Transformations {GiANT} | R Documentation |
Transformations
Description
Functions to transform the gene-level statistic values prior to the calculation of the gene set statistics, as used in the transformation
parameter of gsAnalysis
. Most of the functions wrap existing R functions.
Usage
transformation.abs(x)
transformation.square(x)
transformation.localFdr(x,
statistic="pvalue",
cutoff.method="fndr",
pct0=0.75)
transformation.binarize(x, quant)
transformation.rank(x)
transformation.adjust(x, adjMethod = "fdr")
transformation.adjustAndBinarize(x, adjMethod = "fdr", threshold = 0.05)
Arguments
x |
A numeric vector of gene-level statistic values, one per gene. These values are calculated by the previous step (see |
statistic |
Specifies the null model for |
cutoff.method |
Type of cut-off method used in |
pct0 |
Fraction of data used by |
quant |
For |
adjMethod |
The method to use for the adjustment for multiple testing (see |
threshold |
The threshold for differential expression of a gene (defaults to |
Details
Standard transformation functions for gene-level statistics (to be used in an analysis pipeline defined by gsAnalysis
):
-
transformation.abs
: Calculates the absolute values of the elements inx
(a wrapper forabs
). -
transformation.square
: Squares all elements inx
. -
transformation.localFdr
: Calculates the local fdr for the elements inx
. This is a wrapper forfdrtool
. -
transformation.binarize
: Binarizes the values inx
by using thequant
quantile as a threshold. -
transformation.rank
: Ranks the values inx
and returns the rank vector. -
transformation.adjust
: Adjusts for multiple testing according to the adjustment method specified inadjMethod
. -
transformation.adjustAndBinarize
: Adjusts for multiple testing according to the adjustment method specified inadjMethod
and binarizes the resulting p-values according tothreshold
(values smaller than the threshold become 1 others 0).
Value
All functions return a vector of transformed values having the same length as x
.
See Also
geneSetAnalysis
, gsAnalysis
, gss
, gls