Table of the Top Differentially Expressed Tags

Share:

Description

Extracts the top DE tags in a data frame for a given pair of groups, ranked by p-value or absolute log-fold change.

Usage

1
topTags(object, n=10, adjust.method="BH", sort.by="PValue", p.value=1)

Arguments

object

a DGEExact object (output from exactTest) or a DGELRT object (output from glmLRT), containing the (at least) the elements table: a data frame containing the log-concentration (i.e. expression level), the log-fold change in expression between the two groups/conditions and the p-value for differential expression, for each tag. If it is a DGEExact object, then topTags will also use the comparison element, which is a vector giving the two experimental groups/conditions being compared. The object may contain other elements that are not used by topTags.

n

scalar, number of tags to display/return

adjust.method

character string stating the method used to adjust p-values for multiple testing, passed on to p.adjust

sort.by

character string, should the top tags be sorted by p-value ("PValue"), by absolute log-fold change ("logFC"), or not sorted ("none").

p.value

cutoff value for adjusted p-values. Only tags with lower p-values are listed.

Value

an object of class TopTags containing the following elements for the top n most differentially expressed tags as determined by sort.by:

table

a data frame containing the elements logFC, the log-abundance ratio, i.e. fold change, for each tag in the two groups being compared, logCPM, the log-average concentration/abundance for each tag in the two groups being compared, PValue, exact p-value for differential expression using the NB model, FDR, the p-value adjusted for multiple testing as found using p.adjust using the method specified.

adjust.method

character string stating the method used to adjust p-values for multiple testing.

comparison

a vector giving the names of the two groups being compared.

test

character string stating the name of the test.

The dimensions, row names and column names of a TopTags object are defined by those of table, see dim.TopTags or dimnames.TopTags.

TopTags objects also have a show method so that printing produces a compact summary of their contents.

Note that the terms ‘tag’ and ‘gene’ are synonymous here. The function is only named as ‘Tags’ for historical reasons.

Author(s)

Mark Robinson, Davis McCarthy, Gordon Smyth

References

Robinson MD, Smyth GK (2008). Small-sample estimation of negative binomial dispersion, with applications to SAGE data. Biostatistics 9, 321-332.

Robinson MD, Smyth GK (2007). Moderated statistical tests for assessing differences in tag abundance. Bioinformatics 23, 2881-2887.

See Also

exactTest, glmLRT, p.adjust.

Analogous to topTable in the limma package.

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
# generate raw counts from NB, create list object
y <- matrix(rnbinom(80,size=1,mu=10),nrow=20)
d <- DGEList(counts=y,group=rep(1:2,each=2),lib.size=rep(c(1000:1001),2))
rownames(d$counts) <- paste("gene",1:nrow(d$counts),sep=".")

# estimate common dispersion and find differences in expression
# here we demonstrate the 'exact' methods, but the use of topTags is
# the same for a GLM analysis
d <- estimateCommonDisp(d)
de <- exactTest(d)

# look at top 10
topTags(de)
# Can specify how many genes to view
tp <- topTags(de, n=15)
# Here we view top 15
tp
# Or order by fold change instead
topTags(de,sort.by="logFC")

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.