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
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
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 locations
(possibly with intervals) for multiple traits
plot_pxg - plot phenotype versus QTL genotypes
Diagnostic plots
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
convert2cross2 - convert an R/qtl1 "cross" object to the R/qtl2
"cross2" format
Boring print functions
Newly added functions (in development version)
compare_founder_geno - compare genotypes for all pairs of founders in a multi-parent population, to assess similarities