SAM.DiffExpress | R Documentation |
Use the SAM method to find differentially expressed genes from a set of transcriptome files.
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, ...)
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
|
This function implements the SAM algorithm of Tusher, et.al., as implemented in R package 'siggenes' by H. Schwender.
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 |
AVG_SET2 |
the average gene intensity over all samples in the other groups |
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.
Bob Morrison
V. Tusher, et.al., PNAS 98 (2001)
rankProductDiffExpress
, for the Rank Product method.
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