Data import

• read_cross2 - read data for a cross from a set of files
• fread_csv - read a csv file, using a particular set of options
• fread_csv_numer - like read_csv but assuming the contents are strictly numeric
• read_pheno - read phenotype data from a CSV file, plus (optionally) phenotype covariate data from a separate CSV file
• write_control_file - write the control file for a set of QTL data
• zip_datafiles - zip a set of data files (in the format read by read_cross2)

Data subsetting

• subset.cross2 - subset a cross2 object by individuals or chromosomes
• "[".cross2 - shorthand for subset.cross2, with the form mycross[ind, chr]
• subset.calc_genoprob subset genotype probabilties by indivduals or chromosomes
• "[".calc_genoprob - shorthand for subset.calc_genoprob, with the form probs[ind, chr]
• subset.scan1 - subset genome scan results by chromosome or column
• subset_scan1 - the same as subset.scan1
• subset.sim_geno - subset genotype imputations by individuals or chromosomes
• "[".sim_geno - shorthand for subset.sim_geno, with the form simg[ind, chr]
• subset.viterbi - subset inferred genotypes
• "[".viterbi - shorthand for subset.viterbi, with the form geno[ind, chr]
• drop_markers - drop a vector of markers from a "cross2" object
• drop_nullmarkers - drop markers with no genotypes from a "cross2" object
• pull_markers - drop all except a vector of markers from "cross2" object
• find_dup_markers - find sets of markers with identical genotype data

Combining data

• cbind_expand - Like cbind() but using row names to align the rows and expanding with missing values as necessary
• cbind.calc_genoprob - combine genotype probabilities for multiple chromosomes but on the same set of individuals
• rbind.calc_genoprob - combine genotype probabilities for different individuals
• cbind.scan1 - combine genome scan results for multiple phenotypes/analyses
• rbind.scan1 - combine genome scan results for different chromosomes
• c.scan1perm - combine genome scan permutation results for multiple replicates
• cbind.scan1perm - combine genome scan permutation results for multiple phenotypes/analyses
• rbind.scan1perm - combine genome scan permutation results for multiple chromosomes
• cbind.sim_geno - combine genotype imputations for multiple chromosomes but on the same set of individuals
• rbind.sim_geno - combine genotype imputations for different individuals
• cbind.viterbi - combine inferred genotypes for multiple chromosomes but on the same set of individuals
• rbind.viterbi - combine inferred genotypes for different individuals

Genotype reconstruction

• calc_genoprob - calculate conditional genotype probabilities given marker data
• clean_genoprob - clean up genotype probabilities, setting small values to 0
• genoprob_to_alleleprob - convert genotype probabilities to allele dosages
• genoprob_to_snpprob - convert genotype probabilities to SNP probabilities
• interp_genoprob - linear interpolation of genotype probabilities, for example to get two sets onto the same map for comparison purposes
• probs_to_grid - subset genotype probabilities to a grid of pseudomarkers
• pull_genoprobpos - pull out the genotype probabilities for a particular position
• pull_genoprobint - pull out the genotype probabilities for an interval

Genotype imputation

• maxmarg - for each individual at each position, find genotype with maximum marginal probability
• guess_phase - turn imputed genotypes into phased genotypes along chromosomes
• sim_geno - multiple imputations of underlying genotypes given marker data
• viterbi - find mostly likely sequence of true genotypes given marker data
• predict_snpgeno - predict SNP genotypes in a multiparent population from inferred genotypes plus founder strains’ SNP alleles.

Kinship matrix calculations

• calc_kinship - calculate genetic similarity among individuals
• decomp_kinship - calculate eigen decomposition of a kinship matrix
• scale_kinship - scale kinship matrix to be like a correlation matrix

Marker maps

• est_map - re-estimate the inter-marker distances in a genetic map
• insert_pseudomarkers - add pseudomarkers into a map of genetic markers
• calc_grid - Calculate indicators of which pseudomarker positions are along a fixed grid
• map_to_grid - subset a map object to the locations on some grid
• interp_map - Use interpolate to convert from one map to another
• reduce_markers - Reduce marker map to the largest subset that are some distance apart
• smooth_gmap - Smooth genetic map by mixing it with a bit of constant recombination
• unsmooth_gmap - Performs the reverse operation of smooth_gmap()

