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bcRep (version 1.3.6)

compare.geneUsage: Compare gene usage of different samples

Description

This function compares the gene usage of different samples (see details!). Analysis can be done for subgroups, genes and alleles (see Details). Values can be returned as relative or absolute abundance. Parallel processing is possible.

Usage

compare.geneUsage(gene.list = NULL, level = c("subgroup", "gene", "allele"), abundance = c("relative", "absolute"), names = NULL, nrCores = 1)
plotCompareGeneUsage(comp.tab = NULL, color = c("gray97", "darkblue"), title = NULL, PDF = NULL)

Arguments

gene.list
A list containing vectors of genes of each sample
level
Gene level used for gene usage analysis: subgroup, gene, allele
abundance
Shall relative or absolute values be returned? (default: relative)
names
A vector containing names for the samples (default: like Sample1, Sample2, ...)
nrCores
Number of cores used for parallel processing
comp.tab
Output tab from compare.geneUsage()
color
Colors used for heatmap (default: gray and darkblue)
title
Title of plot
PDF
PDF project name (see Details)

Value

Output is a data frame containing absolue or relative values of gene usage of each sample.

Details

Gene usage analysis will be done for each sample. Vector of genes will be analyzed for one of the levels subgroup (e.g. IGHV1), gene (e.g. IGHV1-1) or allele (e.g. IGHV1-1*2). Proportions (abundance = "relative") are always based on the number of all alleles found in list: the number of the subgroup/gene/allele is divided by the number of all alleles mentioned for all sequences (in the case there are more alleles/genes mentioned for one sequence).

The PDF character string should be only the project name (without ".pdf").

A figure called "PDF"_Comparison_Gene-usage.pdf will be saved to the working directory.

See Also

geneUsage, compare.geneUsage, plotCompareGeneUsage

Examples

Run this code
data(aaseqtab)
data(aaseqtab2)

Vgenes.comp<-compare.geneUsage(gene.list = list(aaseqtab$V_GENE_and_allele, 
     aaseqtab2$V_GENE_and_allele), level = "subgroup", abundance = "relative", 
     names = c("IndA", "IndB"), nrCores = 1)
## Not run: 
# plotCompareGeneUsage(comp.tab = Vgenes.comp, color = c("gray97", "darkblue"), PDF = "Example")
# ## End(Not run)

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