SAM.DiffExpress: Use SAM for Differential Expression

Description Usage Arguments Details Value Note Author(s) References See Also

View source: R/samTools.R

Description

Use the SAM method to find differentially expressed genes from a set of transcriptome files.

Usage

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SAM.DiffExpress(fnames, fids, groupset, targetGroup = sort(groupset)[1], 
		geneColumn = "GENE_ID", intensityColumn = "INTENSITY", 
		keepIntergenics = FALSE, minimumIntensity = NULL, 
		missingGenes = "fill", 
		wt.folds = 1, wt.pvalues = 1, wt.dists = 1, ...)

Arguments

fnames

character vector of full pathnames to existing transcriptome files

fids

character vector of SampleIDs

groupset

character vector of GroupIDs or conditions, to categorize the transcripts

targetGroup

the one GroupID to be the chosen subset, to compare all other groups against. This is the group that is being tested for up-regulation.

geneColumn

column name of the column of GeneIDs

intensityColumn

column name of the column of intensity values

keepIntergenics

logical, explicity keep the non-genes, or drop them from consideration

minimumIntensity

the 'fudge factor' called 'S0' for SAM, that represents a minimum intensity added to all denominators to prevent division by zero and effectively scale the distances 'D' produced by SAM

missingGenes

method for dealing with genes that are not present in every transcript file. Either drop entire gene rows, or fill in with minimum observed intensity.

wt.folds, wt.pvalues, wt.dists

weight terms for influencing the final ordering of DE genes. See SAM.diffExpressRankOrder

Details

This function implements the SAM algorithm of Tusher, et.al., as implemented in R package 'siggenes' by H. Schwender.

Value

A data frame of consensus gene differential expression, sorted by consensus of up-regulation, with columns:

GENE_ID

the genes, sorted from most up-regulated to most down-regulated

PRODUCT

the gene product descriptions

LOG_2_FOLD

the average fold change for each gene

P_VALUE

the P-value for each gene

Q_VALUE

the Q-value for each gene

AVG_SET1

the average gene intensity over all samples in group targetGroup

AVG_SET2

the average gene intensity over all samples in the other groups

Note

Typically, this function is called once for each group, to get all possible DE comparisons between the various groups. While the function explicitly measures up-regulation, by reversing the order of the rows of the result, you get the answer for down-regulation.

Author(s)

Bob Morrison

References

V. Tusher, et.al., PNAS 98 (2001)

See Also

rankProductDiffExpress, for the Rank Product method.


robertdouglasmorrison/DuffyTools documentation built on Dec. 7, 2018, 8:02 a.m.