QTL analysis

• est_herit - estimate heritability with linear mixed model
• fit1 - fit a single-QTL model at a single position
• scan1 - genome scan with a single-QTL model
• scan1perm - permutation test to establish statistical significance in genome scan
• scan1coef - calculate QTL effects in scan along one chromosome
• scan1blup - like scan1coef, but calculating treating QTL effects as random and calculating BLUPs
• scan1snps - single-QTL scan over SNPs in a multi-parent population
• scan1max - genome-wide maximum LOD score from genome scan

QTL summaries

• maxlod - calculate genome-wide maximum LOD score in genome scan results
• max.scan1 - calculate maximum LOD score in genome scan and the position at which it occurred
• max_scan1 - the same as max.scan1
• find_peaks - find QTL peaks in genome scan results
• lod_int - calculate LOD support intervals from genome scan results
• bayes_int - calculate approximate Bayes intervals for QTL position from genome scan results
• summary.scan1perm - calculate significance thresholds from genome scan permutation results
• summary_scan1perm - same as summary.scan1perm
• top_snps - find the top SNPs from a SNP association scan

Data diagnostics

• check_cross2 - check for inconsistencies or errors in a "cross2" object
• calc_entropy - calculate entropy from genotype probabilities, for each individual and position
• calc_errorlod - calculate genotyping error LOD scores to help identify potential genotyping errors and problem markers or individuals
• calc_geno_freq - calculate genotype frequencies, by individual or marker, from genotype probabilities
• calc_het - Calculate heterozygosities, by individual or marker, from genotype probabilities
• chisq_colpairs - Perform chi-square test for independence for all pairs of columns of a matrix
• convert2cross2 - convert an R/qtl1 "cross" object to the R/qtl2 "cross2" format
• compare_geno - compare genotypes for all pairs of individuals, to look for possible sample duplicates
• compare_genoprob - compare two sets of genotype probabilities for one individual on a single chromosome
• summary.compare_geno - summarize the results of compare_geno
• summary_compare_geno - same as summary.compare_geno
• max.compare_geno - from the results of compare_geno, show the pair with most similar genotypes
• max_compare_geno - same as max.compare_geno
• count_xo - count the number of crossovers in each individual on each chromosome, from matrices of inferred genotypes
• locate_xo - locate the positions of crossovers in each individual on each chromosome, from matrices of inferred genotypes.
• find_ibd_segments - in genotypes of a set of inbred lines, find genomic segments that are identity-by-descent (IBD)
• compare_maps - compare two marker maps, to identify markers present in one but not the other, or on different chromosomes or in different orders between the maps.
• find_map_gaps - find large gaps between markers in a genetic map
• reduce_map_gaps - reduce the lengths of gaps in a genetic map
• calc_raw_het - Calculate heterozygosity in the raw SNP genotypes
• calc_raw_maf - Calculate the minor allele frequency in the raw SNP genotypes
• calc_raw_geno_freq - Calculate the genotype frequencies in the raw SNP data
• calc_raw_founder_maf - Calculate the minor allele frequency in the founder strains’ SNP genotypes

Data summaries

• summary.cross2 - summarize a "cross2" object
• chr_names - names of chromosomes in a "cross2" object
• marker_names - names of markers in a "cross2" object
• pheno_names - names of phenotypes in a "cross2" object
• phenocovar_names - names of “phenotype covariates” (metadata about phenotypes) in a "cross2" object
• covar_names - names of covariates in a "cross2" object
• ind_ids - return IDs for all individuals in a "cross2" object
• ind_ids_geno - return IDs for all individuals in a "cross2" object that have genotype data
• ind_ids_pheno - return IDs for all individuals in a "cross2" object that have phenotype data
• ind_ids_gnp - return IDs for all individuals in a "cross2" object that have both genotype and phenotype data
• ind_ids_covar - return IDs for all individuals in a "cross2" object that have covariate data
• n_chr - number of chromosomes in a "cross2" object
• n_ind - number of individuals in a "cross2" object
• n_ind_geno - number of individuals in a "cross2" object that have genotype data
• n_ind_pheno - number of individuals in a "cross2" object that have phenotype data
• n_ind_gnp - number of individuals in a "cross2" object that have both genotype and phenotype data
• n_ind_covar - number of individuals in a "cross2" object that have covariate data
• n_mar - number of markers on each chromosome in a "cross2" object
• tot_mar - total number of markers in a "cross2" object
• n_pheno - number of phenotypes in a "cross2" object
• n_covar - number of covariates in a "cross2" object
• n_phenocovar - number of “phenotype covariates” (metadata on phenotypes) in a "cross2" object
• chr_lengths - calculate chromosome lengths for a map object
• find_marker - find marker closest to a particular genomic position
• find_markerpos - find the position of a marker
• n_missing - number of missing genotypes, by individual or marker
• n_typed - number of genotypes, by individual or marker
• founders - names of the founder strains
• n_founders - number of founder strains

