Tools for Analyzing QTL Experiments
Number of genotypes
Identify markers without any genotype data
Find an initial order for markers within chromosomes
Pull out the phenotypes names from a cross
Find column number for a particular phenotype
Determine the number of QTL in a QTL object
Introductory comments on R/qtl
Indicate marker covariates from composite interval mapping
Add significance threshold to plot
Add QTL x covariate interaction to a multiple-QTL model
Add pairwise interaction to a multiple-QTL model
Add phenotype location into a cross object
Add a marker to a cross
Scan for an additional pair of QTL in a multiple-QTL model
Scan for an additional QTL in a multiple-QTL model
Number of missing genotypes
Add to a qtl object
Test all possible splits of a chromosome into two pieces
Reconstruct underlying genotypes
Arithmetic operators for scanone and scantwo results
Arithmetic Operators for permutation results
Bayesian credible interval
Convert a cross to RIL by selfing
Combine data for QTL experiments
Combine columns from multiple scanone results
Combine data from scanone permutations
Combine columns from multiple scantwo results
Combine data from scantwo permutations
Convert a cross to RIL by sib mating
Identify likely genotyping errors
Calculate conditional genotype probabilities
Calculate LOD penalties
Combine columns from multiple scanone permutation results
Combine scantwo permutations by column
Change map function for a genetic map
Identify markers with switched alleles
Chromosome lengths in QTL experiment
Pull out the chromosome names from a cross
Composite interval mapping
Remove derived data
Clean up scantwo output
Convert output from scanone for R/qtl version 0.98
Plot estimated QTL effects across the whole genome
Estimate genetic maps
Delete genotypes that are possibly in error
Compare two cross objects
Compare individuals' genotype data
Compare two orderings of markers on a chromosome
Condense the output from a 2-d genome scan
Convert output from scantwo for R/qtl version 1.03 and earlier
Convert a sex-specific map to a sex-averaged one
Count number of obligate crossovers for each individual
Drop duplicate markers
Drop a set of markers
Drop markers without any genotype data
Drop a QTL from a qtl object
Drop one marker at a time and determine effect on genetic map
Plot phenotype means against genotypes at one or two markers
Estimate pairwise recombination fractions
Fill holes in genotype data
Find large intervals in a map
Find flanking markers for a specified position
Find marker closest to a specified position
Find position of a marker
Find the pseudomarker closest to a specified position
Find markers with identical genotype data
Determine the numeric index for a marker
Fit a multiple-QTL model
Fit Stahl interference model
Flip the orders of markers on a set of chromosomes
Partition markers into linkage groups
Jitter marker positions in a genetic map
Create matrix of marker covariates for QTL analysis
Create table of two-locus genotypes
Plot grid of genotype data
Create table of genotype distributions
Pull out the individual identifiers from a cross
Pull out the marker names from a cross
Retrieving groups of traits after clustering
Crude reconstruction of founder haplotypes in multi-parent RIL
Identify inferred partitions in mapping QTL to a phylogenetic tree
Interpolate positions from one map to another
Determine the number of phenotypes QTL experiment
Estimate locations of crossovers
LOD support interval
Make a qtl object
Convert genetic map from list to table.
General likelihood ratio test for association between marker pairs
Subsetting chromosomes for a genetic map
Maximum peak in genome scan
Maximum peak in genome scan to map a QTL to a phylogenetic tree
Maximum peak in two-dimensional genome scan
Move a marker to a new chromosome
Introduction to Multiple QTL Model (MQM) mapping
MQM augmentation
Transform a vector of quantitative values to the corresponding normal ...
Automatic setting of cofactors, taking marker density into account
MQM marker extraction
Fetch significant markers after permutation analysis
Retrieve the QTL model used in mapping from the results of an MQM scan
Estimate QTL LOD score significance using permutations or simulations
Plot LOD curves of a multiple-QTL model
Circular genome plot for MQM
cis-trans plot
Plot clustered heatmap of MQM scan on multiple phenotypes
Plot cofactors on the genetic map
Determine the number of individuals QTL experiment
Plot LOD*Effect curves of a multiple-QTL model
Heatmap of a genome of MQM scan on multiple phenotypes
Plot the results from a genomescan using a multiple-QTL model on multi...
