results: Pulling out result

In NBAMSeq: Negative Binomial Additive Model for RNA-Seq Data

Description

This function pulls out result from NBAMSeqDataSet object returned by NBAMSeq

Usage

results(object, name, contrast, indepfilter = TRUE, alpha = 0.1,
  pAdjustMethod = "BH", parallel = FALSE, BPPARAM = bpparam(), ...)

Arguments

object	a NBAMSeqDataSet object returned by NBAMSeq
name	the name of nonlinear variable or continuous linear variable
contrast	a character of length 3. 1st element: name of factor variable; 2nd element: name of numerator level; 3rd element: name of denominator level. contrast = c("group", "treatment", "control") means comparing treatment vs control for group variable.
indepfilter	either TRUE or FALSE indicating whether independent filtering should be performed. Default is TRUE.
alpha	significant threhold for declaring genes as differentially expressed. Default is 0.1.
pAdjustMethod	pvalue adjustment method. Default is "BH". See p.adjust for details.
parallel	either TRUE or FALSE indicating whether parallel should be used. Default is FALSE.
BPPARAM	an argument provided to bplapply. See register for details.
...	additional arguments provided to pvalueAdjustment function in DESeq2. See results for details.

Value

a DataFrame which contains the result

References

Love, M.I., Huber, W., Anders, S. (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15:550. https://doi.org/10.1186/s13059-014-0550-8

Examples

gsd = makeExample(n = 3, m = 10)
gsd = NBAMSeq(gsd)
res = results(gsd, name = "pheno")

NBAMSeq documentation built on Nov. 8, 2020, 6:26 p.m.