bpStats,CopyNumberBreakPoints-method {GeneBreak} | R Documentation |
Applies cohort-based statistics to identify genes and/or chromosomal locations that are recurrently affected by breakpoints.
## S4 method for signature 'CopyNumberBreakPoints' bpStats(object, level = "gene", method = "BH", fdr.threshold = 1)
object |
An object of class CopyNumberBreakPointGenes |
level |
The level at which to operate, this can be either "gene" (correcting for gene length) or "feature" (per probe/bin) |
method |
The FDR correction method to apply. This can be "BH" (applies Benjamini-Hochberg-type FDR correction) or "Gilbert" (for dedicated Benjamini-Hochberg-type FDR correction) |
fdr.threshold |
The threshold for FDR correction' |
The statistical method on gene-level corrects for covariates that may influence the probability to be a breakpoint gene including number of breakpoints in a profile, number of gene-associated features and gene length by gene-associated feature coverage. The statistical analysis includes multiple testing where standard Benjamini-Hochberg-type FDR correction will be performed by default. This less computational intensive method assumes a similar null-distribution for all candidate breakpoint events and satisfies for analysis on breakpoint location-level. For statistics on gene-level however, we recommend to apply the more comprehensive and powerful dedicated Benjamini-Hochberg-type FDR correction that accounts for discreteness in null-distribution (Gilbert, 2005) following correction for covariates that may influence the probability to be a breakpoint gene including number of breakpoints in a profile, number of gene-associated features and gene length by gene-associated feature coverage.
Returns an object of class CopyNumberBreakPointGenes with cohort based statistics added.
Gilbert,P.B. (2005) A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics. Journal of the Royal Statistical Society Series C-Applied Statistics, 54, 143-158.
data( copynumber.data.chr20 ) data( ens.gene.ann.hg18 ) bp <- getBreakpoints( copynumber.data.chr20 ) bp <- bpFilter( bp ) bp <- addGeneAnnotation( bp, ens.gene.ann.hg18 ) bp <- bpGenes( bp ) bp <- bpStats( bp ) ## options to inspect the data bp accessOptions( bp )