCACTGTAGAACCCACAAT +>chr1.1_002703089|Ref_0001 +CAACCACTTTGCAACCTTGCATGAAACTTTTATCTTCATCTGATATCCTAAACCCACCATTCGCACTGTAGAACCCACAAT +>chr1.1_002798325|Alt_0002 +TAGAAGTGTATTATATATATCTAACCTAGTATGTTATTTGCATTTGGACAAATTTGTAAAGGCATGGAGAAATTGGAAGGA +>chr1.1_002798325|Ref_0001 +TAGAAGTGTATTATATATATCTAACCTAGTATTTTATTTGCATTTGGACAAATTTGTAAAGGCATGGAGAAATTGGAAGGA +>chr1.1_003103125|Alt_0002 +CAGTGATAGCTTATCTCAAGTGATGTAGTTAATTTTTGTTCTCAAACTTTAATAGTAATGGTATTTAAAGTTCTACTTTGA +>chr1.1_003103125|Ref_0001 +CAGTGATAGCTTATCTCAAGTGATGTAGTTAATTTTTGTTCTCAAACTATAATAGTAATGGTATTTAAAGTTCTACTTTGA +>chr1.1_003243094|Alt_0002 +AAGGTAAGAACACAACCATTAATGTTATGTTTTTCTGTTTTGTCTTAATGTTTTTATTGATTAGTTACATAATGTCCCATA +>chr1.1_003243094|Ref_0001 +AAGGTAAGAACACAACCATTAATGTTATGTTATTCTGTTTTGTCTTAATGTTTTTATTGATTAGTTACATAATGTCCCATA +>chr1.1_003329439|Alt_0002 +GAACTAAGACCAACGTTTAAATACTAAGTTTATACTAATTAGGGTTTATTTTCTGGTTTGTAACACTGCATGTAAAAGTTA +>chr1.1_003329439|Ref_0001 +GAACTAAGACCAACGTTTAAATACTAAGTTTATCCTAATTAGGGTTTATTTTCTGGTTTGTAACACTGCATGTAAAAGTTA +>chr1.1_003491884|Alt_0002 +GAGGAAATCGACACTTTAGTTGATTATCTCATTAGCCGTGGTTTTGGCAAGAACTAATTATTAAGAGGTGATATACGATCA +>chr1.1_003491884|RefMatch_0001 +GAGGAAATCGACACTTTAGTTGATTATCTCCTTACCCGTGGTTTTGGCAAGAACTAATTATTAAGAGGTGATATACGATCA +>chr1.1_003491884|Ref_0001 +GAGGAAATCGACACTTTAGTTGATTATCTCCTTAGCCGTGGTTTTGGCAAGAACTAATTATTAAGAGGTGATATACGATCA +>chr1.1_003613850|AltMatch_0001 +CATGATCAACCACCAAGGAGGCAAACCCTTGATCAGATTGGATCTGGCATGAACAGTGTTACAATGAGTGACCGTTCTGTA +>chr1.1_003613850|Alt_0002 +CATGATCAACCACCAAGGAGGCAAACCCTTGATCAGATTGGATCTGGCGTGAACAGTGTTACAATGAGTGACCGTTCTGTA +>chr1.1_003613850|RefMatch_0001 +CATGATCAACCACCAAGGAGGCAAACCCTCGATCAGATTGGATCTGGTGTGAACAGTGTTACAATGAGTGACCGTTCTGTA +>chr1.1_003613850|RefMatch_0002 +CATGATCAACCACCAAGGAGGCAAACCCTTGATCAGATTGGATCCGGTGTGAACAGTGTTACAATGAGTGACCGTTCTGTA +>chr1.1_003613850|RefMatch_0003 +CATGATCAACCACCAAGGAGGCAAACCCTTGATCAGATTGGATCTGGTATGAACAGTGTTACAATGAGTGACCGTTCTGTA +>chr1.1_003613850|RefMatch_0004 +CATGATCAACCACCAAGGAGGCAAACCCTTGATCAGATTGGATCTGGTGTGAATAGTGTTACAATGAGTGACCGTTCTGTA +>chr1.1_003613850|Ref_0001 +CATGATCAACCACCAAGGAGGCAAACCCTTGATCAGATTGGATCTGGTGTGAACAGTGTTACAATGAGTGACCGTTCTGTA +>chr1.1_003712477|Alt_0002 +TGATTTTAGAGCTTACCACAAATTATAGCATGTGAATAAATTTCACTCATTTCGAATGCACAAACTTTCCTGTAATATCTA +>chr1.1_003712477|Ref_0001 +TGATTTTAGAGCTTACCACAAATTATAGCATGTGAATAAATTTCACTCATTTTGAATGCACAAACTTTCCTGTAATATCTA +>chr1.1_003898103|Alt_0002 +GTCCGAAAGAAGAAAAAGTGTCATGTAAAGCTTTGTGATCAATCGTCTTATCCAAATTCTGCACAACCAACAACAGCATAA +>chr1.1_003898103|Ref_0001 +GTCCGAAAGAAGAAAAAGTGTCATGTAAAGCTTTGTGATCAATTGTCTTATCCAAATTCTGCACAACCAACAACAGCATAA +>chr1.1_004102347|AltMatch_0001 +GACTTTGCTTCACAAGATTGGTACATACTGTTATATTTCATGAACTTTTTGTTAGAATGTATTCCATTTGTCTCTTGTCAG +>chr1.1_004102347|Alt_0002 +GACTTTGCTTCACAAGATTGGTACATACTGTTATATTTCATGAACTTTTTGTTTGAATGTATTCCATTTGTCTCTTGTCAG +>chr1.1_004102347|RefMatch_0001 +GACTTTGCTTCACAAGATTGGTACATACTGTTATATTTCATGAACTTTCTGTTAGAATGTATTCCATTTGTCTCTTGTCAG +>chr1.1_004102347|Ref_0001 +GACTTTGCTTCACAAGATTGGTACATACTGTTATATTTCATGAACTTTCTGTTTGAATGTATTCCATTTGTCTCTTGTCAG +>chr1.1_004315961|Alt_0002 +GATGGAGTATGGAGAAGAAGTTAATTAAGGGCACTTTGGCTTTCCCTTAGAGTTCTTCATGTCCCTATAGCAAGGGCACTC +>chr1.1_004315961|Ref_0001 +GATGGAGTATGGAGAAGAAGTTAATTAAGGGCATTTTGGCTTTCCCTTAGAGTTCTTCATGTCCCTATAGCAAGGGCACTC +>chr1.1_004436755|Alt_0002 +GCACCAATGTTGGTGGTTTAATTACTGCATTTCTCCTGCTTTATTGTATCTTGATAGATATATTATTGTAATATTTTGGAA +>chr1.1_004436755|RefMatch_0001 +GCACCAATGTTGGTGGTTTAATTACTGCATTTCTCCTGCTTGATTCTAACTTGATAGATATATTATTGTAATATTTTGGAA +>chr1.1_004436755|Ref_0001 +GCACCAATGTTGGTGGTTTAATTACTGCATTTCTCCTGCTTTATTGTAACTTGATAGATATATTATTGTAATATTTTGGAA +>chr1.1_004538231|Alt_0002 +TCTGATCAGAAGGTACTATTGCCGTGCCTTTGATACGAGTCCAAATCTCCTGCCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004538231|RefMatch_0001 +TCTGATCAGAAGGTACTATTGCCGTGCCTCTGATACGAGTCCAAATCTCCTACCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004538231|RefMatch_0002 +TCTGATCAGAAGGTACTATTGCCGTGCCTTTGACACGAGTCCAAATCTCCTACCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004538231|RefMatch_0003 +TCTGATCAGAAGGTACTATTGCCGTGCCTTTGATAAGAGTCCAAATCTCCTACCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004538231|RefMatch_0004 +TCTGATCAGAAGGTACTATTGCCGTGCCTTTGATACAAGTCCAAATCTCCTACCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004538231|RefMatch_0005 +TCTGATCAGAAGGTACTATTGCCGTGCCTTTGATACGAATCCAAATCTCCTACCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004538231|RefMatch_0006 +TCTGATCAGAAGGTACTATTGCCGTGCCTTTGATACGAGTCCAAATCTCTTACCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004538231|RefMatch_0007 +TCTGATCAGAAGGTACTATTGCCGTGCCTTTGATACGAGTCCAAATGTCCTACCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004538231|RefMatch_0008 +TCTGATCAGAAGGTACTATTGCCGTGCCTTTGATACGAGTCCAGATCTCCTACCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004538231|RefMatch_0009 +TCTGATCAGAAGGTACTATTGCCGTGCCTTTGATACTAGTCCAAATCTCCTACCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004538231|Ref_0001 +TCTGATCAGAAGGTACTATTGCCGTGCCTTTGATACGAGTCCAAATCTCCTACCTCCCAAGTTTAGCTTCAACACAAGTGC +>chr1.1_004614862|AltMatch_0001 +GATAGAGTAGACTAGTCATGATGTAATTAAACTATTCTATGTTTCACAAGTCTTGGAGCTCGAGTTCACAACTAATCTAGT +>chr1.1_004614862|Alt_0002 +GATAGAGTAGACTAGTCATGATGTAATTAAACTATTCTATGTTTCACGAGTCTTGGAGCTCGAGTTCACAACTAATCTAGT +>chr1.1_004614862|RefMatch_0001 +GATAGAGTAGACTAGTCATGATGTAATTAAACTATTCTATGTTTCTCAAGTCTTGGAGCTCGAGTTCACAACTAATCTAGT +>chr1.1_004614862|Ref_0001 +GATAGAGTAGACTAGTCATGATGTAATTAAACTATTCTATGTTTCTCGAGTCTTGGAGCTCGAGTTCACAACTAATCTAGT +>chr1.1_004757298|Alt_0002 +TCTTGCTCTTCTAGAAACTTTCAAACTCGCCGAGTCTCTCCAAAACAACCTTCTTAACCTCTCTTCAAAGCTATCAACAGA +>chr1.1_004757298|RefMatch_0001 +TCTTGCTCTTCTAGAAACTTTCAAACTCGCCGAATCTCTCCAAAACAATCTTCTTAACCTCTCTTCAAAGCTATCAACAGA +>chr1.1_004757298|RefMatch_0002 +TCTTGCTCTTCTAGAAACTTTCAAACTCGCCGAGTCTCTCCAAAACAATCTCCTTAACCTCTCTTCAAAGCTATCAACAGA +>chr1.1_004757298|RefMatch_0003 +TCTTGCTCTTCTAGAAACTTTCAAACTCGCCGAGTCTCTTCAAAACAATCTTCTTAACCTCTCTTCAAAGCTATCAACAGA +>chr1.1_004757298|Ref_0001 +TCTTGCTCTTCTAGAAACTTTCAAACTCGCCGAGTCTCTCCAAAACAATCTTCTTAACCTCTCTTCAAAGCTATCAACAGA +>chr1.1_004964967|AltMatch_0001 +GCAATTTCTGATTTTCAACAACAAGAAGGTCATTAATCTCTTCATTGTAAATCTCCATGTATGAAACTCGAATTAAAAACT +>chr1.1_004964967|Alt_0002 +GCAATTTCTGATTTTCAACAACAAGAAGGTCATTAATCTCTTCATTATAAATCTCCATGTATGAAACTCGAATTAAAAACT +>chr1.1_004964967|RefMatch_0001 +GCAATTTCTGATTTTCAACAACAAGAAGGTCATTAATATCTTCGTTATAAATCTCCATGTATGAAACTCGAATTAAAAACT +>chr1.1_004964967|Ref_0001 +GCAATTTCTGATTTTCAACAACAAGAAGGTCATTAATCTCTTCGTTATAAATCTCCATGTATGAAACTCGAATTAAAAACT +>chr1.1_005027893|Alt_0002 +GATCTTGCAATGTTCGTGATAATAATTTGGTTAGGATCTCTCATTCTCCACAAAATATGGATTGAGATTGATATCTATGTT +>chr1.1_005027893|Ref_0001 +GATCTTGCAATGTTCGTGATAATAATTTGGTTAGGATCTCTCATTCTCCACAGAATATGGATTGAGATTGATATCTATGTT +>chr1.1_005278309|Alt_0002 +GTAATGATGTCGAGGAGACCTGGAACTTCTTCTAGAAGATTCGGTGATACCAAATCCAAATCGTCTCCAGTTTTGTCAATT +>chr1.1_005278309|Ref_0001 +GTAATGATGTCGAGGAGACCTGGAACTTCTTCTAGAAGATTCGGCGATACCAAATCCAAATCGTCTCCAGTTTTGTCAATT +>chr1.1_005509457|Alt_0002 +GATATCTACCATTCTAGTACTCATCATGCATATCATTTTTTCGCATAAATCTTAACATTATTGTTCCAGGAGGATTGGAAT +>chr1.1_005509457|RefMatch_0001 +GATATCTACCATTCTAGTACTCATCATGCATATCATTTTTTCTCATATATCTTAACATTATTGTTCCAGGAGGATTGGAAT +>chr1.1_005509457|Ref_0001 +GATATCTACCATTCTAGTACTCATCATGCATATCATTTTTTCTCATAAATCTTAACATTATTGTTCCAGGAGGATTGGAAT +>chr1.1_005618685|Alt_0002 +GATGTTCCTGGCTGATAAACACCTTCAATATTTAATTTTATACACATGTTTATCCACTTTATTTTTCTCTCATATAAACAG +>chr1.1_005618685|Ref_0001 +GATGTTCCTGGCTGATAAACACCTTCATTATTTAATTTTATACACATGTTTATCCACTTTATTTTTCTCTCATATAAACAG +>chr1.1_005850336|Alt_0002 +GGAGTGTGCATATGGTTATCTATCTTTGTAGTTAGTAATGCCTATCATTTGACCAACAGCAGAATTCACATTATATTAAAA +>chr1.1_005850336|RefMatch_0001 +GGAGTGTGCATATGGTTATCTATCTTTGTAGTTGGTAATGCCTATCATTTGTCCAACAGCAGAATTCACATTATATTAAAA +>chr1.1_005850336|Ref_0001 +GGAGTGTGCATATGGTTATCTATCTTTGTAGTTAGTAATGCCTATCATTTGTCCAACAGCAGAATTCACATTATATTAAAA +>chr1.1_006072575|AltMatch_0001 +CCTATAGATCAAAGCTATACCAAACTCTGACAAACAATCCATTTTAACTTCTTTATAACATCAACCATCCAATACTCCATA +>chr1.1_006072575|AltMatch_0002 +CCTATAGATCAAAGCTATACCAAACTCTGACAAACATTCCATTTTTAACTTCTTTATAACATCAACCATCCAATACTCCAT +>chr1.1_006072575|Alt_0002 +CCTATAGATCAAAGCTATACCAAACTCTGACAAACATTCCATTTTAACTTCTTTATAACATCAACCATCCAATACTCCATA +>chr1.1_006072575|Ref_0001 +CCTATAGATCAAAGCTATACCAAACTCTGGCAAACATTCCATTTTAACTTCTTTATAACATCAACCATCCAATACTCCATA +>chr1.1_006263297|AltMatch_0001 +CTACTTTCACTGTGCTGCTTAGTCCTTCGATGTTTTTCGGTATCAGTTAATGTCTAGTATAAACTGCATGTTATACTTTCT +>chr1.1_006263297|AltMatch_0002 +CTACTTTCACTGTGCTGCTTAGTCCTTTGATGTTTTTCGGTATCAGTTAATGTCTAGTATAAACTGCATGTTATACTTTCT +>chr1.1_006263297|Alt_0002 +CTACTTTCACTGTGCTGCTTAGTCCTTCGTTGTTTTTCGGTATCAGTTAATGTATAGTATAAACTGCATGTTATACTTTCT +>chr1.1_006263297|Ref_0001 +CTACTTTCACTGTGCTGCTTAGTCCTTCGTTGTTTTTCGGTATCAGTCAATGTATAGTATAAACTGCATGTTATACTTTCT +>chr1.1_006342913|Alt_0002 +CAATTTGTTCAATTTGCTTGTTTTGTTGATCTTCTGTAGGAATCTTTCGTCAAACAACCTTCAGGGTCCCATTCCAATTGA +>chr1.1_006342913|RefMatch_0001 +CAATTTGTTCAATTTGCTTGTTTTGTTGGTCTTCTGTAGGAATCTTTCATCAAACAACCTTCAGGGTCCCATTCCAATTGA +>chr1.1_006342913|Ref_0001 +CAATTTGTTCAATTTGCTTGTTTTGTTGGTCTTCTGTAGGAATCTTTCGTCAAACAACCTTCAGGGTCCCATTCCAATTGA +>chr1.1_006491042|Alt_0002 +CATGTTGGATGATATATATACCAAGTCTAATAATTTTTGGACGGTCTTTGCAGGGAAGATCAAGGAGACCTCAGCATTTTT +>chr1.1_006491042|RefMatch_0001 +CATGTTGGATGATATATATACCAAGTCTAATAATTTTTGGATGATCTTTGCAGGGAAGATCAAGGAGACCTCAGCATTTTT +>chr1.1_006491042|Ref_0001 +CATGTTGGATGATATATATACCAAGTCTAATAATTTTTGGACGATCTTTGCAGGGAAGATCAAGGAGACCTCAGCATTTTT +>chr1.1_006660525|AltMatch_0001 +ACAACATTTGGAATACCTGACATACCCTCAAACTCATTCTTAATTTTTCTCAAAGAAGCATCATTAGGCCATTGAAGATAC +>chr1.1_006660525|Alt_0002 +ACAACATTTGGAATACCTGACATACCCTCAAATTCATTCTTAATTTTTCTCAAAGAAGCATCATTAGGCCATTGAAGATAC +>chr1.1_006660525|RefMatch_0001 +ACAACATTTGGAATACCTGACATACCCTCAAACTCATTTTTAATTTTTCTCAAAGAAGCATCATTAGGCCATTGAAGATAC +>chr1.1_006660525|Ref_0001 +ACAACATTTGGAATACCTGACATACCCTCAAATTCATTTTTAATTTTTCTCAAAGAAGCATCATTAGGCCATTGAAGATAC +>chr1.1_006759713|AltMatch_0001 +GTGAGATGACTCCAACGCAATGCAGCTTCCAGACTCTAGTCATTGTTTCCTGAATCCTTATACCCTTTGTGTCATGCTCAC +>chr1.1_006759713|Alt_0002 +GTGAGATGACTCCAACGCAATGCAGCTTCCAGACTCTAGTCACTGTTTCCTGAATCCTTATACCCTTTGTGTCATGCTCAC +>chr1.1_006759713|RefMatch_0001 +GTGAGATGACTCCAACGCAATGCGGCTTCCAGACTCTAATCACTGTTTCCTGAATCCTTATACCCTTTGTGTCATGCTCAC +>chr1.1_006759713|Ref_0001 +GTGAGATGACTCCAACGCAATGCAGCTTCCAGACTCTAATCACTGTTTCCTGAATCCTTATACCCTTTGTGTCATGCTCAC +>chr1.1_006927231|AltMatch_0001 +GGTGAATGGTGATGGAACAAATCTAAGCATGCCAAAAACTGGTTATGAATATGTTGGAAACACACCTGAATGTGCTTTATT +>chr1.1_006927231|Alt_0002 +GGTGAATGGTGATGGAACAAATCTAAGCATGCTAAAAACTGGTTATGAATATGTTGGAAACACACCTGAATGTGCTTTATT +>chr1.1_006927231|RefMatch_0001 +GGTGAATGGTGATGGAACAAATCTAAGCATACTAAATACTGGTTATGAATATGTTGGAAACACACCTGAATGTGCTTTATT +>chr1.1_006927231|RefMatch_0002 +GGTGAATGGTGATGGAACAAATCTAAGCATGCTAAATATTGGTTATGAATATGTTGGAAACACACCTGAATGTGCTTTATT +>chr1.1_006927231|Ref_0001 +GGTGAATGGTGATGGAACAAATCTAAGCATGCTAAATACTGGTTATGAATATGTTGGAAACACACCTGAATGTGCTTTATT +>chr1.1_007050147|Alt_0002 +GTCAGAGACATGAGGGAAATGGGAAGCAACTTTTCTCTCAGTAAGATGTTAACAATATCATCACCACCAATATGCAAATCA +>chr1.1_007050147|Ref_0001 +GTCAGAGACATGAGGGAAATGGGAAGCAACTTTTCTCTCAGCAAGATGTTAACAATATCATCACCACCAATATGCAAATCA +>chr1.1_007233177|AltMatch_0001 +GAATAGAAATTTAGTGCAGCGTATGCAATCATCTTTGGGAATCCCCTTTACTAGTGAAGATGATGATGCATTCACTAACTT +>chr1.1_007233177|Alt_0002 +GAATAGAAATTTAGTGCAGCGTATGCAATCATCTGTGGGAATCCCCTTTACTAGTGAAGATGATGATGCATTCACTAACTT +>chr1.1_007233177|RefMatch_0001 +GAATAGAAATTTAGTGCAGCGTATGCAATCATCTGCGGGAATCCCCGTTACTAGTGAAGATGATGATGCATTCACTAACTT +>chr1.1_007233177|RefMatch_0002 +GAATAGAAATTTAGTGCAGCGTATGCAATCATCTTTGGGAATCCCCGTTACTAGTGAAGATGATGATGCATTCACTAACTT +>chr1.1_007233177|Ref_0001 +GAATAGAAATTTAGTGCAGCGTATGCAATCATCTGTGGGAATCCCCGTTACTAGTGAAGATGATGATGCATTCACTAACTT +>chr1.1_007349949|Alt_0002 +CCCTATCTTAGCACAATCCAATACAATAGCATTTTCATCAATGCATGTTCCATAGATATTACTGAATTTGATGTTACTTAT +>chr1.1_007349949|RefMatch_0001 +CCCTATCTTAGCACAATCCAATACAATAGCATTTTCATCAATACATGTTCCACAGATATTACTGAATTTGATGTTACTTAT +>chr1.1_007349949|Ref_0001 +CCCTATCTTAGCACAATCCAATACAATAGCATTTTCATCAATACATGTTCCATAGATATTACTGAATTTGATGTTACTTAT +>chr1.1_007519233|AltMatch_0001 +GCAATATACTAACTAACATTCATGTAAAACACATCTCTATTGTTTTTACTTCCAACAAAGTCATCGAGTAGTTTTAATTTA +>chr1.1_007519233|Alt_0002 +GCAATATACTAACTAACATTCATGTAAAACACATCTCTATATGTTTTTACTTCCAACAAAGTCATCGAGTAGTTTTAATTT +>chr1.1_007519233|Ref_0001 +GCAATATACTAACTAACATTCATGTAAAACACATCTCTATATGTTTTTACTTACAACAAAGTCATCGAGTAGTTTTAATTT +>chr1.1_007830610|Alt_0002 +CTCATTATAACTTGCATCATATAAAGTGCTGATAATTAGACTGAATCTGACATTAGAAACTCTCACAACAAACAAAAAAAA +>chr1.1_007830610|Ref_0001 +CTCATTATAACTTGCATCATATAAAGTGCTGATAATTAGACTGAATCCGACATTAGAAACTCTCACAACAAACAAAAAAAA +>chr1.1_008362856|AltMatch_0001 +TGCCATTGCAATTTGAAATTCTGATCAAGTGGTATCTTTTATTGGACATCATAGCATGCAGTGTGCTAATATCCAAGCTTT +>chr1.1_008362856|Alt_0002 +TGCCATTGCAATTTGAAATTCTGATCAAGTGGTATCTTTTATTGGACACCATAGCATGCAGTGTGCTAATATCCAAGCTTT +>chr1.1_008362856|Ref_0001 +TGCCATTGCAATTTGAAATTCTGATCAAGTGGTATCTTTTATTGGACACCATATCATGCAGTGTGCTAATATCCAAGCTTT +>chr1.1_008573540|Alt_0002 +CCTCCTATTGCAAATGTAGAACTATGCAGTTTTCTTTATCGCATAATGTATTATTGAGTATGAGGATGTGTATTTTTGTGG +>chr1.1_008573540|Ref_0001 +CCTCCTATTGCAAATGTAGAACTATGCAGTTTTCTTTATCACATAATGTATTATTGAGTATGAGGATGTGTATTTTTGTGG +>chr1.1_008671918|Alt_0002 +CCCTGTGCATGAATTTTAAGCGACAAATTCCTTTTGCCTCATAGGATAGTAACATATGGTATTTTGCTTTTTTGAAGTACA +>chr1.1_008671918|RefMatch_0001 +CCCTGTGCATGAATTTTAAGCGACAAATTCCTTTTGCATCATAAGATAGTAACATATGGTATTTTGCTTTTTTGAAGTACA +>chr1.1_008671918|Ref_0001 +CCCTGTGCATGAATTTTAAGCGACAAATTCCTTTTGCATCATAGGATAGTAACATATGGTATTTTGCTTTTTTGAAGTACA +>chr1.1_009082943|Alt_0002 +GCTCATCTGCAGTTATAAAAATATGCCTTGTTGAAAGTAGCTGTAGATAATTGAAGTTTATGGATATTTTATTGTGATCAA +>chr1.1_009082943|Ref_0001 +GCTCATCTGCAGTTATAAAAATATGCCTTGTTGAAAGTAGCTGTAGATAATAGAAGTTTATGGATATTTTATTGTGATCAA +>chr1.1_009175857|AltMatch_0001 +TGCAAGGTTTCCATGTAATTGGCTAATGGCCTCCTTTCACACTGGAAACATTTAAAGTTTCACATTATGCAACAATGTTAC +>chr1.1_009175857|Alt_0002 +TGCAAGGTTTCCATGTAATTGGCTAATGGCCTCCTTTCACACTGGAGACATTTAAAGTTTCACATTATGCAACAATGTTAC +>chr1.1_009175857|RefMatch_0001 +TGCAAGGTTTCCATGTAATTGGCTAATGGCCTTCTTTCACACTGGAGAGATTTAAAGTTTCACATTATGCAACAATGTTAC +>chr1.1_009175857|Ref_0001 +TGCAAGGTTTCCATGTAATTGGCTAATGGCCTCCTTTCACACTGGAGAGATTTAAAGTTTCACATTATGCAACAATGTTAC +>chr1.1_009325684|Alt_0002 +CCTTATTTCTTAGAAGCTTTGGTTACGCTTTCTTCTTTATGATGAATTGGAAATGAGTAATACTTGGGCTAATGAAATTAG +>chr1.1_009325684|Ref_0001 +CCTTATTTCTTAGAAGCTTTGGTTACGCTTTCTTCTTTATGATGAATTGGATATGAGTAATACTTGGGCTAATGAAATTAG +>chr1.1_009654615|Alt_0002 +GATTCATTTTTGGAAGTTGATGTGAAGTTGAATCTCACACTTGAGGTTGCTCTTATACTCAAACTAAAAATATAGCATATA +>chr1.1_009654615|Ref_0001 +GATTCATTTTTGGAAGTTGATGTGAAGTTGAATCTCACACTTGAGGTTACTCTTATACTCAAACTAAAAATATAGCATATA +>chr1.1_009788520|Alt_0002 +ATTACGTTACTCAACAACTCATTCAGGTGATTGTTCAATGCAATGATTGTTACATGGCTAATTGGTTTTCAATGTATCACC +>chr1.1_009788520|RefMatch_0001 +ATTACGTTACTCAACAACTCATTCAGGTGATTGTTCGACGCAATGATTGTTACATGGCTAATTGGTTTTCAATGTATCACC +>chr1.1_009788520|RefMatch_0002 +ATTACGTTACTCAACAACTCATTCAGGTGATTGTTTGATGCAATGATTGTTACATGGCTAATTGGTTTTCAATGTATCACC +>chr1.1_009788520|Ref_0001 +ATTACGTTACTCAACAACTCATTCAGGTGATTGTTCGATGCAATGATTGTTACATGGCTAATTGGTTTTCAATGTATCACC +>chr1.1_010059811|AltMatch_0001 +AGTGCCATGTAACTTCCTAGCACAACACCAGTTGCAAATATCTCCCTCAGTTTCCAACTATCAGGTAGTGGAGATGGTTTC +>chr1.1_010059811|Alt_0002 +AGTGCCATGTAACTTCCTAGCACAACACCAGTTGCAAATATCTCCTTCAGTTTCCAACTATCAGGTAGTGGAGATGGTTTC +>chr1.1_010059811|RefMatch_0001 +AGTGCCATGTAACTTCCTAGCACAACACCAGTAGCAAATATCTCCCTCAGTTTCCAACTATCAGGTAGTGGAGATGGTTTC +>chr1.1_010059811|RefMatch_0002 +AGTGCCATGTAACTTCCTAGCACAACACCAGTAGCAAATATCTCTCTCAGTTTCCAACTATCAGGTAGTGGAGATGGTTTC +>chr1.1_010059811|RefMatch_0003 +AGTGCCATGTAACTTCCTAGCACAACACCAGTAGCAAATATTTCCTTTAGTTTCCAACTATCAGGTAGTGGAGATGGTTTC +>chr1.1_010059811|RefMatch_0004 +AGTGCCATGTAACTTCCTAGCACAACACCAGTAGCGAATATCTCCCTCAGTTTCCAACTATCAGGTAGTGGAGATGGTTTC +>chr1.1_010059811|RefMatch_0005 +AGTGCCATGTAACTTCCTAGCACAACACCAGTAGTGAATATCTCCCTCAGTTTCCAACTATCAGGTAGTGGAGATGGTTTC +>chr1.1_010059811|Ref_0001 +AGTGCCATGTAACTTCCTAGCACAACACCAGTAGCAAATATCTCCTTCAGTTTCCAACTATCAGGTAGTGGAGATGGTTTC +>chr1.1_010182954|AltMatch_0001 +AATCACTCTATTAGTGCTTTCAGACAATCCTTTTGTTTCGTTAACTAATTGATGAATTTGTATTTTGTTCATCATATAATT +>chr1.1_010182954|Alt_0002 +AATCACTCTATTAGTGCTTTCAGACAATCCTTTTGTTTCATTAACTAATTGATGAATTTGTATTTTGTTCATCATATAATT +>chr1.1_010182954|Ref_0001 +AATCACTCTATTAGTGCTTTCAGACAATCCTTTTGTTTCATTAAGTAATTGATGAATTTGTATTTTGTTCATCATATAATT +>chr1.1_010318074|Alt_0002 +GCTTCTGGCTGAATTAATCAATTTCAAGGTTGTTCTTTTGTGTTTATATATTGGATGAGGCTGTCTCCTTGCCCCTTGTTT +>chr1.1_010318074|Ref_0001 +GCTTCTGGCTGAATTAATCAATTTCAAGGTTGTTCTTTTGTGTTTTTATATTGGATGAGGCTGTCTCCTTGCCCCTTGTTT +>chr1.1_010513693|AltMatch_0001 +GACCTTGTCTCATTCAAAATGAAACTTTATTTTACTTGGAAAACACAGATCAGTCTATAAATATCAAGCGTTATACTTATC +>chr1.1_010513693|Alt_0002 +GACCTTGTCTCATTCAAAATGAAACTTTATTTTACTTGGAAAACACTGATCAGTCTATAAATATCAAGCGTTATACTTATC +>chr1.1_010513693|Ref_0001 +GACCTTGTCTCATTCAAAATGAAACTTTATTTTACTTGGAAAACACTTATCAGTCTATAAATATCAAGCGTTATACTTATC +>chr1.1_010654139|Alt_0002 +AAGACAAGCATATTTCATATTCTGAGCTTGCTTTTTGAATCTTTTTATAGACCTTAAAATTTAGTCCTACAATTATCTTAA +>chr1.1_010654139|Ref_0001 +AAGACAAGCATATTTCATATTCTGAGCTTGCTTTTTGAATCTTTTTATAGAGCTTAAAATTTAGTCCTACAATTATCTTAA +>chr1.1_010740435|AltMatch_0001 +GGACTCAAGAGTTCAAGAATGACAGAAATCATTTTTGTATTTTCTTAGGCAAAAATGTTGAAGGTAAGGTTTGAAATCAGT +>chr1.1_010740435|Alt_0002 +GGACTCAAGAGTTCAAGAATGACAGAAATCATTTTGGTATTTTCTTAGGCAAAAATGTTGAAGGTAAGGTTTGAAATCAGT +>chr1.1_010740435|RefMatch_0001 +GGACTCAAGAGTTCAAGAATGACAGAAATCATTTTTGTATATTCTTAGGCAAAAATGTTGAAGGTAAGGTTTGAAATCAGT +>chr1.1_010740435|Ref_0001 +GGACTCAAGAGTTCAAGAATGACAGAAATCATTTTGGTATATTCTTAGGCAAAAATGTTGAAGGTAAGGTTTGAAATCAGT +>chr1.1_011053888|AltMatch_0001 +GCCACAAAACAGATGCAACTAAAGTGTACTCTTTGCCTCTGGAAGGTGCTGATGGAAGTAGAGTTAAAGCTGCTGCTATTT +>chr1.1_011053888|Alt_0002 +GCCACAAAACAGATGCAACTAAAGTATACTATTTGCCTTTGGAAGGTGCTGATGGAAGTAGAGTTAAAGCTGCTGCTATTT +>chr1.1_011053888|RefMatch_0001 +GCCACAAAACAGATGCAACTAAAGTTTACTCTGTGCCTCTAGAAGGTGCTGATGGAAGTAGAGTTAAAGCTGCTGCTATTT +>chr1.1_011053888|RefMatch_0002 +GCCACAAAACAGATGCAACTAAAGTTTACTCTGTGCCTTTGGAAGGTGTTGATGGAAGTAGAGTTAAAGCTGCTGCTATTT +>chr1.1_011053888|Ref_0001 +GCCACAAAACAGATGCAACTAAAGTATACTATGTGCCTTTGGAAGGTGCTGATGGAAGTAGAGTTAAAGCTGCTGCTATTT +>chr1.1_011205612|Alt_0002 +ATGGGGTAATGAGTGTAAACTTTTAAGGTTATGATCCTTGTTTTTCTTCTTACAGCATGAAAGTAACCTTTTGATCTGATT +>chr1.1_011205612|Ref_0001 +ATGGGGTAATGAGTGTAAACTTTTAAGGTTATGATCCTTGTTTTTCTTTTTACAGCATGAAAGTAACCTTTTGATCTGATT +>chr1.1_011294632|AltMatch_0001 +ATGTCAAGTTGCATGTTTATTGCAAACTGTAAGTGAAAGTGTACTTACTTGGACAAGATTGCACCCACCGTTTAAGTATTT +>chr1.1_011294632|Alt_0002 +ATGTCAAGTTGCATGTTTATTGCAAACTGTAAGTTAAAGTGTACTTACTTGGACAAGATTGCACCCACCGTTTAAGTATTT +>chr1.1_011294632|Ref_0001 +ATGTCAAGTTGCATGTTTATTGCAAACTGTAAGTTATAGTGTACTTACTTGGACAAGATTGCACCCACCGTTTAAGTATTT +>chr1.1_011550587|Alt_0002 +GTGCTTACAAGGTAATGCTTTTGTACGAACTCTAGTATACCTGGTTAAATGTTTTGGATTGATAGTTGTACTATGACAAAA +>chr1.1_011550587|RefMatch_0001 +GTGCTTACAAGGTAATGCTTTTGTACGAACTCTAGTATGCCTGGATAAATGTTTTGGATTGATAGTTGTACTATGACAAAA +>chr1.1_011550587|Ref_0001 +GTGCTTACAAGGTAATGCTTTTGTACGAACTCTAGTATACCTGGATAAATGTTTTGGATTGATAGTTGTACTATGACAAAA +>chr1.1_011602715|Alt_0002 +CTGTAATATTTGCATAACCCAATATTTCTATTTGACATATTTGCTTGTATTTTTATCATCCAGATGTTTGATACATATAGA +>chr1.1_011602715|Ref_0001 +CTGTAATATTTGCATAACCCAATATTTCTATTTTACATATTTGCTTGTATTTTTATCATCCAGATGTTTGATACATATAGA +>chr1.1_011667046|AltMatch_0001 +CCAACAACGGTTTTGGAAGGTCCTTACGTTGGAAGAGCTGTGTCTTTTACGACGTCGTATAGGGATAGTAATAACAAGGGC +>chr1.1_011667046|Alt_0002 +CCAACAACGGTTTTGGAAGGTCCATACGTTGGACGAGCAGTGTCTTTTACGACGTCGTATAGGGATAGTAATAACAAGGGC +>chr1.1_011667046|Ref_0001 +CCAACAACGGTTTTGGAAGGTCCATACGTTGGACGTGCAGTGTCTTTTACGACGTCGTATAGGGATAGTAATAACAAGGGC +>chr1.1_011839955|Alt_0002 +ATTATACCTGTCCATCAGGCCGATAGCACACTGCGGTGACAATTTCCTTGACGTCAGTCCAATCAACAACATGACAATCAG +>chr1.1_011839955|RefMatch_0001 +ATTATACCTGTCCATCAGGCCGATAGCACACCGCGGTGACAATTTCCTTGACATCAGTCCAATCAACAACATGACAATCAG +>chr1.1_011839955|RefMatch_0002 +ATTATACCTGTCCATCAGGCCGATAGCACACTGCAGTGACAATTTCCTTGACATCAGTCCAATCAACAACATGACAATCAG +>chr1.1_011839955|RefMatch_0003 +ATTATACCTGTCCATCAGGCCGATAGCACACTGCGGTGACAATTTCCCTGACATCAGTCCAATCAACAACATGACAATCAG +>chr1.1_011839955|RefMatch_0004 +ATTATACCTGTCCATCAGGCCGATAGCACACTGCGGTGACAATTTCCTTTACATCAGTCCAATCAACAACATGACAATCAG +>chr1.1_011839955|Ref_0001 +ATTATACCTGTCCATCAGGCCGATAGCACACTGCGGTGACAATTTCCTTGACATCAGTCCAATCAACAACATGACAATCAG +>chr1.1_012022200|Alt_0002 +GTGGAATTGATGAAAGTTTTAATTTAAGATGAATTGACTTTAGTGTAACTTGATTATTGTTTGCTGTGTTATATAACAGAT +>chr1.1_012022200|Ref_0001 +GTGGAATTGATGAAAGTTTTAATTTAAGATGAATTGACTTTAGGGTAACTTGATTATTGTTTGCTGTGTTATATAACAGAT +>chr1.1_012607158|AltMatch_0001 +CCCAAAGAAGGCTCATCTGTTTTACTTGCCATTCAGTTCTAGGATGCTAGAGGAAGCCTTGTATGTGAAGAATTCGCATAG +>chr1.1_012607158|Alt_0002 +CCCAAAGAAGGCTCATCTGTTTTACTTGCCTTTCAGTTCTAGGATGCTAGAGGAAGCCTTGTATGTGAAGAATTCGCATAG +>chr1.1_012607158|Ref_0001 +CCCAAAGAAGGCTCATCTGTTTTACTTACCTTTCAGTTCTAGGATGCTAGAGGAAGCCTTGTATGTGAAGAATTCGCATAG +>chr1.1_012673656|Alt_0002 +CTAACATAAGTGGTTGATGCGCTATACGTGTGTGTTGAAAAATATCAAATAATGAGTTTGATTTGCCCTTATAAAGAATAT +>chr1.1_012673656|RefMatch_0001 +CTAACATAAGTGGTTGATGCGCTATACGTGTGTGTTGAAAAATATCAGATATTGAGTTTGATTTGCCCTTATAAAGAATAT +>chr1.1_012673656|Ref_0001 +CTAACATAAGTGGTTGATGCGCTATACGTGTGTGTTGAAAAATATCAGATAATGAGTTTGATTTGCCCTTATAAAGAATAT +>chr1.1_012905400|Alt_0002 +TGTTTTTCGACATGTTCTAAAATTGTTGGCCTTTTGTTCCTCAAAACATAGTCTTCATGATTCAGACATGTTAAGAAAATA +>chr1.1_012905400|RefMatch_0001 +TGTTTTTCGACATGTTCTAAAATTGTTGGCCTTTCGTTCCTCAAAACATAGTTTTCATGATTCAGACATGTTAAGAAAATA +>chr1.1_012905400|RefMatch_0002 +TGTTTTTCGACATGTTCTAAAATTGTTGGCCTTTTGTTCCTCAACACATAGTTTTCATGATTCAGACATGTTAAGAAAATA +>chr1.1_012905400|Ref_0001 +TGTTTTTCGACATGTTCTAAAATTGTTGGCCTTTTGTTCCTCAAAACATAGTTTTCATGATTCAGACATGTTAAGAAAATA +>chr1.1_012952616|Alt_0002 +CTGAACATGATAGGAACGACCTTTCATTATACTCATCTGATCAAGTTGGTTTTAGAGACAGGGTTATAGGTTCTAGTGTTA +>chr1.1_012952616|Ref_0001 +CTGAACATGATAGGAACGACCTTTCATTATATTCATCTGATCAAGTTGGTTTTAGAGACAGGGTTATAGGTTCTAGTGTTA +>chr1.1_013166244|Alt_0002 +ATCGTGTCATTCCACTAAAGCGCATTAAAATCGTCTTAAGCTGGGTAGTATTTCCTTCGTGGTCATTCTAATTGCTTAAAG +>chr1.1_013166244|Ref_0001 +ATCGTGTCATTCCACTAAAGCGCAATAAAATCGTCTTAAGCTGGGTAGTATTTCCTTCGTGGTCATTCTAATTGCTTAAAG +>chr1.1_013536075|Alt_0002 +GAAATTGACAAAGGGGAACATAATTTGTTGTTCCCCTTATACTGTTATACATATGTTGGGAATCAGACTTCGTTTTGTGTC +>chr1.1_013536075|Ref_0001 +GAAATTGACAAAGGGGAACATAATTTGTTGTTCCCCTTATACTGTAATACATATGTTGGGAATCAGACTTCGTTTTGTGTC +>chr1.1_014007601|Alt_0002 +TTGAAGACTAGTGTCAGGAGTGTACATACATTGTTGCTTGCATCTAGAGTCAATTATTTTGATTTTGATTATTATTATTAT +>chr1.1_014007601|RefMatch_0001 +TTGAAGACTAGTGTCAGGAGTGTACATACATTGTTGCTTGTATCTAGTGTCAATTATTTTGATTTTGATTATTATTATTAT +>chr1.1_014007601|RefMatch_0002 +TTGAAGACTAGTGTCAGGAGTGTACATACGTTGTTGCTTGCATCTAGTGTCAATTATTTTGATTTTGATTATTATTATTAT +>chr1.1_014007601|Ref_0001 +TTGAAGACTAGTGTCAGGAGTGTACATACATTGTTGCTTGCATCTAGTGTCAATTATTTTGATTTTGATTATTATTATTAT +>chr1.1_014100127|Alt_0002 +ATTTTTTAACTTCTAACAATTGAAATTATGTTTGGATTATTTGATTTGCTCTTCTAAGGACATCAACAATCAAATTCATGG +>chr1.1_014100127|Ref_0001 +ATTTTTTAACTTCTAACAATTGAAATTATGTTTGGATTAGTTGATTTGCTCTTCTAAGGACATCAACAATCAAATTCATGG +>chr1.1_014207906|Alt_0002 +CCAAATGAATAATAGTTATGTGCATGAAAATTTTCTCATTATTTTATATTTCTTCCAAAACCAAGTGAAATGATTGGGTTG +>chr1.1_014207906|Ref_0001 +CCAAATGAATAATAGTTATGTGCATGAAAATTTTCTCATTATTTTATATATCTTCCAAAACCAAGTGAAATGATTGGGTTG +>chr1.1_014290088|Alt_0002 +CTCACAACAGCACCAACAGATGCATAATCTAGGCAATAATACTTTCAGGTAAAAAAGAGATCAATCTAACTTGATATTTTT +>chr1.1_014290088|Ref_0001 +CTCACAACAGCACCAACAGATGCATAATCTAGGCAATAATATTTTCAGGTAAAAAAGAGATCAATCTAACTTGATATTTTT +>chr1.1_014683124|Alt_0002 +CATTCATGGTATTAAATGATCATATATGTGTCTACATATTTGTAGTTATGCACCTAAGCTAAACATTGCCATCCCAAGACC +>chr1.1_014683124|Ref_0001 +CATTCATGGTATTAAATGATCATATATGTGTCTATATATTTGTAGTTATGCACCTAAGCTAAACATTGCCATCCCAAGACC +>chr1.1_014788595|Alt_0002 +AATGCTGAAAAGATAATTGTCACATTCACCTAATCAATTTAATGATCAGTCGCATGATTTCCTGCTTTTCAAAGGAAGGTA +>chr1.1_014788595|RefMatch_0001 +AATGCTGAAAAGATAATTGTCACATTCACCTACGCAATTTAATGATCAGTCGCATGATTTCCTGCTTTTCAAAGGAAGGTA +>chr1.1_014788595|RefMatch_0002 +AATGCTGAAAAGATAATTGTCACATTCACCTACTCAACTTAATGATCAGTCGCATGATTTCCTGCTTTTCAAAGGAAGGTA +>chr1.1_014788595|RefMatch_0003 +AATGCTGAAAAGATAATTGTCACATTCACCTACTCAATTTAATGATCAGTCACATGATTTCCTGCTTTTCAAAGGAAGGTA +>chr1.1_014788595|RefMatch_0004 +AATGCTGAAAAGATAATTGTCACATTCACCTACTCAATTTAATGATTAGTCGCATGATTTCCTGCTTTTCAAAGGAAGGTA +>chr1.1_014788595|Ref_0001 +AATGCTGAAAAGATAATTGTCACATTCACCTACTCAATTTAATGATCAGTCGCATGATTTCCTGCTTTTCAAAGGAAGGTA +>chr1.1_014974968|Alt_0002 +CGGCAGTTGTTCGCAGGTAAGATATGCATGCCTTTTTCATGTCCAAATATATTTGTTTTCTTTTTACTGCTATACATTTTT +>chr1.1_014974968|RefMatch_0001 +CGGCAGTTGTTCGCAGGTAAGATATGCACGCCATTTTCATGTCCAAATATATTTGTTTTCTTTTTACTGCTATACATTTTT +>chr1.1_014974968|Ref_0001 +CGGCAGTTGTTCGCAGGTAAGATATGCACGCCTTTTTCATGTCCAAATATATTTGTTTTCTTTTTACTGCTATACATTTTT +>chr1.1_015044468|Alt_0002 +GATTAGCTTTTCGTACCATCAAACTCTGACATGACATGGCTCACATGGATTAGTCCATACCCATCTGCACAAGGCAGTTTA +>chr1.1_015044468|RefMatch_0001 +GATTAGCTTTTCGTACCATCAAACTCTGACATGATATGGCTCCCATGGATTAGTCCATACCCATCTGCACAAGGCAGTTTA +>chr1.1_015044468|Ref_0001 +GATTAGCTTTTCGTACCATCAAACTCTGACATGACATGGCTCCCATGGATTAGTCCATACCCATCTGCACAAGGCAGTTTA +>chr1.1_015282744|AltMatch_0001 +AGAATTAAATTTGTGTATGATGTTTGTCACTTCTTTAATCATTCTTGTTTGTTGTAAATTTTTAGCTGATTTTGTATTGAG +>chr1.1_015282744|Alt_0002 +AGAATTAAATTTGTGTATGATGTTTGTCACTTCTTTAATCATTCTTGTTTGTCGTAAATTTTTAGCTGATTTTGTATTGAG +>chr1.1_015282744|RefMatch_0001 +AGAATTAAATTTGTGTATGATGTTTGTCACTTCTTCAAGCATTCTTGTTTGTTGTAAATTTTTAGCTGATTTTGTATTGAG +>chr1.1_015282744|RefMatch_0002 +AGAATTAAATTTGTGTATGATGTTTGTCACTTCTTTAAGCATTATTGTTTGTTGTAAATTTTTAGCTGATTTTGTATTGAG +>chr1.1_015282744|RefMatch_0003 +AGAATTAAATTTGTGTATGATGTTTGTCACTTCTTTAAGCATTCTTGTTTGTTGTAAATTTTTAGCTGATTTTGTATTGAG +>chr1.1_015282744|RefMatch_0004 +AGAATTAAATTTGTGTATGATGTTTGTCACTTCTTTAGGCATTCTTGTTTGTTGTAAATTTTTAGCTGATTTTGTATTGAG +>chr1.1_015282744|Ref_0001 +AGAATTAAATTTGTGTATGATGTTTGTCACTTCTTTAAGCATTCTTGTTTGTCGTAAATTTTTAGCTGATTTTGTATTGAG +>chr1.1_015424890|Alt_0002 +CTATACTTATGCTCTCTTTCGGCAACTGCTTTTGCCACGTGTCCATGCTAACATTGCCTAATTTTCTTTCAAGTTCATTCA +>chr1.1_015424890|RefMatch_0001 +CTATACTTATGCTCTCTTTCGGCAACTGCTTTTGGCACGTGTCCATACTAACATTGCCTAATTTTCTTTCAAGTTCATTCA +>chr1.1_015424890|RefMatch_0002 +CTATACTTATGCTCTCTTTCGGCAACTGCTTTTGGCATGTGTCCATGCTAACATTGCCTAATTTTCTTTCAAGTTCATTCA +>chr1.1_015424890|Ref_0001 +CTATACTTATGCTCTCTTTCGGCAACTGCTTTTGGCACGTGTCCATGCTAACATTGCCTAATTTTCTTTCAAGTTCATTCA +>chr1.1_015712918|Alt_0002 +GCACGGAATAGACTCTATTTGGTTGCATTTCATCCATAGTGTAGATATTTCAAGACTTACTAAGTAATAGTATATCATTTC +>chr1.1_015712918|RefMatch_0001 +GCACGGAATAGACTCTATTTGGTTGCATGTCATCCATAGTGTAGATAATTCAAGACTTACTAAGTAATAGTATATCATTTC +>chr1.1_015712918|RefMatch_0002 +GCACGGAATAGACTCTATTTGGTTGCATTTCATCCATAATGTAGATAATTCAAGACTTACTAAGTAATAGTATATCATTTC +>chr1.1_015712918|Ref_0001 +GCACGGAATAGACTCTATTTGGTTGCATTTCATCCATAGTGTAGATAATTCAAGACTTACTAAGTAATAGTATATCATTTC +>chr1.1_016006885|Alt_0002 +GGTTTTAGAGGTATCTTTATTTATAAATATGTTTTGGTTATTTATGCTTTCAACTGATTCATCTTTGTCACAATAATATTC +>chr1.1_016006885|Ref_0001 +GGTTTTAGAGGTATCTTTATTTATAAATATGTTTTGGTTATTGATGCTTTCAACTGATTCATCTTTGTCACAATAATATTC +>chr1.1_016136535|Alt_0002 +AGTTATGCATGTAATTTTGAAATTTCATAAATTTCTCTATACTTCCTTTTGTTTGTTATGTCTTCATCACATGATCAAGAA +>chr1.1_016136535|RefMatch_0001 +AGTTATGCATGTAATTTTGAAATTTCATAAAGTTATCTATACTTCCTTTTGTTTGTTATGTCTTCATCACATGATCAAGAA +>chr1.1_016136535|RefMatch_0002 +AGTTATGCATGTAATTTTGAAATTTCATAAAGTTCTCTATACTTCCTTCTGTTTGTTATGTCTTCATCACATGATCAAGAA +>chr1.1_016136535|Ref_0001 +AGTTATGCATGTAATTTTGAAATTTCATAAAGTTCTCTATACTTCCTTTTGTTTGTTATGTCTTCATCACATGATCAAGAA +>chr1.1_016221768|AltMatch_0001 +GATATTTCACCATGATGTTATCTCATAATATGATTTTCTAACACTATTCTGCTAGTAGTAGCCAGCTACATTGAGTGCTAA +>chr1.1_016221768|Alt_0002 +GATATTTCACCATGATGTTATCTCATAATATTATTTTCTAACACTATTCTGCTAGTAGTAGCCAGCTACATTGAGTGCTAA +>chr1.1_016221768|Ref_0001 +GATATTTCACCATGATGTTATCTCATAATATTATTTTCTAACTCTATTCTGCTAGTAGTAGCCAGCTACATTGAGTGCTAA +>chr1.1_016403559|Alt_0002 +CACTGGGAATATACAATAGGTAATTAAGGTTATTATGTTTCATAGTTTTATTTTATTTATTGCTTAAAGGTAATAGTAGTA +>chr1.1_016403559|Ref_0001 +CACTGGGAATATACAATAGGTAATTAAGGTTATTATGTTTCATATTTTTATTTTATTTATTGCTTAAAGGTAATAGTAGTA +>chr1.1_016522945|AltMatch_0001 +TGTGTGAAGTTTGAGAATAATTAACCAATCAAGTATTTGATAATAGACTGTTCCTAACTGTTAGGACTGAATAATGGGAAG +>chr1.1_016522945|Alt_0002 +TGTGTGAAGTTTGAGAATAATTAACCAATCAAGTATTTGATAATAGACCGTTCCTAACTGTTAGGACTGAATAATGGGAAG +>chr1.1_016522945|Ref_0001 +TGTGTGAAGTTTGAGAATAATTAACCAATCAAGTATTTGATAATAGATCGTTCCTAACTGTTAGGACTGAATAATGGGAAG +>chr1.1_016563045|Alt_0002 +TAGCCAGCGCTTCTAAAGGGATGTGTATTCTATCGTTGTTAAAGACATCGCTTATTATATCAGTTGATATAATTCAAAGTT +>chr1.1_016563045|RefMatch_0001 +TAGCCAGCGCTTCTAAAGGGATGTGTATTCTATCATTGTTAAAGACATCGCTTTTTATATCAGTTGATATAATTCAAAGTT +>chr1.1_016563045|RefMatch_0002 +TAGCCAGCGCTTCTAAAGGGATGTGTATTCTATCGTTATTAAAGACATCGCTTTTTATATCAGTTGATATAATTCAAAGTT +>chr1.1_016563045|RefMatch_0003 +TAGCCAGCGCTTCTAAAGGGATGTGTATTCTATCGTTGTTAAAGACATCGCGTTTTATATCAGTTGATATAATTCAAAGTT +>chr1.1_016563045|RefMatch_0004 +TAGCCAGCGCTTCTAAAGGGATGTGTATTCTATCGTTGTTAAAGGCACCGCTTTTTATATCAGTTGATATAATTCAAAGTT +>chr1.1_016563045|RefMatch_0005 +TAGCCAGCGCTTCTAAAGGGATGTGTATTCTATCGTTGTTAAAGGCATCGCTTTTTATATCAGTTGATATAATTCAAAGTT +>chr1.1_016563045|Ref_0001 +TAGCCAGCGCTTCTAAAGGGATGTGTATTCTATCGTTGTTAAAGACATCGCTTTTTATATCAGTTGATATAATTCAAAGTT +>chr1.1_016763798|AltMatch_0001 +CTTCTGGACTGTCTTTTAGCCTGAAAGGGTGGCTGATGTTATGAACACCACACCTTCTTGAACATGACTCTTTTTGCTCAT +>chr1.1_016763798|Alt_0002 +CTTCTGGACTGTCTTTTAGCCTGAAAGGGTGGCTGATGTTATGAACACCACACTTTCTTGAACATGACTCTTTTTGCTCAT +>chr1.1_016763798|RefMatch_0001 +CTTCTGGACTGTCTTTTAGCCTGAAAGGGTGACTGATGTTATGAACACCGCACCTTCTTGAACATGACTCTTTTTGCTCAT +>chr1.1_016763798|RefMatch_0002 +CTTCTGGACTGTCTTTTAGCCTGAAAGGGTGGCTGATGTTATGAACACCGCACCTTCTTGAACATGACTCTTTTTGCTCAT +>chr1.1_016763798|RefMatch_0003 +CTTCTGGACTGTCTTTTAGCCTGAAAGGGTGGCTGATGTTATGAACACCGTACTTTCTTGAACATGACTCTTTTTGCTCAT +>chr1.1_016763798|RefMatch_0004 +CTTCTGGACTGTCTTTTAGCCTGAAAGGGTGGCTGATGTTATGGACACCGCACCTTCTTGAACATGACTCTTTTTGCTCAT +>chr1.1_016763798|Ref_0001 +CTTCTGGACTGTCTTTTAGCCTGAAAGGGTGGCTGATGTTATGAACACCGCACTTTCTTGAACATGACTCTTTTTGCTCAT +>chr1.1_016976894|Alt_0002 +TGCATGTGAAACTCAGACTAGTAATTGGTCTTCAGATGAATTTTTATGCTATATTGTTTGGTGATCTCATATGGTTGTAAT +>chr1.1_016976894|RefMatch_0001 +TGCATGTGAAACTCAGACTAGTAATTGGTTTTCAGATGAATTTTCATGCTATATTGTTTGGTGATCTCATATGGTTGTAAT +>chr1.1_016976894|Ref_0001 +TGCATGTGAAACTCAGACTAGTAATTGGTTTTCAGATGAATTTTTATGCTATATTGTTTGGTGATCTCATATGGTTGTAAT +>chr1.1_017030914|Alt_0002 +CTACCTCTTTAATTATTATTGCAGACCGTTTTGACTTAGAATCAAGCAATTCAACATCAGTCTTCCCTCTGACGACAACAC +>chr1.1_017030914|RefMatch_0001 +CTACCTCTTTAATTATTATTGCAGACCGTTTTGACTTAGAATCAAGCTGTTCAACATCAGTCTTCCCTCTGACGACAACAC +>chr1.1_017030914|Ref_0001 +CTACCTCTTTAATTATTATTGCAGACCGTTTTGACTTAGAATCAAGCAGTTCAACATCAGTCTTCCCTCTGACGACAACAC +>chr1.1_017368305|Alt_0002 +AACTGATCACTTTCGGTCACAATATCCTGTGTTAAAAGATTAGAGTGTAATCAATAGTTAATCTAAAAGGATTTGAATCAT +>chr1.1_017368305|RefMatch_0001 +AACTGATCACTTTCGGTCACAATATCCTGTGTTAAAAGATTAGAGTGCAATCAGTAGTTAATCTAAAAGGATTTGAATCAT +>chr1.1_017368305|Ref_0001 +AACTGATCACTTTCGGTCACAATATCCTGTGTTAAAAGATTAGAGTGTAATCAGTAGTTAATCTAAAAGGATTTGAATCAT +>chr1.1_017502654|Alt_0002 +GTGTCTCATTAAACCGAAATCACGGTACACAAGTCAATGCTTGTTTTTGAAGTTAACCATACTTGACTTAGAGGAGGGTTA +>chr1.1_017502654|RefMatch_0001 +GTGTCTCATTAAACCGAAATCACGGTACACAACTCAATGCTTGTTTTTGAACTTAACCATACTTGACTTAGAGGAGGGTTA +>chr1.1_017502654|RefMatch_0002 +GTGTCTCATTAAACCGAAATCACGGTACACAACTCAATGTTTGTTTTTGAAGTTAACCATACTTGACTTAGAGGAGGGTTA +>chr1.1_017502654|Ref_0001 +GTGTCTCATTAAACCGAAATCACGGTACACAACTCAATGCTTGTTTTTGAAGTTAACCATACTTGACTTAGAGGAGGGTTA +>chr1.1_017604907|Alt_0002 +TATGTTGCCTTTCATCTCATCATGTTCAGTAAGTTTTCATTCAGCATCATTTCTTACACAACAGTACAAGATTATACAGTG +>chr1.1_017604907|Ref_0001 +TATGTTGCCTTTCATCTCATCATGTTCAGTAAGTTTTCATTCAACATCATTTCTTACACAACAGTACAAGATTATACAGTG +>chr1.1_017863839|Alt_0002 +ATCTTGTAACTGTTTGCCACATTCTTCACAGATTCCACCAGCTTGCTTTTGAGATGTTGATGTCTTTGCTACTGATAGTCG +>chr1.1_017863839|RefMatch_0001 +ATCTTGTAACTGTTTGCCACATTCTTCACAAAATCCACCAGCTTGCTTTTGAGATGTTGATGTCTTTGCTACTGATAGTCG +>chr1.1_017863839|RefMatch_0002 +ATCTTGTAACTGTTTGCCACATTCTTCACAAATTCCACCAGCTTGTTTTTGAGATGTTGATGTCTTTGCTACTGATAGTCG +>chr1.1_017863839|RefMatch_0003 +ATCTTGTAACTGTTTGCCACATTCTTCACAAATTCCACCTGCTTGCTTTTGAGATGTTGATGTCTTTGCTACTGATAGTCG +>chr1.1_017863839|RefMatch_0004 +ATCTTGTAACTGTTTGCCACATTCTTCACAAATTCCTCCAGCTTGCTTTTGAGATGTTGATGTCTTTGCTACTGATAGTCG +>chr1.1_017863839|Ref_0001 +ATCTTGTAACTGTTTGCCACATTCTTCACAAATTCCACCAGCTTGCTTTTGAGATGTTGATGTCTTTGCTACTGATAGTCG +>chr1.1_018083264|AltMatch_0001 +TGCTGCTGCTCTAGGTCGAGGGATTTCAGGTTTTATTACAGCACAAGGGAGAACAGGTCAAAATGATGCAAATGGTTTTGT +>chr1.1_018083264|AltMatch_0002 +TGCTGCTGCTCTAGGTCGAGGGATTTCGGGTTTTATTACAGCACAAGGGAGAACAGGTCAAAATGATGCAAATGGTTTTGT +>chr1.1_018083264|Alt_0002 +TGCTGCTGCTCTAGGTCGAGGGATTTCTGGTTTTATTACAGCACAAGGGAGAACAGGTCAAAATGATGCAAATGGTTTTGT +>chr1.1_018083264|Ref_0001 +TGCTGCTGCTCTAGGTCGAGGAATTTCTGGTTTTATTACAGCACAAGGGAGAACAGGTCAAAATGATGCAAATGGTTTTGT +>chr1.1_018128065|AltMatch_0001 +GTACCTTGGAGATGTTTCTTGTTGTGAGACTTTGCAGGATACTCCCAGTCATAGCATCTGAAGCTGTAGACTTTACCGACT +>chr1.1_018128065|Alt_0002 +GTACCTTGGAGATGTTTCTTGTTGTGTGACTTTGCTGGATACTCCCAGTCATAGCATCTGAAGCTGTAGACTTTACCGACT +>chr1.1_018128065|RefMatch_0001 +GTACCTTGGAGATGTTTCTTGTTATGAGACTTTGCAGGATACTCCCAGTCATAGCATCTGAAGCTGTAGACTTTACCGACT +>chr1.1_018128065|RefMatch_0002 +GTACCTTGGAGATGTTTCTTGTTATGTGACTTTGCAGGATACTCCCAGTCATAGCATCTGAAGCTGTAGACTTTACCGACT +>chr1.1_018128065|Ref_0001 +GTACCTTGGAGATGTTTCTTGTTATGTGACTTTGCTGGATACTCCCAGTCATAGCATCTGAAGCTGTAGACTTTACCGACT +>chr1.1_018362099|Alt_0002 +GAGCGTACCATAGAAGTCGCTGTTGTTATATGCTAAATTCGATTACATATATAATTCGTCCCAAAAACTCATTATTCTTAA +>chr1.1_018362099|Ref_0001 +GAGCGTACCATAGAAGTCGCTGTTGTTATATGCTAAATTCGATTAAATATATAATTCGTCCCAAAAACTCATTATTCTTAA +>chr1.1_018698343|AltMatch_0001 +GGCTGAAAGTCATACATCTCACCCAATATTTTATCTTGCTTAGCTGAGGAGTAGTCCCTAGATACTTCCATAATGGCCCTC +>chr1.1_018698343|Alt_0002 +GGCTGAAAGTCATACATCTCACCCAATATTTTATCTTGCTTATCTGAGGAGTAGTCCCTAGATACTTCCATAATGGCCCTC +>chr1.1_018698343|RefMatch_0001 +GGCTGAAAGTCATACATCTCACCCAATATTTTATCTTGCATATCTGGGGAGTAGTCCCTAGATACTTCCATAATGGCCCTC +>chr1.1_018698343|Ref_0001 +GGCTGAAAGTCATACATCTCACCCAATATTTTATCTTGCATATCTGAGGAGTAGTCCCTAGATACTTCCATAATGGCCCTC +>chr1.1_018789059|AltMatch_0001 +CCATACCGACTTTTGAGTACACACCAACCATTATACCTGCCATAGCTTTATCGATCAGACCCTTATTGAGTCTATACTCAT +>chr1.1_018789059|AltMatch_0002 +CCATACCGACTTTTGAGTACACACCAACCATTGTACCTGCCATAGCTTTATCGATCAGACCCTTATTGAGTCTATACTCAT +>chr1.1_018789059|Alt_0002 +CCATACCGACTTTTGAGTACACACCAACCATTGTACCTGCCATAGCTTTATCAATCAGACCCTTATTGAGTCTATACTCAT +>chr1.1_018789059|RefMatch_0001 +CCATACCGACTTTTGAGTACACACCAACCATTGTACCTGCCATCACTTTATCAATCAGACCCTTATTGAGTCTATACTCAT +>chr1.1_018789059|Ref_0001 +CCATACCGACTTTTGAGTACACACCAACCATTGTACCTGCCATCGCTTTATCAATCAGACCCTTATTGAGTCTATACTCAT +>chr1.1_018934716|Alt_0002 +AACGGTTGTTCCATAGTTAACCACATCAACCCATGGTGTAGATGTTTTTAATACAACATGATTATGATCATAGATAGGAGC +>chr1.1_018934716|Ref_0001 +AACGGTTGTTCCATAGTTAACCACATCAACCCATGGTGTAGATCTTTTTAATACAACATGATTATGATCATAGATAGGAGC +>chr1.1_019009023|AltMatch_0001 +CAGGAGTTAACTCTCCCAGCTAATTTTTAGGTTGAGCTAACGTGGTGCTGCAAGTGAGGGTTCATCCTCTTTTAGACGAAA +>chr1.1_019009023|Alt_0002 +CAGGAGTTAACTCTCCCAGCTAATTTTTAGGTTGAGCTAACGCGGTGCTGCAAGTGAGGGTTCATCCTCTTTTAGACGAAA +>chr1.1_019009023|Ref_0001 +CAGGAGTTAACTCTCCCAGCTAATTTTTAGGTTGAGCTAACGCAGTGCTGCAAGTGAGGGTTCATCCTCTTTTAGACGAAA +>chr1.1_019232221|Alt_0002 +GAATATGCATTCGGAGCCCATGACTATCCATCAAGTGGTGTATTTGAGGTTGAACCTAGGCAGTGTCCTGGATTCAAGTTC +>chr1.1_019232221|Ref_0001 +GAATATGCATTCGGAGCCCATGACTATCCATCAAGTGGTGTATTTGAAGTTGAACCTAGGCAGTGTCCTGGATTCAAGTTC +>chr1.1_019281061|AltMatch_0001 +AGCAGAAGCCCATGGTGAAAGCTGACTAGCTATCTTCTCACCATCAACACCTTGTCTGAGTAAAACGTGAATTTCCTGAGA +>chr1.1_019281061|Alt_0002 +AGCAGAAGCCCATGGTGAAAGCTGACTAGCTATCTTCTCACTATCAACACCTTGTCTGAGTAAAACGTGAATTTCCTGAGA +>chr1.1_019281061|RefMatch_0001 +AGCAGAAGCCCATGGTGAAAGCTGACTAGCTATCTTCTCAGCATCAACACCTTGTCTGAGTAAAACGTGAATTTCCTGAGA +>chr1.1_019281061|RefMatch_0002 +AGCAGAAGCCCATGGTGAAAGCTGACTAGCTATCTTCTCAGCATTAACACCTTGTCTGAGTAAAACGTGAATTTCCTGAGA +>chr1.1_019281061|Ref_0001 +AGCAGAAGCCCATGGTGAAAGCTGACTAGCTATCTTCTCAGTATCAACACCTTGTCTGAGTAAAACGTGAATTTCCTGAGA +>chr1.1_019387175|Alt_0002 +TACTCCTGGTGTTGCACCGGTAATAGTCCTTTCTGAACTCGTCATTCTTCAACAGCTCATGCATTCTCTCAGCCTGAAAGC +>chr1.1_019387175|Ref_0001 +TACTCCTGGTGTTGCACCGGTAATAGTCCTTTCTGAACTCATCATTCTTCAACAGCTCATGCATTCTCTCAGCCTGAAAGC +>chr1.1_019596141|Alt_0002 +CGCCGTAAAATAAATGGCCCTAATATAGACTTCATACGACTAGTTAAATCTTTATCTTCTGCACTAAGTAACTTTTTTAAG +>chr1.1_019596141|Ref_0001 +CGCCGTAAAATAAATGGCCCTAATATAGACTTCATACGACTAGTTAAATCTCTATCTTCTGCACTAAGTAACTTTTTTAAG +>chr1.1_019780298|Alt_0002 +GTGTACAATTCATGAAAATATCTTTAAACTATGTTTACTTTGTTCTTAATTACAGCAGATTCTGTAAGTCCGAATTTACAT +>chr1.1_019780298|RefMatch_0001 +GTGTACAATTCATGAAAATATCTTTAAACTATGTTTTCTTTGTTCTTCATTACAGCAGATTCTGTAAGTCCGAATTTACAT +>chr1.1_019780298|RefMatch_0002 +GTGTACAATTCATGAAAATATCTTTAAACTTTGTTTTCTTTGTTCTTAATTACAGCAGATTCTGTAAGTCCGAATTTACAT +>chr1.1_019780298|Ref_0001 +GTGTACAATTCATGAAAATATCTTTAAACTATGTTTTCTTTGTTCTTAATTACAGCAGATTCTGTAAGTCCGAATTTACAT +>chr1.1_020097917|Alt_0002 +CCTCACCACAAACGGGTGATGAAATGATGGCATTTGGTGATGGCATTTGTTGGGAGGTTGGTTATGTAGTAGTGGAATTTG +>chr1.1_020097917|RefMatch_0001 +CCTCACCACAAACGGGTGATGAAATGATGGCATTTGATGATGGCATATGTTGGGAGGTTGGTTATGTAGTAGTGGAATTTG +>chr1.1_020097917|RefMatch_0002 +CCTCACCACAAACGGGTGATGAAATGATGGCATTTGGTGATGGCATATGTTGGAAGGTTGGTTATGTAGTAGTGGAATTTG +>chr1.1_020097917|Ref_0001 +CCTCACCACAAACGGGTGATGAAATGATGGCATTTGGTGATGGCATATGTTGGGAGGTTGGTTATGTAGTAGTGGAATTTG +>chr1.1_020310833|Alt_0002 +GTTCAATAGACTCTAATCTGTTAATTTCGCTTTCGCTTTCGCTATATATCTCATCTTGATATAACTTCGCATTAGATTTTT +>chr1.1_020310833|Ref_0001 +GTTCAATAGACTCTAATCTGTTAATTTCGCTTTCGCTTTCGCTATATATCTTATCTTGATATAACTTCGCATTAGATTTTT +>chr1.1_020548930|Alt_0002 +GGCAACTTTGGATTTATTCCCGATGTGTTTAGAGTATTGTCTCTGCTACAGGGTAGAGTGGAAGGTTCTAAGTTATATGCA +>chr1.1_020548930|RefMatch_0001 +GGCAACTTTGGATTTATTCCCGATGTGTTCAGAGTATTGTCTCTGCAACAGGGTAGAGTGGAAGGTTCTAAGTTATATGCA +>chr1.1_020548930|RefMatch_0002 +GGCAACTTTGGATTTATTCCCGATGTGTTTAGAGTATTATCTCTGCAACAGGGTAGAGTGGAAGGTTCTAAGTTATATGCA +>chr1.1_020548930|Ref_0001 +GGCAACTTTGGATTTATTCCCGATGTGTTTAGAGTATTGTCTCTGCAACAGGGTAGAGTGGAAGGTTCTAAGTTATATGCA +>chr1.1_020860458|Alt_0002 +TGTCAATTTTTCCAACTTGTCACTTTAAACCTTTAATTGAGGCTTTAATATTGTTCCAATGCTTCATGGAAATTTAAATGA +>chr1.1_020860458|Ref_0001 +TGTCAATTTTTCCAACTTGTCACTTTAAACCTTTAATTGAGGCTTTAATATTCTTCCAATGCTTCATGGAAATTTAAATGA +>chr1.1_021161903|Alt_0002 +ACTTATTTCAATCCAAACCAGACATATATGAGGTCTTTTTATGAAGTGTTAACAATTATATTTTCAGATAAATTTAATTTC +>chr1.1_021161903|Ref_0001 +ACTTATTTCAATCCAAACCAGACATATATGAGGTCTTTTTATGAAGTGTTCACAATTATATTTTCAGATAAATTTAATTTC +>chr1.1_022487705|AltMatch_0001 +AGCTGAGCTTATCCGTCTATCTACAGTACAACAATAATTGTTTTTAATATTTAAACTGGTTTCGCACTTCAACACTACTCA +>chr1.1_022487705|Alt_0002 +AGCTGAGCTTATCCGTCTATCTACAGTACGACAATAATTGTTTTTAATATTTAAACTGGTTTCGCACTTCAACACTACTCA +>chr1.1_022487705|Ref_0001 +AGCTGAGCTTATCCGTCTATCTACAGTACGACAATAATTGTTTTTAATATTTGAACTGGTTTCGCACTTCAACACTACTCA +>chr1.1_022582932|Alt_0002 +TCATTCACATTTAGAGAAGCAGTTAGAGATGTGGAGCTGCAAGGTTACTCCATTCCAAAAGGTTGGAAAGTCCTTCCACTC +>chr1.1_022582932|RefMatch_0001 +TCATTCACATTTAGAGAAGCAGTTAGAGATGTGAAGCTACAAGGTTACTCCATTCCAAAAGGTTGGAAAGTCCTTCCACTC +>chr1.1_022582932|RefMatch_0002 +TCATTCACATTTAGAGAAGCAGTTAGAGATGTGGAACTACAAGGTTACTCCATTCCAAAAGGTTGGAAAGTCCTTCCACTC +>chr1.1_022582932|RefMatch_0003 +TCATTCACATTTAGAGAAGCAGTTAGAGATGTGGAGATACAAGGTTACTCCATTCCAAAAGGTTGGAAAGTCCTTCCACTC +>chr1.1_022582932|RefMatch_0004 +TCATTCACATTTAGAGAAGCAGTTAGAGATGTGGAGCTACAAGGTTACACCATTCCAAAAGGTTGGAAAGTCCTTCCACTC +>chr1.1_022582932|RefMatch_0005 +TCATTCACATTTAGAGAAGCAGTTAGAGATGTGGAGTTACAAGGTTACTCCATTCCAAAAGGTTGGAAAGTCCTTCCACTC +>chr1.1_022582932|Ref_0001 +TCATTCACATTTAGAGAAGCAGTTAGAGATGTGGAGCTACAAGGTTACTCCATTCCAAAAGGTTGGAAAGTCCTTCCACTC +>chr1.1_023060630|AltMatch_0001 +CAAGACAAAGAGGTGGAGAGGGTTGAGTTGTTTGTTAGAAATACTGGATGAGACTTGGGTAGTAGTATGGTTTTAAAGGGT +>chr1.1_023060630|Alt_0002 +CAAGACAAAGAGGTGGAGAGGGTTGAGTTGTTTGTTAGAAATATTGGATGAGACTTGGGTAGTAGTATGGTTTTAAAGGGT +>chr1.1_023060630|Ref_0001 +CAAGACAAAGAGGTGGAGAGGGTTGACTTGTTTGTTAGAAATATTGGATGAGACTTGGGTAGTAGTATGGTTTTAAAGGGT +>chr1.1_023241568|Alt_0002 +GAAGAGACATAAAGCTTACATAAATCATATTTTGATTGTATCTATACTGTAAATCGTATAAAACTGACGGTTCGTTTAAAT +>chr1.1_023241568|Ref_0001 +GAAGAGACATAAAGCTTACATAAATCATATTTTGATTGTATCTATACTGTAGATCGTATAAAACTGACGGTTCGTTTAAAT +>chr1.1_023395952|Alt_0002 +CGAAGAAGATAGTCATGTAATGTTAAAAACTGTAAGTTCAGCTTTGGTAACGCTAAACAACCTTCTCCAGAATAATTTATG +>chr1.1_023395952|Ref_0001 +CGAAGAAGATAGTCATGTAATGTTAAAAATTGTAAGTTCAGCTTTGGTAACGCTAAACAACCTTCTCCAGAATAATTTATG +>chr1.1_023535207|AltMatch_0001 +TGTTTGAAGAAAGGCTGGTTAACTTCAAGCTGTGTATGATGGTTTTCCATAATACAATGTACAATATATGATGAATATATG +>chr1.1_023535207|Alt_0002 +TGTTTGAAGAAAGGCTGGTTAACTTCAAGCTGTGAATGATGGTTTTCCATAATACAATGTACAATATATGATGAATATATG +>chr1.1_023535207|Ref_0001 +TGTTTGAAGAAAGGCTGGTTAACTTCAAGCTGTGAATGATGGTTTTCCCTAATACAATGTACAATATATGATGAATATATG +>chr1.1_023709651|Alt_0002 +GAGGGTAGAGACATGACATATTTTGAATTTCTAAGGACATTTATATATGTGAAGTACAATATATGATGGCATCCATGTAAG +>chr1.1_023709651|RefMatch_0001 +GAGGGTAGAGACATGACATATTTTGAATTTCTAACGAGATTTATATATGTGAAGTACAATATATGATGGCATCCATGTAAG +>chr1.1_023709651|RefMatch_0002 +GAGGGTAGAGACATGACATGTTTTGAATTTCTAACGAGATTTATATATGTCAAGTACAATATATGATGGCATCCATGTAAG +>chr1.1_023709651|RefMatch_0003 +GAGGGTAGAGACATGACATGTTTTGAATTTCTAACGAGATTTATATATGTGAAGTACAATATATGATGGCATCCATGTAAG +>chr1.1_023709651|Ref_0001 +GAGGGTAGAGACATGACATATTTTGAATTTCTAAGGAGATTTATATATGTGAAGTACAATATATGATGGCATCCATGTAAG +>chr1.1_024489859|Alt_0002 +GCTAGAACCCTAACACCCGACTTAACAAGATTCCCTAGCATAGAGATGGTAGGAATCTCAAGGTTCTGAAAATCATATACC +>chr1.1_024489859|Ref_0001 +GCTAGAACCCTAACACCCGACTTAACAAGTTTCCCTAGCATAGAGATGGTAGGAATCTCAAGGTTCTGAAAATCATATACC +>chr1.1_024760634|AltMatch_0001 +CACCATCAAACCAAACGATACCTTTTTCCTTGTTTCAACTATAAACTTCCAAAACCTCACTACTTATCCTTCTGTTGAAGT +>chr1.1_024760634|Alt_0002 +CACCATCAAACCAAACGATACTTTTTTCCTTGTTTCAACTATAAACTTCCAAAACCTCACTACTTATCCTTCTGTTGAAGT +>chr1.1_024760634|RefMatch_0001 +CACCATCAAACCAAACGATACTTTCTTCCTAGTTTCAACTATAAACTTCCAAAACCTCACTACTTATCCTTCTGTTGAAGT +>chr1.1_024760634|RefMatch_0002 +CACCATCAAACCAAACGATACTTTCTTCCTTGTTTCAACTATAAACTTTCAAAACCTCACTACTTATCCTTCTGTTGAAGT +>chr1.1_024760634|RefMatch_0003 +CACCATCAAACCAAACGATACTTTCTTCCTTGTTTCAACTGTAAACTTCCAAAACCTCACTACTTATCCTTCTGTTGAAGT +>chr1.1_024760634|Ref_0001 +CACCATCAAACCAAACGATACTTTCTTCCTTGTTTCAACTATAAACTTCCAAAACCTCACTACTTATCCTTCTGTTGAAGT +>chr1.1_024951410|AltMatch_0001 +ACAGTTTATAATCAGACACAATAGAAACTTTCAGTGATGTTGCACATATAATTGGATGATAATGTGGAGAGAGAAAATACA +>chr1.1_024951410|Alt_0002 +ACAGTTTATAATCAGACACAATAGAAACTTTCAGTGATGTTGCACACATAATTGGATGATAATGTGGAGAGAGAAAATACA +>chr1.1_024951410|Ref_0001 +ACAGTTTATAATCAGACACAATAGAAACTTTCAGTGATGTTGCTCACATAATTGGATGATAATGTGGAGAGAGAAAATACA +>chr1.1_025281938|Alt_0002 +CATTATGGTACTGAGATTTAAAAGGTTGTTTAATTGTTAGAGTCTGGTTTGAGAAGAAAGTAGACTGGCCACGTTATATAT +>chr1.1_025281938|RefMatch_0001 +CATTATGGTACTGAGATTTAAAAGGTTGTTTAATTGTTAGAGTTTGGATTGAGAAGAAAGTAGACTGGCCACGTTATATAT +>chr1.1_025281938|Ref_0001 +CATTATGGTACTGAGATTTAAAAGGTTGTTTAATTGTTAGAGTCTGGATTGAGAAGAAAGTAGACTGGCCACGTTATATAT +>chr1.1_025474859|Alt_0002 +AACATTCGATCTCATATTCTCCACTTCTTGAGCTCGCTTGCTATCTTTAACTAGTTGGTTTATCTTCTTTATCTTTTTCAA +>chr1.1_025474859|RefMatch_0001 +AACATTCGATCTCATATTCTCCACTTCTTGAGCTCGCTTGCTATCTTTCACTAATTGGTTTATCTTCTTTATCTTTTTCAA +>chr1.1_025474859|RefMatch_0002 +AACATTCGATCTCATATTCTCCACTTCTTGAGCTCGTTTGCTATCTTTCACTAGTTGGTTTATCTTCTTTATCTTTTTCAA +>chr1.1_025474859|Ref_0001 +AACATTCGATCTCATATTCTCCACTTCTTGAGCTCGCTTGCTATCTTTCACTAGTTGGTTTATCTTCTTTATCTTTTTCAA +>chr1.1_025688638|Alt_0002 +GGTCAGTTGCATTTTGGGTATTTACACCTACATCTTACTTTGCCCAATATAGTTTGCATGAATAAAGACCAAATGAAAGTA +>chr1.1_025688638|RefMatch_0001 +GGTCAGTTGCATTTTGGGTATTTACACCTACATCTTGCTTTGCTCAATATAGTTTGCATGAATAAAGACCAAATGAAAGTA +>chr1.1_025688638|RefMatch_0002 +GGTCAGTTGCATTTTGGGTATTTACACCTACATCTTGCTTTTCCCAATATAGTTTGCATGAATAAAGACCAAATGAAAGTA +>chr1.1_025688638|RefMatch_0003 +GGTCAGTTGCATTTTGGGTATTTACACCTACATCTTGCTTTTCCCAATGTAGTTTGCATGAATAAAGACCAAATGAAAGTA +>chr1.1_025688638|Ref_0001 +GGTCAGTTGCATTTTGGGTATTTACACCTACATCTTGCTTTGCCCAATATAGTTTGCATGAATAAAGACCAAATGAAAGTA +>chr1.1_025728959|Alt_0002 +GTTCCCCACATGTTCATTTTTATTGTCTTTTTCCAATTCATGGTTGTGATTCTGTACCTTGATATGGGCACTTTCTTTGGT +>chr1.1_025728959|RefMatch_0001 +GTTCCCCACATGTTCATTTTTATTGTCTCTTCCCAATTCATGGTTGTGATTCTGTACCTTGATATGGGCACTTTCTTTGGT +>chr1.1_025728959|RefMatch_0002 +GTTCCCCACATGTTCATTTTTATTGTCTCTTTCCAATTCATGGCTGTGATTCTGTACCTTGATATGGGCACTTTCTTTGGT +>chr1.1_025728959|RefMatch_0003 +GTTCCCCACATGTTCATTTTTATTGTCTCTTTCCAATTCATGGTTGTGATTCCGTACCTTGATATGGGCACTTTCTTTGGT +>chr1.1_025728959|RefMatch_0004 +GTTCCCCACATGTTCATTTTTATTGTCTCTTTCCAATTCATGGTTGTGATTCTATACCTTGATATGGGCACTTTCTTTGGT +>chr1.1_025728959|Ref_0001 +GTTCCCCACATGTTCATTTTTATTGTCTCTTTCCAATTCATGGTTGTGATTCTGTACCTTGATATGGGCACTTTCTTTGGT +>chr1.1_026050142|Alt_0002 +AGAGACCTATGCTGCAGTCCTTGCGCAGACCCATTCCTTCTTGAAAATGCCCCCACTGCACCAGATAATCTATCTCGAATT +>chr1.1_026050142|Ref_0001 +AGAGACCTATGCTGCAGTCCTTGCGCAGAGCCATTCCTTCTTGAAAATGCCCCCACTGCACCAGATAATCTATCTCGAATT +>chr1.1_026445102|AltMatch_0001 +CAGACTCCCCGATATAGAACCTAGCTACGTCTTCAGTCAGTATATCTTTCCGCATCAGCAACGTCATCATATCTCCACCGG +>chr1.1_026445102|AltMatch_0002 +CAGACTCCCCGATATAGAACCTAGCTTCATCTTCAGTCAGTACTTCTTTCCGCATCAGCAACGTCATCATATCTCCACCGG +>chr1.1_026445102|Alt_0002 +CAGACTCCCCGATATAGAACCTAGCTACATCTTCAGTCAGTATATCTTTCCGCATCAGCAACGTCATCATATCTCCACCGG +>chr1.1_026445102|Ref_0001 +CAGACTCCCCGATATAGAACCTAGCTACATCTTCAGTCAGTATATCTTTGCGCATCAGCAACGTCATCATATCTCCACCGG +>chr1.1_026502181|AltMatch_0001 +TCACCTTCAAGTACACACAAATTTATTACAAATTGGACCATGAATAATTGGTCACACAAACTCAAACCCTTTAGTTACTGC +>chr1.1_026502181|Alt_0002 +TCACCTTCAAGTACACACAAATTTATTACAAATTGGACCGTGAATAATTGGTCACACAAACTCAAACCCTTTAGTTACTGC +>chr1.1_026502181|Ref_0001 +TCACCTTCAAGTACACACAAATTTATTACAAAATGGACCGTGAATAATTGGTCACACAAACTCAAACCCTTTAGTTACTGC +>chr1.1_026672067|Alt_0002 +CTAAATAAAGTAACACAATCAACCTTTATTAGGGGGTTCTCTACTGTGCCTTTCAATCAACTCCATTGTGATACGATTATG +>chr1.1_026672067|Ref_0001 +CTAAATAAAGTAACACAATCAACCTTTATTAGGGGGTTCTCTACTGTGTCTTTCAATCAACTCCATTGTGATACGATTATG +>chr1.1_026865008|Alt_0002 +CCTACGGTTAGTAGTGAATTATGTCTTAGGTTTAATTCAATAGTGATCAAGTAAAGAAAGTCATTTAGCGAAATAATTACT +>chr1.1_026865008|Ref_0001 +CCTACGGTTAGTAGTGAATTATGTCTTAGATTTAATTCAATAGTGATCAAGTAAAGAAAGTCATTTAGCGAAATAATTACT +>chr1.1_026940687|AltMatch_0001 +ACCGGTGTTTATTGAGAATGTTCAAACCCATATTTGTAACGTAGCAAAATCTTCAACTCTGAAGTCTCACTTAAAATTCCA +>chr1.1_026940687|Alt_0002 +ACCGGTGTTTATTGAGAATGTTCAAACCCATATTTGTGACGTAGCAAAATCTTCAACTCTGAAGTCTCACTTAAAATTCCA +>chr1.1_026940687|Ref_0001 +ACCGGTGTTTATTGAGAATGTTCAAACCCATATTTGTGATGTAGCAAAATCTTCAACTCTGAAGTCTCACTTAAAATTCCA +>chr1.1_027050989|AltMatch_0001 +GATCCTAGTAAAGATGTTCATGGTTGGGGAGTTAATGAACGTGGTGTTTCGTTTACTTTTGGTGCTAGTAAGATTCAAGAG +>chr1.1_027050989|Alt_0002 +GATCCTAGTAAAGATGTTCATGGTTGGGGAGTTAATGAACGTGGTGTTTCATTTACTTTTGGTGCTAGTAAGATTCAAGAG +>chr1.1_027050989|RefMatch_0001 +GATCCTAGTAAAGATGTTCATGGTTGGGGTGTTAATGAACGTGGTGTTTCGTTTACTTTTGGTGCTAGTAAGATTCAAGAG +>chr1.1_027050989|Ref_0001 +GATCCTAGTAAAGATGTTCATGGTTGGGGTGTTAATGAACGTGGTGTTTCATTTACTTTTGGTGCTAGTAAGATTCAAGAG +>chr1.1_027377103|Alt_0002 +ATCCAAACTATGGATATATCCCAATGTGGCATTATCTTCCTCAATCAGCTCGTGATACGTCCCAAGATCATGAGCTCAGGC +>chr1.1_027377103|Ref_0001 +ATCCAAACTATGGATATATCCCAATGTGGCATTATCTTCCTCAATCAGCTCGCGATACGTCCCAAGATCATGAGCTCAGGC +>chr1.1_027461652|Alt_0002 +GCTTCTTAATAACACTAAATAGATGGGTTCTTATTTGTCACATTAAATTATCAATGTTTCTGGAATCCTGAGGTAGAGATG +>chr1.1_027461652|Ref_0001 +GCTTCTTAATAACACTAAATAGATGGGTTCTTATTTGTCACATTAAGTTATCAATGTTTCTGGAATCCTGAGGTAGAGATG +>chr1.1_027966972|AltMatch_0001 +TTTCGGTTTCCAAAGTTAATCTTATTGTTCATTGTAACTGAAAGATATCCATGTGTATGTGATGGTCTTCAACTTGTCTCT +>chr1.1_027966972|AltMatch_0002 +TTTCGGTTTCCAAAGTTAATCTTATTGTTCATTGTAATTGAAAGATATCCATGTGTATGTGATGGTCTTCAACTTGTCTCT +>chr1.1_027966972|Alt_0002 +TTTCGGTTTCCAAAGTTAATCTTATTGTTCATTATAATTGAAAGATATCCATGTGTATGTGATGGTCTTCAACTTGTCTCT +>chr1.1_027966972|Ref_0001 +TTTCGGTTTCCAAAGTTAATCTTATTGTTCATTATAATTGAAATATATCCATGTGTATGTGATGGTCTTCAACTTGTCTCT +>chr1.1_028084165|Alt_0002 +GACTGGTGTCAATGGTTACACAGTATTCAGGCCTTCGAATGGTCAGTAGAGGGAAAGGATGGCAACGAATGTAATAATGTG +>chr1.1_028084165|RefMatch_0001 +GACTGGTGTCAATGGTTACACAGTATTCAGACCTTCAAATGGTCAGTAGAGGGAAAGGATGGCAACGAATGTAATAATGTG +>chr1.1_028084165|Ref_0001 +GACTGGTGTCAATGGTTACACAGTATTCAGGCCTTCAAATGGTCAGTAGAGGGAAAGGATGGCAACGAATGTAATAATGTG +>chr1.1_028189850|Alt_0002 +TGATGGATAATCATAGGCAAGCACTTGGGAGCTTTGCAATGGTAGCATTACTCTTTCTTGGTTTTATTTTCATTTACCATT +>chr1.1_028189850|Ref_0001 +TGATGGATAATCATAGGCAAGCACTTGGGAGTTTTGCAATGGTAGCATTACTCTTTCTTGGTTTTATTTTCATTTACCATT +>chr1.1_028465946|Alt_0002 +GTTGGCATGGACTGATTCTTGACTCCTGTTGGTAGTTATATATAATTTGTGCCTTTGGAATTTGTTGGGCGTTTCTTTGGT +>chr1.1_028465946|Ref_0001 +GTTGGCATGGACTGATTCTTGACTCCTGTTGGTAGTTATATATAGTTTGTGCCTTTGGAATTTGTTGGGCGTTTCTTTGGT +>chr1.1_028687110|Alt_0002 +TCCTAAGGCTTTCTTTGACCTATTGCTACCTTGTGAGTGATATGAATTGTATATTTTGCTGCCTCCTAATAATAAGACTGT +>chr1.1_028687110|RefMatch_0001 +TCCTAAGGCTTTCTTTGACCTATTGCTACCTTGTGAGTAATATGAATTATATATTTTGCTGCCTCCTAATAATAAGACTGT +>chr1.1_028687110|RefMatch_0002 +TCCTAAGGCTTTCTTTGACCTATTGCTACCTTGTGAGTAATATGAATTGTCTATTTTGCTGCCTCCTAATAATAAGACTGT +>chr1.1_028687110|RefMatch_0003 +TCCTAAGGCTTTCTTTGACCTATTGCTACCTTGTTAGTAATATGAATTGTATATTTTGCTGCCTCCTAATAATAAGACTGT +>chr1.1_028687110|Ref_0001 +TCCTAAGGCTTTCTTTGACCTATTGCTACCTTGTGAGTAATATGAATTGTATATTTTGCTGCCTCCTAATAATAAGACTGT +>chr1.1_028857948|AltMatch_0001 +GTTCCAAATGCTTATTTTCATAGTATAAATAATTAATTAATGTGTCTTTTTTCCTAAAAAATAGGTGGGGTGTGAGTGTTA +>chr1.1_028857948|Alt_0002 +GTTCCAAATGCTTATTTTCATAGTATAAATAATTAATTAATGTGTCTTTTCTCCTAAAAAATAGGTGGGGTGTGAGTGTTA +>chr1.1_028857948|Ref_0001 +GTTCCAAATGCTTATTTTCATAGTATAAATAAATAATTAATGTGTCTTTTCTCCTAAAAAATAGGTGGGGTGTGAGTGTTA +>chr1.1_028955804|Alt_0002 +GTCCTTTATTTTTCCAACATAATTGTTGTTCTTGACAAATTAGGTTATGGTTCTAATATGAAGAATCTCATGTATATAAGC +>chr1.1_028955804|RefMatch_0001 +GTCCTTTATTTTTCCAACATAATTGTTGTTCTTAACAAATTAGGTTGTGGTTCTAATATGAAGAATCTCATGTATATAAGC +>chr1.1_028955804|RefMatch_0002 +GTCCTTTATTTTTCCAACATAATTGTTGTTCTTGACAAATTAGGTTGTAGTTCTAATATGAAGAATCTCATGTATATAAGC +>chr1.1_028955804|RefMatch_0003 +GTCCTTTATTTTTCCAACATAATTGTTGTTCTTGACAAATTTGGTTGTGGTTCTAATATGAAGAATCTCATGTATATAAGC +>chr1.1_028955804|RefMatch_0004 +GTCCTTTATTTTTCCAACATAATTGTTGTTCTTGGCAAATTAGGTTGTGGTTCTAATATGAAGAATCTCATGTATATAAGC +>chr1.1_028955804|Ref_0001 +GTCCTTTATTTTTCCAACATAATTGTTGTTCTTGACAAATTAGGTTGTGGTTCTAATATGAAGAATCTCATGTATATAAGC +>chr1.1_029222133|Alt_0002 +GAACTAACGGGTTTAATCTAGAGTCCACATATTTAGAAACCATATTTGAAGAACTTGTTTCTGTTTTTTTTAGTAAAAAAA +>chr1.1_029222133|Ref_0001 +GAACTAACGGGTTTAATCTAGAGTCCACACATTTAGAAACCATATTTGAAGAACTTGTTTCTGTTTTTTTTAGTAAAAAAA +>chr1.1_029326140|Alt_0002 +CACATTTCCATTCAACCTGACAATGACTTGGTGCTTTCTGCTGATGAAATTTGCACAATATATGATGTACTACAGGCTTCA +>chr1.1_029326140|RefMatch_0001 +CACATTTCCATTCAACCTGACAATGACTTAGTGCTCTCTGCTGATGAAATTTGCACAATATATGATGTACTACAGGCTTCA +>chr1.1_029326140|RefMatch_0002 +CACATTTCCATTCAACCTGACAATGACTTAGTGCTTTCTGCTGATGAAATTTGAACAATATATGATGTACTACAGGCTTCA +>chr1.1_029326140|Ref_0001 +CACATTTCCATTCAACCTGACAATGACTTAGTGCTTTCTGCTGATGAAATTTGCACAATATATGATGTACTACAGGCTTCA +>chr1.1_029362039|Alt_0002 +GGGAGCAATGTACTTTGCAATGTTATTCATCAGTTGGGATCTTAATAACTCAGCTAGAAAGTAAGGAACCTAATTTATCAC +>chr1.1_029362039|Ref_0001 +GGGAGCAATGTACTTTGCAATGTTATTCATCAGTTGGGATCTGAATAACTCAGCTAGAAAGTAAGGAACCTAATTTATCAC +>chr1.1_029584457|Alt_0002 +CAAATTAAAATACAAAGAATTAATCAGAGGTAATGACTTATACCAGTTTTTCTGAAATGTAGTTAGCAAGGAGTGATCCTC +>chr1.1_029584457|Ref_0001 +CAAATTAAAATACAAAGAATTAATCAGAGGTGATGACTTATACCAGTTTTTCTGAAATGTAGTTAGCAAGGAGTGATCCTC +>chr1.1_030458048|Alt_0002 +GAAACCAATACCACAGTCTGCTAGGCGCTTCCTGTTTTGTTGCCAATTGCGGTCACAACGCCAACAATCGTCAATAGGGTT +>chr1.1_030458048|RefMatch_0001 +GAAACCAATACCACAGTCTGCCAGACGCTTCCTGTTTTGTTGCCAATTGCGGTCACAACGCCAACAATCGTCAATAGGGTT +>chr1.1_030458048|RefMatch_0002 +GAAACCAATACCACAGTCTGCTAGACGCTTCCTGTTTTGTTGCCAATTACGGTCACAACGCCAACAATCGTCAATAGGGTT +>chr1.1_030458048|RefMatch_0003 +GAAACCAATACCACAGTCTGCTAGACGCTTCCTGTTTTGTTGCCAATTGCAGTCACAACGCCAACAATCGTCAATAGGGTT +>chr1.1_030458048|Ref_0001 +GAAACCAATACCACAGTCTGCTAGACGCTTCCTGTTTTGTTGCCAATTGCGGTCACAACGCCAACAATCGTCAATAGGGTT +>chr1.1_030744456|Alt_0002 +CAAACGTGATTACTAGACCTAATGATATATATGCCTCCTGTTTCGTTAACATACAGTGCGTCTGATCAAGTCGTACGGAAT +>chr1.1_030744456|Ref_0001 +CAAACGTGATTACTAGACCTAATGATATATATGCCTCCTGTTTGGTTAACATACAGTGCGTCTGATCAAGTCGTACGGAAT +>chr1.1_030969636|AltMatch_0001 +GGTGAGTGCTCACAAAGCTCCTAGTCTTTTTACTTCTCCATCCCTTTCTGAATATTGTTCTTATTCTTGTATTTGCTTGTA +>chr1.1_030969636|Alt_0002 +GGTGAGTGCTCACAAAGCTCCTAGTCTTTTCAGTTCTCCATCCCTTTCTGAATATTGTTCTTATTCTTGTATTTGCTTGTA +>chr1.1_030969636|RefMatch_0001 +GGTGAGTGCTCACAAAGCTCCTAGTCTCTTCAGTTCTCCATCCTTTTCTGAATATTGTTCTTATTCTTGTATTTGCTTGTA +>chr1.1_030969636|RefMatch_0002 +GGTGAGTGCTCACAAAGCTCCTAGTCTCTTTACTTCTCCATCCCTTTCTGAATATTGTTCTTATTCTTGTATTTGCTTGTA +>chr1.1_030969636|Ref_0001 +GGTGAGTGCTCACAAAGCTCCTAGTCTCTTCAGTTCTCCATCCCTTTCTGAATATTGTTCTTATTCTTGTATTTGCTTGTA +>chr1.1_031180522|Alt_0002 +GGGGGACCAATATCTGATACCTGTCTTATTTTGGCTCTAGAATTGAAAACAGAACATTTTTACCATGATTTTCTTTTATAT +>chr1.1_031180522|Ref_0001 +GGGGGACCAATATCTGATACCTGTCTTATTTTGGCTCTATAATTGAAAACAGAACATTTTTACCATGATTTTCTTTTATAT +>chr1.1_031360007|Alt_0002 +CAATTTTACAAGATATAAATTCTGCTTTTATGTTTCAGTGTTATGTAATTTCTGTGGTGTAATAGAAGTATCAATCTCAAA +>chr1.1_031360007|Ref_0001 +CAATTTTACAAGATATAAATTCTGCTTTTATGTTTCAGTGTTATGTAATTTCTATGGTGTAATAGAAGTATCAATCTCAAA +>chr1.1_031442927|Alt_0002 +TAATATCAACAGCATTCTTTGCAGCAACTGTCTCCTCGGCATGAATGGTAATTGCCCCTTGATTTATTTGACTACTATTCC +>chr1.1_031442927|RefMatch_0001 +TAATATCAACAGCATTCTTTGCAGCAACTGTCTCCTCAACATGAATGGTAATTGCCCCTTGATTTATTTGACTACTATTCC +>chr1.1_031442927|Ref_0001 +TAATATCAACAGCATTCTTTGCAGCAACTGTCTCCTCAGCATGAATGGTAATTGCCCCTTGATTTATTTGACTACTATTCC +>chr1.1_031546487|Alt_0002 +AATGAATTACTATGACTATAATACTAAGTCCGATCCAATCATGTGTATGTTTTCTTCTTCTGGGTTATGAGAAGAATTAGT +>chr1.1_031546487|RefMatch_0001 +AATGAATTACTATGACTATAATACTAAGTCCTATCCAATCATGTTTATGTTTTCTTCTTCTGGGTTATGAGAAGAATTAGT +>chr1.1_031546487|Ref_0001 +AATGAATTACTATGACTATAATACTAAGTCCTATCCAATCATGTGTATGTTTTCTTCTTCTGGGTTATGAGAAGAATTAGT +>chr1.1_031816459|AltMatch_0001 +GGGACAAATTTGAGAATGGACAAGGAGCATTGGTATTCTTTTGGAATATGCATCAATTTGTCTTATAATGAATGTTTGACC +>chr1.1_031816459|Alt_0002 +GGGACAAATTTGAGAATGGACAAGGAGCATTGGTACTCTTTTGGAATATGCATCAATTTGTCTTATAATGAATGTTTGACC +>chr1.1_031816459|RefMatch_0001 +GGGACAAATTTGAGAATGGACAAGGAGCATTGATGCTCCTTTGGAATATGCATCAATTTGTCTTATAATGAATGTTTGACC +>chr1.1_031816459|RefMatch_0002 +GGGACAAATTTGAGAATGGACAAGGAGCATTGATGCTCTTTTGGAATATGCATCAATTTGTCTTATAATGAATGTTTGACC +>chr1.1_031816459|RefMatch_0003 +GGGACAAATTTGAGAATGGACAAGGAGCATTGGTGCTCTTTTAGAATATGCATCAATTTGTCTTATAATGAATGTTTGACC +>chr1.1_031816459|Ref_0001 +GGGACAAATTTGAGAATGGACAAGGAGCATTGGTGCTCTTTTGGAATATGCATCAATTTGTCTTATAATGAATGTTTGACC +>chr1.1_031907509|Alt_0002 +GAGCTGTGAGTTTCTCTCGAACATACAATTCTTTTGTTTTATTAAAGTCGTTTTATGTTAACTGTACCATATCTCTGGTAG +>chr1.1_031907509|Ref_0001 +GAGCTGTGAGTTTCTCTCGAACATACAATTCTTTTGTTTTATTAAAGTCATTTTATGTTAACTGTACCATATCTCTGGTAG +>chr1.1_032107042|AltMatch_0001 +TTGTTTAAAGCCCTTAAGGTTGGGACTTGGAGTAAAGTCAATAACACCATTTCGGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|AltMatch_0002 +TTGTTTAAAGCCCTTAAGGTTGGGACTTGGAGTAAAGTCGATAACACCATTTCAGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|AltMatch_0003 +TTGTTTAAAGCCCTTAAGGTTGGGACTTGGAGTAAAGTCGATAACACCATTTCGGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|AltMatch_0004 +TTGTTTAAAGCCCTTAAGGTTGGGACTTGGAGTAAAGTCGATAACACCATTTTGGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|Alt_0002 +TTGTTTAAAGCCCTTAAGGTTGGGACTTTGAGTAAAGTCGATAACACCATTTTGGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|RefMatch_0001 +TTGTTTAAAGCCCTTAAGGTTGGGACTTGGAGCAATGTCGATAACACCATTTCGGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|RefMatch_0002 +TTGTTTAAAGCCCTTAAGGTTGGGACTTGGAGTAATGCCGATAACACCATTTCCGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|RefMatch_0003 +TTGTTTAAAGCCCTTAAGGTTGGGACTTGGAGTAATGTCGATAACACCATTTAGGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|RefMatch_0004 +TTGTTTAAAGCCCTTAAGGTTGGGACTTGGAGTAATGTCGATAACACCATTTCCGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|RefMatch_0005 +TTGTTTAAAGCCCTTAAGGTTGGGACTTGGAGTAATGTCGATAACACCATTTCGGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|RefMatch_0006 +TTGTTTAAAGCCCTTAAGGTTGGGACTTTGAGTAATGTCGATAACACCATTTCGGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032107042|Ref_0001 +TTGTTTAAAGCCCTTAAGGTTGGGACTTTGAGTAATGTCGATAACACCATTTTGGTTGATTCATTTTGTCACAAACCATTC +>chr1.1_032180745|AltMatch_0001 +TCTTGAGTTCTTGTCCTTCTTCTCATTCTTCTCTTTCGTTTTTGTCAAAAACTACTATTTCAAATGGATCATTTTTCTTCT +>chr1.1_032180745|Alt_0002 +TCTTGAGTTCTTGTCCTTCTTCTCATTCTTCTCTTTCGTTTTTGTCGAAAACTACTATTTCAAATGGATCATTTTTCTTCT +>chr1.1_032180745|RefMatch_0001 +TCTTGAGTTCTTGTCCTTCTTCTCATTCTTCTCTTTTGTTTTTGTCAAAAACTACTATTTCAAATGGATCATTTTTCTTCT +>chr1.1_032180745|RefMatch_0002 +TCTTGAGTTCTTGTCCTTCTTCTCATTCTTCTCTTTTGTTTTTGTCAAAACTACTATTTCAAATGGATCATTTTTCTTCTA +>chr1.1_032180745|RefMatch_0003 +TCTTGAGTTCTTGTCCTTCTTCTCATTCTTCTCTTTTGTTTTTGTTAAAAACTACTATTTCAAATGGATCATTTTTCTTCT +>chr1.1_032180745|Ref_0001 +TCTTGAGTTCTTGTCCTTCTTCTCATTCTTCTCTTTTGTTTTTGTCGAAAACTACTATTTCAAATGGATCATTTTTCTTCT +>chr1.1_032924623|AltMatch_0001 +TGGTATTGATATCATTGTGTTGGAGAGCATTATTCATCATTGATTGTGGAATGGTTGCTGTTATTATTGATAATAGCATGG +>chr1.1_032924623|Alt_0002 +TGGTATTGATATCATTGTGTTGGAGAGCATTATTCATCATTGGTTGTGGAATGGTTGCTGTTATTATTGATAATAGCATGG +>chr1.1_032924623|RefMatch_0001 +TGGTATTGATATCATTGTGTTGGAGAGCATTATTCATCATTGATTGTGGAGTGGTTGCTGTTATTATTGATAATAGCATGG +>chr1.1_032924623|RefMatch_0002 +TGGTATTGATATCATTGTGTTGGAGAGCATTATTCATCATTGGTTGTGGAGTGTTTGCTGTTATTATTGATAATAGCATGG +>chr1.1_032924623|Ref_0001 +TGGTATTGATATCATTGTGTTGGAGAGCATTATTCATCATTGGTTGTGGAGTGGTTGCTGTTATTATTGATAATAGCATGG +>chr1.1_033171704|Alt_0002 +GGTGCTTCTATTTTGGAGTTCTTAAAAAGTTTTCTTTCACATGAAGATCCAAATATGCGTGCAAAAGCTTGCAGTGCTCTT +>chr1.1_033171704|RefMatch_0001 +GGTGCTTCTATTTTGGAGTTCTTAAAAAGTTTTCTTTTGCATGAAGATCCAAATATGCGTGCAAAAGCTTGCAGTGCTCTT +>chr1.1_033171704|Ref_0001 +GGTGCTTCTATTTTGGAGTTCTTAAAAAGTTTTCTTTCGCATGAAGATCCAAATATGCGTGCAAAAGCTTGCAGTGCTCTT +>chr1.1_034199458|Alt_0002 +CCTCATTAGAATCCTTTAGAAAGGAAAACATATTTTTTGCTGCAGGAGTTTTCTCCAATATACTGTTTTAACAAAACCAAT +>chr1.1_034199458|RefMatch_0001 +CCTCATTAGAATCCTTTAGAAAGGAAAACATATTTTTTGTTGCAGGTGTTTTCTCCAATATACTGTTTTAACAAAACCAAT +>chr1.1_034199458|Ref_0001 +CCTCATTAGAATCCTTTAGAAAGGAAAACATATTTTTTGCTGCAGGTGTTTTCTCCAATATACTGTTTTAACAAAACCAAT +>chr1.1_034284365|AltMatch_0001 +CCAATTTCCTTTTTTGGATTTGTGTAAATTCACTTTTCATATATTTATTGTGCTACACACCAGCTCTGGAGGAGATACTGT +>chr1.1_034284365|Alt_0002 +CCAATTTCCTTTTTTGGATTTGTGTAAATTCACTTTTCATATATATATTGTGCTACACACCAGCTCTGGAGGAGATACTGT +>chr1.1_034284365|RefMatch_0001 +CCAATTTCCTTTTTTGGATTTGTGTAAATACACTTTTCATATATATATTGTTCTACACACCAGCTCTGGAGGAGATACTGT +>chr1.1_034284365|RefMatch_0002 +CCAATTTCCTTTTTTGGATTTGTGTAAATTCACTTTTCATATATTTATTGTTCTACACACCAGCTCTGGAGGAGATACTGT +>chr1.1_034284365|Ref_0001 +CCAATTTCCTTTTTTGGATTTGTGTAAATTCACTTTTCATATATATATTGTTCTACACACCAGCTCTGGAGGAGATACTGT +>chr1.1_034579746|Alt_0002 +ACCAACTGGTAGAAAAAGGGTGACCTACCATGGACCAGCAATGGCCTTCCATTCAATGGTAATGAAGACATTCATAAAACA +>chr1.1_034579746|RefMatch_0001 +ACCAACTGGTAGAAAAAGGGTGACCTACCATGGGCCTGCAATGGCCTTCCATTCAATGGTAATGAAGACATTCATAAAACA +>chr1.1_034579746|Ref_0001 +ACCAACTGGTAGAAAAAGGGTGACCTACCATGGACCTGCAATGGCCTTCCATTCAATGGTAATGAAGACATTCATAAAACA +>chr1.1_034663420|Alt_0002 +CAATGACGATTCCCTCTCCCTTTCCTAGTATTGGTTAAAATGAATGTGATTGATGGTAACAAACAAACACATAATAAATTG +>chr1.1_034663420|Ref_0001 +CAATGACGATTCCCTCTCCCTTTCCTAGTATTGGTTAAAATGAATGTCATTGATGGTAACAAACAAACACATAATAAATTG +>chr1.1_034929778|AltMatch_0001 +GGAGGGGAAAGGTAGAAGCCTGAGGGGCACGGTTGTTTATTACGATGGCCAGATGAATGATGCACGACTTAATGTTGGGTT +>chr1.1_034929778|Alt_0002 +GGAGGGGAAAGGTAGAAGCTTGAGGGGCACGGTTGTTTATTACGATGGCCAGATGAATGATGCACGACTTAATGTTGGGTT +>chr1.1_034929778|Ref_0001 +GGAGGGGAAAGGTAGAAGCTTGAGGGGCACAGTTGTTTATTACGATGGCCAGATGAATGATGCACGACTTAATGTTGGGTT +>chr1.1_035085053|Alt_0002 +ACCATCCCTGGTAACATGAATAGATATCTTTTTCTTCTCTTTGTCCAAATCTAAGAATTGCAGAGATTGCTGATAGTCACT +>chr1.1_035085053|Ref_0001 +ACCATCCCTGGTAACATGAATAGAAATCTTTTTCTTCTCTTTGTCCAAATCTAAGAATTGCAGAGATTGCTGATAGTCACT +>chr1.1_035253375|Alt_0002 +ACTCCAAAATTAACTCCCAAGCACCTAACCTCACTTAACGTTCTTAAATCCTTCACCAACCTATCGACTTTATAACATCCA +>chr1.1_035253375|RefMatch_0001 +ACTCCAAAATTAACTCCCAAGCACCTAACCTCACCTCACGTTCTTAATTCCTTCACCAACCTATCGACTTTATAACATCCA +>chr1.1_035253375|RefMatch_0002 +ACTCCAAAATTAACTCCCAAGCACCTAACCTCACTACACGTTCTTAAATCCTTCACCAACCTATCGACTTTATAACATCCA +>chr1.1_035253375|RefMatch_0003 +ACTCCAAAATTAACTCCCAAGCACCTAACCTCACTCCACGTTCTTAAATCCTTCACCAACCTATCGACTTTATAACATCCA +>chr1.1_035253375|RefMatch_0004 +ACTCCAAAATTAACTCCCAAGCACCTAACCTCACTTCACATTCTTAAATCCTTTACCAACCTATCGACTTTATAACATCCA +>chr1.1_035253375|Ref_0001 +ACTCCAAAATTAACTCCCAAGCACCTAACCTCACTTCACGTTCTTAAATCCTTCACCAACCTATCGACTTTATAACATCCA +>chr1.1_035517292|Alt_0002 +GGGTCACTGTATTAATCGATAGGTGTATCTTTAATGTAAATGGGAAAATCTTGGAGGATTTGGTCTTGGCTGCCGAAGCAG +>chr1.1_035517292|Ref_0001 +GGGTCACTGTATTAATCGATAGGTGTATCTTTAATGGAAATGGGAAAATCTTGGAGGATTTGGTCTTGGCTGCCGAAGCAG +>chr1.1_035606739|Alt_0002 +GTCCCGAATCTGAAACTGCAGTGAAGTATTGAATAATTTTTAGCCAAGAATAAATAATGGGTGTACTTGTATATATTTATT +>chr1.1_035606739|RefMatch_0001 +GTCCCGAATCTGAAACTGCAGTGAAGTATTGAATGATTTTTAGCCAACAATAAATAATGGGTGTACTTGTATATATTTATT +>chr1.1_035606739|Ref_0001 +GTCCCGAATCTGAAACTGCAGTGAAGTATTGAATAATTTTTAGCCAACAATAAATAATGGGTGTACTTGTATATATTTATT +>chr1.1_035758205|Alt_0002 +CTCATCTCAAGATCTTTTGTATTCTTAATCTTAGCTTCTTGAATGACTCTCTGTTGCTTCTGTTCTTCCTTAAGCTCTGCC +>chr1.1_035758205|RefMatch_0001 +CTCATCTCAAGATCTTTTGTATTCTTAATCCGAGCTTCTTGAATGACTCTCTGTTGCTTCTGTTCTTCCTTAAGCTCTGCC +>chr1.1_035758205|RefMatch_0002 +CTCATCTCAAGATCTTTTGTATTCTTAATCTGAGCTTCTTGAATGACTCTATGTTGCTTCTGTTCTTCCTTAAGCTCTGCC +>chr1.1_035758205|RefMatch_0003 +CTCATCTCAAGATCTTTTGTATTCTTAATCTGAGCTTCTTGAATGACTCTTTGTTGCTTCTGTTCTTCCTTAAGCTCTGCC +>chr1.1_035758205|Ref_0001 +CTCATCTCAAGATCTTTTGTATTCTTAATCTGAGCTTCTTGAATGACTCTCTGTTGCTTCTGTTCTTCCTTAAGCTCTGCC +>chr1.1_035847212|Alt_0002 +TACATGCACGGGAATCAGATGAACAACTTTTCAGAAGATTCATACAGTCAACTCAATTTCATAAAAAGGATATGAAGAAAA +>chr1.1_035847212|RefMatch_0001 +TACATGCACGGGAATCAGATGAACAACTTTCCAGAAGATTCATACAGTCGACTCAATTTCATAAAAAGGATATGAAGAAAA +>chr1.1_035847212|Ref_0001 +TACATGCACGGGAATCAGATGAACAACTTTTCAGAAGATTCATACAGTCGACTCAATTTCATAAAAAGGATATGAAGAAAA +>chr1.1_036130046|Alt_0002 +GAAGTTTTAATTTCATTTGAGTTTATAGAATCTTCAAGAGGGTCTCTTTGCCTTTACATATGTTGTGAATATTCCTGTATT +>chr1.1_036130046|Ref_0001 +GAAGTTTTAATTTCATTTGAGTTTATAGAATCTTCGAGAGGGTCTCTTTGCCTTTACATATGTTGTGAATATTCCTGTATT +>chr1.1_036517797|Alt_0002 +GGACCGCCGTCCTAAATAATATTAATATGATATCATCTTAAGCATATCGGTCCTAGTTTTCCATTTGTTTTGACAATAACC +>chr1.1_036517797|Ref_0001 +GGACCGCCGTCCTAAATAATATTAATATGATATCATCTTAAGCATATGGGTCCTAGTTTTCCATTTGTTTTGACAATAACC \ No newline at end of file diff --git a/inst/imputation_ignore.txt b/inst/imputation_ignore.txt new file mode 100644 index 0000000..907502d --- /dev/null +++ b/inst/imputation_ignore.txt @@ -0,0 +1,4 @@ +SNP_ID +SNP1 +SNP3 +SNP14 diff --git a/inst/imputation_reference.txt b/inst/imputation_reference.txt new file mode 100644 index 0000000..13875f1 --- /dev/null +++ b/inst/imputation_reference.txt @@ -0,0 +1,21 @@ +ID SNP1 SNP2 SNP3 SNP4 SNP5 SNP6 SNP7 SNP8 SNP9 SNP10 SNP11 SNP12 SNP13 SNP14 SNP15 SNP16 SNP17 SNP18 SNP19 SNP20 SNP21 SNP22 SNP23 SNP24 SNP25 SNP26 SNP27 SNP28 SNP29 SNP30 +ID1 5 1 0 1 1 0 5 1 5 0 0 0 0 5 5 1 0 0 2 0 0 0 0 1 2 0 0 2 0 0 +ID2 1 2 5 2 0 2 5 0 0 1 2 1 5 5 2 0 2 0 0 2 0 5 1 1 2 2 2 5 1 0 +ID3 2 2 1 1 0 1 1 5 0 2 0 2 1 1 0 1 1 0 0 5 2 1 5 2 0 5 2 0 1 0 +ID4 5 0 0 5 5 0 1 0 0 5 0 5 1 0 2 0 1 5 0 5 0 0 2 0 1 5 0 2 5 1 +ID5 5 0 2 2 5 0 0 2 1 2 2 2 5 1 5 2 2 2 1 5 5 1 1 1 5 2 1 1 0 0 +ID6 5 5 1 5 5 5 2 1 0 0 5 0 2 2 1 1 0 2 2 1 1 1 5 5 1 0 0 5 1 0 +ID7 2 0 5 2 1 1 0 1 1 0 5 1 5 0 0 1 1 2 0 5 1 0 1 2 5 0 2 1 0 5 +ID8 1 2 0 2 5 2 5 5 0 2 0 2 0 5 1 2 2 5 5 0 0 1 1 0 0 5 2 0 0 2 +ID9 1 5 5 1 2 5 0 1 1 0 2 2 1 2 2 1 1 2 5 5 5 5 0 2 5 1 1 5 5 5 +ID10 2 1 2 0 1 0 1 2 1 2 2 0 5 1 1 1 1 5 5 1 5 1 0 2 5 2 1 1 1 0 +ID11 1 1 0 0 2 0 0 2 5 5 0 5 0 5 5 0 1 5 1 5 2 1 5 2 1 0 1 2 2 0 +ID12 5 0 1 1 2 1 2 5 2 1 2 5 0 5 2 1 5 5 5 1 0 5 0 0 1 2 2 5 5 1 +ID13 1 5 0 5 5 2 1 5 0 1 2 2 0 5 2 0 0 1 2 5 5 5 2 0 0 2 0 1 2 2 +ID14 5 0 0 1 0 5 1 0 0 1 1 2 1 5 2 5 2 1 5 0 0 0 1 0 2 0 5 0 5 0 +ID15 5 1 0 1 1 0 5 0 0 1 0 0 1 5 1 1 5 1 2 5 5 0 2 5 0 0 5 1 2 5 +ID16 0 1 5 1 2 2 0 5 1 1 5 1 0 0 2 2 5 1 1 1 2 0 2 2 5 2 5 0 5 2 +ID17 1 1 0 1 0 2 2 5 5 2 1 5 1 1 5 1 0 5 2 0 0 1 0 0 0 1 5 1 1 5 +ID18 1 1 2 2 2 2 0 5 5 1 0 0 2 0 1 0 5 2 2 2 2 0 5 5 2 5 5 0 5 1 +ID19 1 5 5 2 5 0 2 5 5 1 2 5 1 1 0 1 0 1 5 5 2 2 1 5 5 5 1 0 5 2 +ID20 2 5 1 1 2 5 2 1 0 0 0 1 5 5 2 1 2 5 2 5 1 5 5 0 5 0 5 5 1 1 \ No newline at end of file diff --git a/inst/imputation_test.txt b/inst/imputation_test.txt new file mode 100644 index 0000000..b137d31 --- /dev/null +++ b/inst/imputation_test.txt @@ -0,0 +1,29 @@ +ID SNP1 SNP2 SNP3 SNP4 SNP5 SNP6 SNP7 SNP8 SNP9 SNP10 SNP11 SNP12 SNP13 SNP14 SNP15 SNP16 SNP17 SNP18 SNP19 SNP20 SNP21 SNP22 SNP23 SNP24 SNP25 SNP26 SNP27 SNP28 SNP29 SNP30 SNP32 NSP42 +ID1 5 1 0 1 2 2 2 1 5 0 0 0 0 5 5 1 0 0 2 0 0 0 0 1 2 0 0 2 0 0 1 2 +ID2 1 2 5 2 0 2 5 1 0 5 2 1 5 5 2 0 2 0 0 2 0 5 1 1 2 2 2 5 1 0 5 5 +ID3 2 2 1 1 0 1 1 5 0 2 0 2 1 1 0 1 1 0 0 5 2 1 5 2 0 5 2 0 1 0 5 1 +ID4 5 0 0 5 5 0 1 0 0 5 0 5 1 0 2 0 1 5 0 5 0 0 2 0 1 5 0 2 5 1 5 0 +ID5 5 0 2 2 5 0 0 2 1 2 2 2 5 1 5 2 2 2 1 5 5 1 1 1 5 2 1 1 0 0 0 0 +ID6 5 5 1 5 5 5 2 1 0 2 2 2 2 2 2 2 2 2 2 1 1 1 5 5 1 0 0 5 1 0 5 5 +ID7 2 0 5 2 1 1 0 1 1 0 5 1 2 5 1 2 1 1 1 1 1 0 1 2 5 0 2 1 0 5 0 2 +ID8 1 2 0 2 5 2 5 5 0 2 0 2 0 5 1 2 2 5 5 0 0 1 1 0 0 5 2 0 0 2 5 5 +ID9 1 5 5 1 2 5 0 1 1 0 2 2 1 2 2 1 1 2 5 5 5 5 0 2 5 1 1 5 5 5 1 1 +ID10 2 1 2 0 1 0 0 2 1 2 2 0 5 1 1 1 1 5 5 1 5 1 0 2 5 2 1 1 1 0 1 0 +ID11 1 1 0 0 2 0 0 2 5 2 2 2 2 5 5 0 1 5 1 5 2 1 5 2 1 0 1 2 2 0 0 5 +ID12 5 0 1 1 2 1 2 5 2 1 2 5 0 1 2 2 0 5 5 1 0 5 0 0 1 2 2 5 5 1 2 5 +ID13 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4 4 4 +Test147 4 1 4 3 4 4 4 4 4 2 2 4 2 4 2 4 4 4 4 0 4 4 3 4 4 4 3 3 4 2 4 4 4 4 4 4 +Test148 4 2 4 3 4 4 4 4 4 3 3 4 3 4 3 4 4 4 4 2 4 4 3 4 4 4 4 4 4 2 4 4 4 4 4 4 +Test149 4 3 4 3 4 4 4 4 4 4 4 4 4 4 4 4 3 4 4 2 4 3 4 4 4 4 4 4 4 2 3 4 3 4 4 4 +Test150 4 2 4 3 4 4 4 4 4 4 3 4 4 4 3 4 3 4 4 1 4 3 4 4 4 4 4 4 4 3 3 4 4 4 4 4 +Test151 4 1 4 2 4 4 4 4 4 2 4 4 2 4 2 4 3 4 4 1 4 3 2 4 4 4 4 4 4 1 3 4 4 4 4 4 +Test152 4 2 4 3 4 4 4 4 4 2 4 4 2 4 2 4 4 4 4 0 4 4 0 4 4 4 4 4 4 0 4 4 3 4 4 4 +Test153 4 3 4 4 4 4 4 4 4 4 3 4 4 4 4 4 4 4 4 1 4 4 4 4 4 4 4 4 4 1 4 4 3 4 4 4 +Test154 4 1 4 3 4 4 4 4 4 2 3 4 2 4 2 4 4 4 4 0 4 4 2 4 4 4 4 3 4 0 4 4 3 4 4 4 +Test155 4 1 4 2 4 4 4 4 4 3 3 4 3 4 2 4 3 4 4 1 4 3 3 4 4 4 4 4 4 1 3 4 4 4 4 4 +Test156 4 1 4 3 4 4 4 4 4 2 3 4 2 4 1 4 4 4 4 1 4 4 3 4 4 4 4 4 4 2 4 4 4 4 4 4 +Test157 4 3 4 4 4 4 4 4 4 3 4 4 3 4 3 4 4 4 4 2 4 4 3 4 4 4 4 4 4 1 4 4 3 4 4 4 +Test158 4 1 4 2 4 4 4 4 4 3 3 4 3 4 2 4 3 4 4 0 4 3 3 4 4 4 4 4 4 0 3 4 3 4 4 4 +Test159 4 3 4 3 4 4 4 4 4 3 4 4 3 4 2 4 4 4 4 2 4 4 3 4 4 4 4 4 4 2 4 4 3 4 4 4 +Test160 4 3 4 4 4 4 4 4 4 3 4 4 3 4 2 4 4 4 4 2 4 4 3 4 4 4 4 4 4 1 4 4 3 4 4 4 +Test161 4 1 4 3 4 4 4 4 4 3 3 4 3 4 4 4 3 4 4 1 4 3 3 4 4 4 4 4 4 1 3 4 4 4 4 4 +Test162 4 2 4 4 4 4 4 4 4 3 3 4 3 4 3 4 4 4 4 1 4 4 3 4 4 4 4 4 4 1 4 4 3 4 4 4 +Test163 4 2 4 4 4 4 4 4 4 3 3 4 3 4 3 4 4 4 4 1 4 4 3 4 4 4 4 4 4 1 4 4 3 4 4 4 +Test164 4 3 4 3 4 4 4 4 4 4 4 4 4 4 4 4 3 4 4 1 4 3 4 4 4 4 4 4 4 1 4 4 3 4 4 4 +Test165 4 2 4 3 4 4 4 4 4 3 4 4 3 4 4 4 3 4 4 1 4 3 3 4 4 4 4 4 4 1 3 4 3 4 4 4 +Test166 4 1 4 3 4 4 4 4 4 2 3 4 2 4 2 4 4 4 4 0 4 4 2 4 4 4 4 3 4 0 4 4 3 4 4 4 +Test167 4 1 4 3 4 4 4 4 4 2 3 4 2 4 2 4 4 4 4 0 4 4 2 4 4 4 4 4 4 0 4 4 3 4 4 4 +Test168 4 1 4 3 4 4 4 4 4 2 3 4 2 4 2 4 4 4 4 0 4 4 2 4 4 4 3 3 4 0 4 4 3 4 4 4 +Test169 4 2 4 3 4 4 4 4 4 3 4 4 3 4 3 4 3 4 4 1 4 3 3 4 4 4 4 4 4 1 3 4 3 4 4 4 +Test170 4 1 4 2 4 4 4 4 4 3 3 4 3 4 2 4 3 4 4 0 4 3 3 4 4 4 4 4 4 0 3 4 3 4 4 4 +Test171 4 1 4 3 4 4 4 4 4 2 3 4 2 4 1 4 4 4 4 1 4 4 3 4 4 4 4 4 4 1 4 4 4 4 4 4 +Test172 4 3 4 4 4 4 4 4 4 3 4 4 3 4 3 4 4 4 4 2 4 4 3 4 4 4 4 4 4 1 4 4 3 4 4 4 +Test173 4 2 4 3 4 4 4 4 4 3 4 4 3 4 3 4 3 4 4 0 4 3 2 4 4 4 4 4 4 1 4 4 2 4 4 4 +Test174 4 3 4 4 4 4 4 4 4 3 4 4 3 4 3 4 4 4 4 1 4 4 2 4 4 4 4 4 4 1 4 4 2 4 4 4 +Test175 4 1 4 2 4 4 4 4 4 3 3 4 3 4 3 4 3 4 4 1 4 3 3 4 4 4 4 4 4 2 3 4 4 4 4 4 \ No newline at end of file diff --git a/man/add_ref_alt.Rd b/man/add_ref_alt.Rd deleted file mode 100644 index c8a8fe6..0000000 --- a/man/add_ref_alt.Rd +++ /dev/null @@ -1,18 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_OffTargets.R -\name{add_ref_alt} -\alias{add_ref_alt} -\title{Check if Ref_0001 and Alt_0002 tags are present, if not, add them from the hap_seq input. Function made for parallelization.