PlotTransBiasGeneExpToPdf {ICAMS} | R Documentation |
Plot transcription strand bias with respect to gene expression values to a PDF file
Description
Plot transcription strand bias with respect to gene expression values to a PDF file
Usage
PlotTransBiasGeneExpToPdf(
annotated.SBS.vcf,
file,
expression.data,
Ensembl.gene.ID.col,
expression.value.col,
num.of.bins,
plot.type = c("C>A", "C>G", "C>T", "T>A", "T>C", "T>G"),
damaged.base = NULL
)
Arguments
annotated.SBS.vcf |
An SBS VCF annotated by
|
file |
The name of output file. |
expression.data |
A |
Ensembl.gene.ID.col |
Name of column which has the Ensembl gene ID
information in |
expression.value.col |
Name of column which has the gene expression
values in |
num.of.bins |
The number of bins that will be plotted on the graph. |
plot.type |
A vector of character indicating types to be plotted. It can be one or more types from "C>A", "C>G", "C>T", "T>A", "T>C", "T>G". The default is to print all the six mutation types. |
damaged.base |
One of |
Value
A list whose first element is a logic value indicating whether the plot is successful. The second element is a named numeric vector containing the p-values printed on the plot.
Note
The p-values are calculated by logistic regression using function
glm
. The dependent variable is labeled "1" and "0" if
the mutation from annotated.SBS.vcf
falls onto the untranscribed and
transcribed strand respectively. The independent variable is the binary
logarithm of the gene expression value from expression.data
plus one,
i.e. log_2 (x + 1)
where x
stands for gene
expression value.
Examples
file <- c(system.file("extdata/Strelka-SBS-vcf/",
"Strelka.SBS.GRCh37.s1.vcf",
package = "ICAMS"))
list.of.vcfs <- ReadAndSplitStrelkaSBSVCFs(file)
SBS.vcf <- list.of.vcfs$SBS.vcfs[[1]]
if (requireNamespace("BSgenome.Hsapiens.1000genomes.hs37d5", quietly = TRUE)) {
annotated.SBS.vcf <- AnnotateSBSVCF(SBS.vcf, ref.genome = "hg19",
trans.ranges = trans.ranges.GRCh37)
PlotTransBiasGeneExpToPdf(annotated.SBS.vcf = annotated.SBS.vcf,
expression.data = gene.expression.data.HepG2,
Ensembl.gene.ID.col = "Ensembl.gene.ID",
expression.value.col = "TPM",
num.of.bins = 4,
plot.type = c("C>A","C>G","C>T","T>A","T>C"),
file = file.path(tempdir(), "test.pdf"))
}