Genotyping and QTL Mapping in DO Mice


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Documentation for package ‘DOQTL’ version 1.2.0

Help Pages

add.missing.F1s Add Missing F1 Samples
add.slash Add a forward slash to a character string.
addLog Add two log values.
addLogVector Add a vector of log values.
assoc.map Perform association mapping on DO mice.
assoc.map.perms Perform association mapping on DO mice.
assoc.plot Plot association mapping results.
batch.normalize Batch normalize the X & Y intensity data.
bayesint FALSEind a Bayesian Credible Interval around a QTL.
calc.genoprob Calculate the founder genotype probabilities at each SNP.
calc.genoprob.alleles Calculate the founder genotype probabilities at each SNP using allele calls.
calc.genoprob.intensity Calculate the founder genotype probabilities at each SNP.
categorize.variants categorize.variants
cc.trans.probs Transition probabilities for CC mice.
chr.skeletons Plot the genome of a DO sample.
cluster.strains cluster.strains
coef.doqtl Return the coefficients of a DOQTL object.
coefplot Plot the QTL model coefficients
colSumsLog Sum columns of log transformed data.
condense.model.probs Condense 36 state genotypes down to founder genotypes.
convert.allele.calls Convert allele calls to numeric values.
convert.genes.to.GRanges Convert MGI genes to GRanges.
convert.genotypes Convert the genotype data from A,C,G,T format to A, H, B, N.
convert.variants.to.GRanges convert.variants.to.GRanges
convert.variants.to.numeric convert.variants.to.numeric
create.genotype.states Create genotype states.
create.html.page Create an HTML QTL report
create.Rdata.files Convert *.txt files to *.Rdata files.
do.colors do.colors
do.states do.states
do.trans.probs Determine DO transition probabilities
do2sanger Impute the Sanger SNPs onto DO genomes
do2sanger.helper Impute the Sanger SNPs onto DO genomes
estimate.cluster.params Estimate genotype cluster means and variances
example.genes example.genes
example.pheno Example phenotypes.
example.qtl Example QTL.
example.snps example.snps
extract.raw.data Extract intensities, genotypes and call rates from from raw MUGA or MegaMUGA data files
fast.qtlrel QTL mapping using QTLRel
fill.in.snps Interpolate between SNPs at the same cM value.
filter.geno.probs Remove SNPs where the genotype probabilities are too low for one founder state
filter.samples FALSEilter X, Y and genotype data by call rate
find.overlapping.genes find.overlapping.genes
founder.F1.intensity.plot Plot founders and F1 hybrids or genotype state means and variances on an intensity plot.
gene.plot gene.plot
generic.trans.probs Generic transition probabilities
genomic.points Plot the genome of a DO sample.
genotype.by.sample.barplot Genome summary plots
genotype.by.snp.barplot Genome summary plots
get.additive Condense 36 state genotypes down to founder genotypes.
get.chr.lengths Get chromosome lengths for the mouse
get.do.states Get the 36 genotype states for the DO
get.dominance Condense 36 state genotypes down to founder genotypes.
get.full Condense 36 state genotypes down to founder genotypes.
get.gene.name Get the gene symbol
get.machine.precision Get the machine precsion
get.max.geno Get the genotype with the highest probability
get.mgi.features get.mgi.features
get.num.auto Get the number of autosomes
get.pattern.variants get.pattern.variants
get.strains get.strains
get.trans.probs Get the transition probabilities between markers.
get.variants get.variants
get.vcf.strains Read and parse VCFALSE data
html.report Create an HTML report for a set of QTL
intensity.mean.covar.plot Plot founders and F1 hybrids or genotype state means and variances on an intensity plot.
keep.homozygotes Estimate genotype cluster means and variances
kinship.alleles Create a kinship matrix.
kinship.probs Create a kinship matrix.
matrixeqtl.snps Mapping using the Matrix EQTL algorithm.
muga.snps.to.keep SNPs to use for genotyping and mapping on the MUGA
normalize.batches Batch normalize the X & Y intensity data.
num.recomb.plot Summarize the genotype data output by the genotyping HMM.
permutations.qtl.LRS QTL mapping with no kinship.
plot.doqtl Plot a QTL
plot.genoprobs Plot the genome of a DO sample.
prsmth.plot Plot the genome of a DO sample.
pxg.plot Phenotype by genotype plot at a single marker.
qtl.heatmap Plot a Heatmap of all QTL
qtl.LRS QTL mapping with no kinship.
qtl.qtlrel Use QTLRel to map a set of traits
qtl.simulate Simulate a QTL in the DO
quantilenorm Batch normalize the X & Y intensity data.
rankZ Rank Z transformation
read.vcf Read and parse VCFALSE data
rowSumsLog Sum columns of log transformed data.
scanone Perform a genome scan.
scanone.eqtl Mapping using the Matrix EQTL algorithm.
scanone.perm Perform a genome scan.
sdp.plot Plot association mapping results.
sex.predict Determine the sex of each sample
snp.plot snp.plot
summarize.by.samples Summarize the genotype data output by the genotyping HMM.
summarize.by.snps Summarize the genotype data output by the genotyping HMM.
summarize.genotype.transitions Summarize the genotype data output by the genotyping HMM.
variant.plot variant.plot
write.founder.genomes Write out the genotypes of DO samples
write.genoprob.plots Plot the genome of a DO sample.