} -\usage{ -add_ref_alt(one_tag, hap_seq, nsamples) -} -\arguments{ -\item{one_tag}{madc file split by tag} - -\item{hap_seq}{haplotype DB} - -\item{nsamples}{number of samples} -} -\description{ -Check if Ref_0001 and Alt_0002 tags are present, if not, add them from the hap_seq input. Function made for parallelization. -} diff --git a/man/allele_freq_poly.Rd b/man/allele_freq_poly.Rd new file mode 100644 index 0000000..6db4ee6 --- /dev/null +++ b/man/allele_freq_poly.Rd @@ -0,0 +1,49 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/breedtools_functions.R +\name{allele_freq_poly} +\alias{allele_freq_poly} +\title{Computes allele frequencies for specified populations given SNP array data} +\usage{ +allele_freq_poly(geno, populations, ploidy = 2) +} +\arguments{ +\item{geno}{matrix of genotypes coded as the dosage of allele B \code{{0, 1, 2, ..., ploidy}} +with individuals in rows (named) and SNPs in columns (named)} + +\item{populations}{list of named populations. Each population has a vector of IDs +that belong to the population. Allele frequencies will be derived from all animals} + +\item{ploidy}{integer indicating the ploidy level (default is 2 for diploid)} +} +\value{ +data.frame consisting of allele_frequencies for populations (columns) for +each SNP (rows) +} +\description{ +Computes allele frequencies for specified populations given SNP array data +} +\examples{ +# Example inputs +geno_matrix <- matrix( +c(4, 1, 4, 0, # S1 + 2, 2, 1, 3, # S2 + 0, 4, 0, 4, # S3 + 3, 3, 2, 2, # S4 + 1, 4, 2, 3),# S5 +nrow = 4, ncol = 5, byrow = FALSE, # individuals=rows, SNPs=cols +dimnames = list(paste0("Ind", 1:4), paste0("S", 1:5)) +) + +pop_list <- list( +PopA = c("Ind1", "Ind2"), +PopB = c("Ind3", "Ind4") +) + +allele_freqs <- allele_freq_poly(geno = geno_matrix, populations = pop_list, ploidy = 4) +print(allele_freqs) + +} +\references{ +Funkhouser SA, Bates RO, Ernst CW, Newcom D, Steibel JP. Estimation of genome-wide and locus-specific +breed composition in pigs. Transl Anim Sci. 2017 Feb 1;1(1):36-44. +} diff --git a/man/check_ped.Rd b/man/check_ped.Rd index 119c977..e86ab0a 100644 --- a/man/check_ped.Rd +++ b/man/check_ped.Rd @@ -4,11 +4,13 @@ \alias{check_ped} \title{Evaluate Pedigree File for Accuracy} \usage{ -check_ped(ped.file) +check_ped(ped.file, return.output = FALSE) } \arguments{ \item{ped.file}{path to pedigree text file. The pedigree file is a 3-column pedigree tab separated file with columns labeled as id sire dam in any order} + +\item{return.output}{logical. If TRUE, the function will return a list of dataframes with the error types found.} } \value{ A list of dataframes of error types, and the output printed to the console diff --git a/man/compare.Rd b/man/compare.Rd deleted file mode 100644 index 929ada4..0000000 --- a/man/compare.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_OffTargets.R -\name{compare} -\alias{compare} -\title{Get SNP positions, reference and alternative alleles based on the reference -Align alternatives to reference and discard low score alignment tags -Discard tags if alternative in the target locus is N -Do the complement reverse if cloneID present in the botloci vector} -\usage{ -compare(one_tag, botloci) -} -\arguments{ -\item{one_tag}{madc file split by tag} - -\item{botloci}{file containing the target IDs that were designed in the bottom strand} -} -\description{ -Get SNP positions, reference and alternative alleles based on the reference -Align alternatives to reference and discard low score alignment tags -Discard tags if alternative in the target locus is N -Do the complement reverse if cloneID present in the botloci vector -} diff --git a/man/create_VCF_body.Rd b/man/create_VCF_body.Rd deleted file mode 100644 index f00315a..0000000 --- a/man/create_VCF_body.Rd +++ /dev/null @@ -1,31 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_OffTargets.R -\name{create_VCF_body} -\alias{create_VCF_body} -\title{Creates VCF body from CSV generated by loop_though_dartag_report} -\usage{ -create_VCF_body( - csv, - rm_multiallelic_SNP = TRUE, - multiallelic_SNP_dp_thr = 2, - multiallelic_SNP_sample_thr = 10, - n.cores = 1, - verbose = TRUE -) -} -\arguments{ -\item{csv}{CSV file generated by loop_though_dartag_report} - -\item{rm_multiallelic_SNP}{logical. If TRUE, SNP with more than one alternative base will be removed. If FALSE, check \code{multiallelic_SNP_dp_thr} specs} - -\item{multiallelic_SNP_dp_thr}{numerical. If \code{rm_multiallelic_SNP} is FALSE, set a minimum depth by tag threshold \code{multiallelic_SNP_dp_thr} combined with minimum number of samples \code{multiallelic_SNP_sample_thr} to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites.} - -\item{multiallelic_SNP_sample_thr}{numerical. If \code{rm_multiallelic_SNP} is FALSE, set a minimum depth by tag threshold \code{multiallelic_SNP_dp_thr} combined with minimum number of samples \code{multiallelic_SNP_sample_thr} to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites.} - -\item{n.cores}{number of cores to be used in the parallelization} - -\item{verbose}{print metrics on the console} -} -\description{ -Creates VCF body from CSV generated by loop_though_dartag_report -} diff --git a/man/get_OffTargets.Rd b/man/get_OffTargets.Rd index 4b59548..96a071c 100644 --- a/man/get_OffTargets.Rd +++ b/man/get_OffTargets.Rd @@ -27,9 +27,13 @@ get_OffTargets( \item{rm_multiallelic_SNP}{logical. If TRUE, SNP with more than one alternative base will be removed. If FALSE, check \code{multiallelic_SNP_dp_thr} specs} -\item{multiallelic_SNP_dp_thr}{nnumerical. If \code{rm_multiallelic_SNP} is FALSE, set a minimum depth by tag threshold \code{multiallelic_SNP_dp_thr} combined with minimum number of samples \code{multiallelic_SNP_sample_thr} to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites.} +\item{multiallelic_SNP_dp_thr}{nnumerical. If \code{rm_multiallelic_SNP} is FALSE, set a minimum depth by tag threshold \code{multiallelic_SNP_dp_thr} combined +with minimum number of samples \code{multiallelic_SNP_sample_thr} to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic +aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites.} -\item{multiallelic_SNP_sample_thr}{numerical. If \code{rm_multiallelic_SNP} is FALSE, set a minimum depth by tag threshold combined with minimum number of samples \code{multiallelic_SNP_sample_thr} to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites.} +\item{multiallelic_SNP_sample_thr}{numerical. If \code{rm_multiallelic_SNP} is FALSE, set a minimum depth by tag threshold combined with minimum number of +samples \code{multiallelic_SNP_sample_thr} to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, +the marker is discarded. This is likely to happen to paralogous sites.} \item{out_vcf}{output VCF file name} diff --git a/man/get_ref_alt_hap_seq.Rd b/man/get_ref_alt_hap_seq.Rd deleted file mode 100644 index 3045797..0000000 --- a/man/get_ref_alt_hap_seq.Rd +++ /dev/null @@ -1,16 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_OffTargets.R -\name{get_ref_alt_hap_seq} -\alias{get_ref_alt_hap_seq} -\title{Converts the fasta to a data.frame with first column the AlleleID and and second the AlleleSequence -The function will work even if the sequence is split in multiple lines} -\usage{ -get_ref_alt_hap_seq(hap_seq) -} -\arguments{ -\item{hap_seq}{haplotype db} -} -\description{ -Converts the fasta to a data.frame with first column the AlleleID and and second the AlleleSequence -The function will work even if the sequence is split in multiple lines -} diff --git a/man/imputation_concordance.Rd b/man/imputation_concordance.Rd index 310a7ec..5cfb782 100644 --- a/man/imputation_concordance.Rd +++ b/man/imputation_concordance.Rd @@ -9,7 +9,8 @@ imputation_concordance( imputed_genos, missing_code = NULL, snps_2_exclude = NULL, - output = "imputation_concordance" + output = "imputation_concordance", + verbose = FALSE ) } \arguments{ @@ -22,6 +23,8 @@ imputation_concordance( \item{snps_2_exclude}{Optional input to exclude specific markers from concordance calculation. Single column of marker ids.} \item{output}{Optional input to assign the output dataframe to a specific variable name. Default is "imputation_concordance"} + +\item{verbose}{Optional input to print the concordance summary.} } \value{ 2 outputs: 1) A data frame with sample IDs and concordance percentages. 2) A summary of concordance percentages. diff --git a/man/loop_though_dartag_report.Rd b/man/loop_though_dartag_report.Rd deleted file mode 100644 index ed7db3d..0000000 --- a/man/loop_though_dartag_report.Rd +++ /dev/null @@ -1,28 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_OffTargets.R -\name{loop_though_dartag_report} -\alias{loop_though_dartag_report} -\title{Include SNP_position_in_Genome, Ref, and Alt information} -\usage{ -loop_though_dartag_report( - report, - botloci, - hap_seq, - n.cores = 1, - verbose = TRUE -) -} -\arguments{ -\item{report}{MADC file} - -\item{botloci}{file containing the target IDs that were designed in the bottom strand} - -\item{hap_seq}{haplotype DB fasta file} - -\item{n.cores}{number of cores to be used in the parallelization} - -\item{verbose}{print metrics on the console} -} -\description{ -Include SNP_position_in_Genome, Ref, and Alt information -} diff --git a/man/merge_MADCs.Rd b/man/merge_MADCs.Rd index cee847e..d88e045 100644 --- a/man/merge_MADCs.Rd +++ b/man/merge_MADCs.Rd @@ -24,3 +24,41 @@ they are used as suffix, if not, files will be identified from 1 to number of files, considering the order that was defined in the function. } +\examples{ +# First generating example MADC files +temp_dir <- tempdir() +file1_path <- file.path(temp_dir, "madc1.csv") +file2_path <- file.path(temp_dir, "madc2.csv") +out_path <- file.path(temp_dir, "merged_madc.csv") + +# Data for file 1: Has SampleA and SampleB +df1 <- data.frame( + AlleleID = c("chr1.1_0001|Alt_0002", "chr1.1_0001|Ref_0001", "chr1.1_0001|AltMatch_0001"), + CloneID = c("chr1.1_0001", "chr1.1_0001", "chr1.1_0001"), + AlleleSequence = c("GGG", "AAA", "TTT"), + SampleA = c(10, 8, 0), + SampleB = c(5, 4, 9), + stringsAsFactors = FALSE, + check.names = FALSE +) +write.csv(df1, file1_path, row.names = FALSE, quote = FALSE) + +# Data for file 2: Has SampleA (duplicate name) and SampleC, different rows +df2 <- data.frame( + AlleleID = c("chr1.1_0001|Alt_0002", "chr1.1_0001|Ref_0001", "chr1.1_0001|AltMatch_0001"), + CloneID = c("chr1.1_0001", "chr1.1_0001", "chr1.1_0001"), + AlleleSequence = c("GGG", "AAA", "TTT"), + SampleA = c(11, 7, 20), + SampleC = c(1, 2, 6), + stringsAsFactors = FALSE, + check.names = FALSE +) +write.csv(df2, file2_path, row.names = FALSE, quote = FALSE) + +# 2. Run the merge function +# Use default suffixes (.x, .y) for the duplicated "SampleA" +merge_MADCs(madc_list = list(file1_path, file2_path), + out_madc = out_path) + + +} diff --git a/man/merge_counts.Rd b/man/merge_counts.Rd deleted file mode 100644 index 3b27281..0000000 --- a/man/merge_counts.Rd +++ /dev/null @@ -1,25 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/get_OffTargets.R -\name{merge_counts} -\alias{merge_counts} -\title{Function made for parallelization of create_VCF_body function} -\usage{ -merge_counts( - cloneID_unit, - rm_multiallelic_SNP = FALSE, - multiallelic_SNP_dp_thr = 0, - multiallelic_SNP_sample_thr = 0 -) -} -\arguments{ -\item{cloneID_unit}{one item of csv file split by cloneID} - -\item{rm_multiallelic_SNP}{logical. If TRUE, SNP with more than one alternative base will be removed. If FALSE, check \code{multiallelic_SNP_dp_thr} specs} - -\item{multiallelic_SNP_dp_thr}{numerical. If \code{rm_multiallelic_SNP} is FALSE, set a minimum depth by tag threshold combined with minimum number of samples \code{multiallelic_SNP_sample_thr} to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites.} - -\item{multiallelic_SNP_sample_thr}{numerical. If \code{rm_multiallelic_SNP} is FALSE, set a minimum depth by tag threshold \code{multiallelic_SNP_dp_thr} combined with minimum number of samples \code{multiallelic_SNP_sample_thr} to eliminate low frequency SNP allele. If the threshold does not eliminate the multiallelic aspect of the marker, the marker is discarded. This is likely to happen to paralogous sites.} -} -\description{ -Function made for parallelization of create_VCF_body function -} diff --git a/man/solve_composition_poly.Rd b/man/solve_composition_poly.Rd new file mode 100644 index 0000000..d95645f --- /dev/null +++ b/man/solve_composition_poly.Rd @@ -0,0 +1,82 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/breedtools_functions.R +\name{solve_composition_poly} +\alias{solve_composition_poly} +\title{Compute genome-wide breed composition} +\usage{ +solve_composition_poly( + Y, + X, + ped = NULL, + groups = NULL, + mia = FALSE, + sire = FALSE, + dam = FALSE, + ploidy = 2 +) +} +\arguments{ +\item{Y}{numeric matrix of genotypes (columns) from all animals (rows) in population +coded as dosage of allele B \code{{0, 1, 2, ..., ploidy}}} + +\item{X}{numeric matrix of allele frequencies (rows) from each reference panel (columns). Frequencies are +relative to allele B.} + +\item{ped}{data.frame giving pedigree information. Must be formatted "ID", "Sire", "Dam"} + +\item{groups}{list of IDs categorized by breed/population. If specified, output will be a list +of results categorized by breed/population.} + +\item{mia}{logical. Only applies if ped argument is supplied. If true, returns a data.frame +containing the inferred maternally inherited allele for each locus for each animal instead +of breed composition results.} + +\item{sire}{logical. Only applies if ped argument is supplied. If true, returns a data.frame +containing sire genotypes for each locus for each animal instead of breed composition results.} + +\item{dam}{logical. Only applies if ped argument is supplied. If true, returns a data.frame +containing dam genotypes for each locus for each animal instead of breed composition results.} + +\item{ploidy}{integer. The ploidy level of the species (e.g., 2 for diploid, 3 for triploid, etc.).} +} +\value{ +A data.frame or list of data.frames (if groups is !NULL) with breed/ancestry composition +results +} +\description{ +Computes genome-wide breed/ancestry composition using quadratic programming on a +batch of animals. +} +\examples{ +# Example inputs for solve_composition_poly (ploidy = 4) + +# (This would typically be the output from allele_freq_poly) +allele_freqs_matrix <- matrix( + c(0.625, 0.500, + 0.500, 0.500, + 0.500, 0.500, + 0.750, 0.500, + 0.625, 0.625), + nrow = 5, ncol = 2, byrow = TRUE, + dimnames = list(paste0("SNP", 1:5), c("VarA", "VarB")) +) + +# Validation Genotypes (individuals x SNPs) +val_geno_matrix <- matrix( + c(2, 1, 2, 3, 4, # Test1 dosages for SNP1-5 + 3, 4, 2, 3, 0), # Test2 dosages for SNP1-5 + nrow = 2, ncol = 5, byrow = TRUE, + dimnames = list(paste0("Test", 1:2), paste0("SNP", 1:5)) +) + +# Calculate Breed Composition +composition <- solve_composition_poly(Y = val_geno_matrix, + X = allele_freqs_matrix, + ploidy = 4) +print(composition) + +} +\references{ +Funkhouser SA, Bates RO, Ernst CW, Newcom D, Steibel JP. Estimation of genome-wide and locus-specific +breed composition in pigs. Transl Anim Sci. 2017 Feb 1;1(1):36-44. +} diff --git a/tests/testthat/iris_updog.RData b/tests/testthat/iris_updog.RData new file mode 100644 index 0000000..1d7024a Binary files /dev/null and b/tests/testthat/iris_updog.RData differ diff --git a/tests/testthat/test-breedtools_poly.R b/tests/testthat/test-breedtools_poly.R new file mode 100644 index 0000000..91ed356 --- /dev/null +++ b/tests/testthat/test-breedtools_poly.R @@ -0,0 +1,31 @@ +context("BreedTools") + + +test_that("test breedtools poly",{ + #Input variables + ref_file <- system.file("test_ref.txt", package="BIGr") + val_file <- system.file("test_test.txt", package="BIGr") + ref_ids <- system.file("ref_ids.txt", package="BIGr") + + #import files + reference = read.table(ref_file, header = T, row.names = 1, sep = "\t") + validation = read.table(val_file, header = T, row.names = 1, sep = "\t") + reference_ids = read.table(ref_ids, header = T, sep = "\t") + + #Calculations + ref_ids = lapply(as.list(reference_ids),as.character) + + freq = allele_freq_poly(reference, ref_ids, ploidy = 4) + + prediction = as.data.frame(solve_composition_poly(validation,freq, ploidy = 4)) + + #Check + freq_mean <- round(mean(as.numeric(freq)),6) + pred_mean <- round(mean(as.numeric(prediction$R2)),6) + + + expect_equal(freq_mean, 0.888889, tolerance = 0.01) + expect_equal(pred_mean, 0.841454, tolerance = 0.01) + expect_true(nrow(prediction) == 175) + +}) diff --git a/tests/testthat/test-check_ped.R b/tests/testthat/test-check_ped.R new file mode 100644 index 0000000..f0fac82 --- /dev/null +++ b/tests/testthat/test-check_ped.R @@ -0,0 +1,20 @@ +context("Imputation Concordance") + + +test_that("test imputation",{ + #Input variables + ped_file <- system.file("check_ped_test.txt", package="BIGr") + + #Calculations + output.list <- check_ped(ped_file, TRUE) + + #Check + df_length <- length(output.list) + messy_parents <- output.list$messy_parents + missing_parents <- output.list$missing_parents + + expect_true(df_length == 2) + expect_true(all(messy_parents$id == c("grandfather2","grandfather3"))) + expect_true(nrow(missing_parents) == 13) + +}) diff --git a/tests/testthat/test-get_OffTargets.R b/tests/testthat/test-get_OffTargets.R new file mode 100644 index 0000000..002d11d --- /dev/null +++ b/tests/testthat/test-get_OffTargets.R @@ -0,0 +1,46 @@ +context("Get OffTargets") + + +test_that("test madc offtargets",{ + #Input variables + madc_file <- system.file("example_MADC_FixedAlleleID.csv", package="BIGr") + bot_file <- system.file("example_SNPs_DArTag-probe-design_f180bp.botloci", package="BIGr") + db_file <- system.file("example_allele_db.fa", package="BIGr") + + #Calculations + temp <- tempfile(fileext = ".vcf") + temp_multi <- tempfile(fileext = ".vcf") + + set.seed(123) + get_OffTargets(madc = madc_file, + botloci = bot_file, + hap_seq = db_file, + n.cores = 2, + rm_multiallelic_SNP = FALSE, + multiallelic_SNP_dp_thr = 0, + multiallelic_SNP_sample_thr = 0, + out_vcf = temp, + verbose = FALSE) + + set.seed(456) + get_OffTargets(madc = madc_file, + botloci = bot_file, + hap_seq = db_file, + n.cores = 2, + rm_multiallelic_SNP = TRUE, + multiallelic_SNP_dp_thr = 0, + multiallelic_SNP_sample_thr = 0, + out_vcf = temp_multi, + verbose = FALSE) + + vcf <- read.vcfR(temp) + vcf_multi <- read.vcfR(temp_multi) + + #Check + expect_true(all(dim(vcf@gt) == c("33","11"))) + expect_true(all(dim(vcf_multi@gt) == c("32","11"))) + + rm(vcf) + rm(vcf_multi) + +}) diff --git a/tests/testthat/test-imputation_concordance.R b/tests/testthat/test-imputation_concordance.R new file mode 100644 index 0000000..73eb089 --- /dev/null +++ b/tests/testthat/test-imputation_concordance.R @@ -0,0 +1,24 @@ +context("Imputation Concordance") + + +test_that("test imputation",{ + #Input variables + ignore_file <- system.file("imputation_ignore.txt", package="BIGr") + ref_file <- system.file("imputation_reference.txt", package="BIGr") + test_file <- system.file("imputation_test.txt", package="BIGr") + + #import files + snps = read.table(ignore_file, header = TRUE) + ref = read.table(ref_file, header = TRUE) + test = read.table(test_file, header = TRUE) + + #Calculations + result <- imputation_concordance(ref, test,snps_2_exclude = snps, missing_code =5, output = NULL, verbose = FALSE) + + #Check + result2 <- sum(as.numeric(gsub("%","",result$Concordance))) + + expect_equal(result2, 1910.51, tolerance = 0.01) + expect_true(nrow(result) == nrow(ref)) + +}) diff --git a/tests/testthat/test-merge_MADCs.R b/tests/testthat/test-merge_MADCs.R new file mode 100644 index 0000000..f4f41b7 --- /dev/null +++ b/tests/testthat/test-merge_MADCs.R @@ -0,0 +1,35 @@ +context("Merge MADCs") + + +test_that("test merge madc",{ + #Input variables + madc_file <- system.file("example_MADC_FixedAlleleID.csv", package="BIGr") + madc2_file <- system.file("example_MADC_to_merge.csv", package="BIGr") + + #Calculations + temp <- tempfile(fileext = ".csv") + temp2 <- tempfile(fileext = ".csv") + + merge_MADCs(madc_list = list(madc_file,madc2_file), + out_madc=temp, run_ids=NULL) + + merge_MADCs(madc_list = list(madc_file,madc_file), out_madc=temp2, run_ids=NULL) + + merged_madc <- data.frame(read_csv(temp)) + merged_madc2 <- data.frame(read_csv(temp2)) + + #Check + count_sum <- sum(as.matrix(merged_madc[,-c(1,2,3)])) + df_dim <- dim(merged_madc) + + + expect_true(all(df_dim == c("61","23"))) + expect_true(count_sum == 86845) + expect_error(merge_MADCs(madc_list = NULL,out_madc=temp, run_ids=NULL)) + expect_error(merge_MADCs(madc_list = list(madc_file,madc2_file), out_madc=NULL, run_ids=NULL)) + expect_error(merge_MADCs(madc_list = list(madc_file,madc2_file), out_madc=temp, run_ids="one")) + expect_true(all(merged_madc2[,4:13] == merged_madc2[,14:23])) + + rm(count_sum,merged_madc,merged_madc2,df_dim) + +}) diff --git a/tests/testthat/test-updog2vcf.R b/tests/testthat/test-updog2vcf.R index cd25579..0faca49 100644 --- a/tests/testthat/test-updog2vcf.R +++ b/tests/testthat/test-updog2vcf.R @@ -3,10 +3,9 @@ context("Updog to VCF") test_that("test updog conversion",{ #Input variables - updog_file <- system.file("iris_updog_multidog.RData", package="BIGr") + load(testthat::test_path("iris_updog.RData")) temp_file <- tempfile() - load(updog_file) # Convert updog to VCF updog2vcf(