Plot results from mqmpermutation
Determine the numbers of markers on each chromosome
Convert mqmmulti objects into a scanoneperm object
Genome scan with a multiple QTL model (MQM)
Parallelized MQM on multiple phenotypes in a cross object
Estimate FDR for multiple trait QTL analysis
Set cofactors at fixed intervals, to be used with MQM
Shapiro normality test used for MQM
Determine the number of chromosomes
Identify the largest subset of markers that are some distance apart
Plot genotype comparison
Plot various features of a cross object
Plot grid of error LOD values
Plot observed genotypes, flagging likely errors
Plot the proportion of missing genotype information
Plot genetic map
Plot grid of missing genotypes
Plot a phenotype distribution
Plot phenotypes versus marker genotypes
Plot QTL locations
Plot recombination fractions
Plot recombination fractions or LOD scores for a single marker
Plot LOD curves
Plot results of bootstrap for QTL position
Plot permutation results for a single-QTL genome scan
Plot LOD curves from single-QTL scan to map QTL to a phylogenetic tree
Plot LOD scores for a two-dimensional genome scan
Plot permutation results for a 2d, 2-QTL genome scan
Plot 1-d LOD profiles for a multiple QTL model
Plot a QTL model
Pull out the results of the Viterbi algorithm from a cross
Pull out the genotype imputations from a cross
Pull out the genotype data from a cross
Pull out the genotype probabilities from a cross
Pull out the genetic map from a cross
Drop all but a selected set of markers
Pull out phenotype data from a cross
Pull out recombination fractions or LOD scores from a cross object
Internal qtl functions
Installed version of R/qtl
Read data for a QTL experiment
Read data for 4- or 8-way RIL
Subsetting the results of a genome scan
Reduce to a grid of pseudomarkers.
Refine the positions of QTL
Reorder the QTL in a qtl object
Replace the genetic map of a cross
Replace the genetic map in QTL mapping results with an alternate map
Replace the genetic map in QTL mapping results with an alternate map
Replace a QTL in a qtl object with a different position
Rescale genetic maps
Compare marker orders
Genome scan with a single QTL model
Bootstrap to get interval estimate of QTL location
Permutation test for mean effect in scanonevar
Genome scan for QTL affecting mean and/or variance
Permutation test for variance effect in scanonevar
Single-QTL genome scan to map QTL to a phylogenetic tree
General QTL scan
Two-dimensional genome scan with a two-QTL model
Permutation test for 2d genome scan by Haley-Knott regression
Shift starting points in genetic maps
Simulate a QTL experiment
Simulate genotypes given observed marker data
Subsetting permutation test results
Simulate a genetic map
Simulate founder SNPs for a multiple-strain RIL
Simulate a set of intercrosses for a single diallelic QTL
Simulates missing genotype data
Stepwise selection for multiple QTL
Strip partially informative genotypes
Subsetting data for QTL experiment
Subsetting the results of a 2-d genome scan
Subsetting two-dimensional permutation test results
Print pairs of individuals with similar genotype data.
Print summary of QTL experiment
Summary of fit of qtl model
Print summary of a genetic map
Print summary of a QTL object
Print summary of ripple results
Summarize the results of a genome scans
Bootstrap confidence interval for QTL location
LOD thresholds from scanone permutation results
Summarize the results a genome scan to map a QTL to a phylogenetic tre...
Summarize the results of a two-dimensional genome scan
Summarize the results of a two-dimensional genome scan
LOD thresholds from scantwo permutation results
Switch the order of markers on a chromosome
Switch alleles at selected markers
Convert a table of marker positions to a map object.
List genotypes with large error LOD scores
Determine the total number of markers
Transformation of the phenotypes in a cross object
Test all possible positions for a marker
Maximum distance between genotyped markers
Write data for a QTL experiment to a file
Get x-axis locations in scanone plot
Analysis of experimental crosses to identify genes (called quantitative trait loci, QTLs) contributing to variation in quantitative traits. Broman et al. (2003) <doi:10.1093/bioinformatics/btg112>.