normaliseGeneExpression {psichomics} | R Documentation |
Filter and normalise gene expression
normaliseGeneExpression( geneExpr, geneFilter = NULL, method = "TMM", p = 0.75, log2transform = TRUE, priorCount = 0.25, performVoom = FALSE )
geneExpr |
Matrix or data frame: gene expression |
geneFilter |
Boolean: filtered genes |
method |
Character: normalisation method, including |
p |
percentile (between 0 and 1) of the counts that is aligned when |
log2transform |
Boolean: perform log2-transformation? |
priorCount |
Average count to add to each observation to avoid zeroes after log-transformation |
performVoom |
Boolean: perform mean-variance modelling
( |
edgeR::calcNormFactors
will be used to normalise gene
expression if one of the following methods is set: TMM
, RLE
,
upperquartile
or none
. However, voom
will
be used for normalisation if performVoom = TRUE
and the selected
method is quantile
.
Filtered and normalised gene expression
Other functions for gene expression pre-processing:
convertGeneIdentifiers()
,
filterGeneExpr()
,
plotGeneExprPerSample()
,
plotRowStats()
geneExpr <- readFile("ex_gene_expression.RDS") normaliseGeneExpression(geneExpr)