QTL plots

• plot.scan1 - plot genome scan results
• plot_scan1 - same as plot.scan1
• xpos_scan1 - determine the x-axis location of a particular genomic position in a genome scan plot (for adding annotations)
• add_threshold - Add horizontal line at a significance threshold to a genome scan plot.
• plot.scan1coef - plot QTL effects along a chromosome
• plot_coef - same as plot.scan1coef
• plot_coefCC - like plot_coef but assuming there are 8 effects and using the standard colors for the Collaborative Cross (CCcolors)
• plot_snpasso - plot SNP association results
• plot_genes - plot locations of a set of genes
• plot_sdp - plot strain distribution patterns of SNPs in a region
• plot_peaks - plot a summary of QTL positions for multiple phenotypes, using the results of find_peaks
• plot_lodpeaks - scatterplot of LOD scores vs QTL peak locatiosn (possibly with intervals) for multiple traits
• plot_pxg - plot phenotype versus QTL genotypes

Diagnostic plots

• plot.calc_genoprob - plot the genotype probabilities for one individual on one chromosome, as a heat map
• plot_genoprob - the same as plot.calc_genoprob
• plot_onegeno - plot one individual’s genome-wide genotypes
• plot_genoprobcomp - plot a comparison of two sets of genotype probabilities for one individual on one chromosome, as a bivariate heat map
• plot_compare_geno - Plot histogram of the results of compare_geno()
• plot.compare_geno - Same as plot_compare_geno()

SNP/gene databases

• create_variant_query_func - create a function to connect to a SQLite database of founder variant information and return a data frame with variants for a selected region
• create_gene_query_func - create a function to connect to a SQLite database of gene annotations and return a data frame with genes in a selected region
• calc_sdp - convert founder SNP genotypes to a numeric code for the strain distribution pattern
• invert_sdp - the inverse of calc_sdp
• index_snps - partition SNPs into groups that are contained within common marker intervals and have the same strain distribution pattern, and create an index to a set of distinct SNPs, one per partition
• find_index_snp - For a particular SNP, find the corresponding indexed SNP.
• create_snpinfo - Create a table of SNP information from a cross2 object.
• sdp2char - convert strain distribution pattern numeric codes to more meaningful character strings

Utility functions

• batch_cols - identify batches of columns of a matrix that have the same pattern of missing values
• batch_vec - split a vector into batches, for help in balancing parallel code
• get_common_ids - find IDs that are present in all of the input objects
• get_x_covar - from a "cross2" object, get the matrix of covariates to be used for the null hypothesis when performing QTL analysis on the X chromosome
• mat2strata - use the rows of a matrix to define a set of strata for a stratified permutation test
• replace_ids - Replace the individual IDs in an object
• replace_ids.calc_genoprob - Replace the individual IDs in a "calc_genoprob" object
• replace_ids.cross2 - Replace the individual IDs in a "cross2" object
• replace_ids.sim_geno - Replace the individual IDs in a "sim_geno" object
• replace_ids.viterbi - Replace the individual IDs in a "viterbi" object
• replace_ids.data.frame - Replace the individual IDs (in row names) in a data frame
• replace_ids.matrix - Replace the individual IDs (in row names) in a matrix
• align_scan1_map - aligns the markers/pseudomarkers in a "scan1" object (output by scan1()) and a marker map.
• clean - clean an object
• clean.scan1 - clean a "scan" object (replacing negative values with NA and removing rows were all values are NA.
• clean_scan1 - the same as clean.scan1.
• clean.calc_genoprob - clean a "calc_genoprob" object (setting small values to 0)
• clean_genoprob - same as clean.calc_genoprob
• qtl2version - print the installed version of R/qtl2
• recode_snps - Recode the SNP genotypes so that 1 is for the major allele in the founders

Boring print functions

• print.cross2 - print method for a "cross2" object
• print.summary.cross2 - print method for the output of summary.cross2
• print.summary.compare_geno - print method for the output of summary.compare_geno
• print.summary.scan1perm - print method for the output of summary.scan1perm

Newly added functions (in development version)