bic.run.deseq.comparison: Run a differential expression comparison between two...
In bic-mskcc/bicrnaseq: MSKCC Bioinformatics Core RNASeq

Description Usage Arguments Value

Compare expression in condition B vs expression in condition B. Results include log2FC, adjusted p-val, and mean expression in each condition. Two result sets are included in returned list: one including ALL genes, and one including only genes differentially expressed as determined by max.p and min.abs.fc. User has the option to include in the results those genes with zero counts in one condition and count greater than min.count/mean(sizeFactors) in the other condition, even if the p-value is greater than max.p, as those genes may still be of interest.

1 2	bic.run.deseq.comparison(countDataSet, conds, condA, condB, max.p = 0.05, min.abs.fc = 2, min.count = 10, zeroaddQ = F, genes = c())

`countDataSet`	A countDataSet object created by running DESeq's newCountDataSet()
`conds`	Vector of sample conditons, in the same order as samples in raw count matrix
`condA`	The first condition in comparison (must be in conditions vector)
`condB`	The second condition in comparison (must be in conditions vector)
`max.p`	A number, the max p-value cutoff to determine which genes are considered differentially expressed; Default: 0.05
`min.abs.fc`	A number, the minimum absolute fold change cutoff to determine which genes are considered differentially expressed; Default: 2
`min.count`	A number, minimum average number of reads in one condition; Default: 10
`zeroaddQ`	Logical, indicates whether to include genes that have zero counts in one condition and insignificant p-value, but at least min.count/mean(sizeFactors) in the other condition; Default: FALSE
`genes`	A named vector of gene symbols, where the names are equivalent to the IDs in the original raw count matrix (e.g., Ensembl IDs); Default: NULL

List containing a matrix of ALL results, a matrix containing results for differentially expressed genes (as determined by cutoffs), a vector of DE genes, the cutoffs used in analysis, and norm factors (TO DO: reword this)

bic-mskcc/bicrnaseq documentation built on May 24, 2019, 3:04 a.m.