ClussCluster (version 0.1.0)

filter_gene: Gene Filter

Description

Filters out genes that are not suitable for differential expression analysis.

Usage

filter_gene(dfname, minmean = 2, n0prop = 0.2, minsd = 1)

Arguments

dfname

name of the expression data frame

minmean

minimum mean expression for each gene

n0prop

minimum proportion of zero expression (count) for each gene

minsd

minimum standard deviation of expression for each gene

Value

a list containing the data set with genes satisfying the thresholds, dat.ft, the name of dat.ft, and the indices of those kept genes, index.

Details

Takes an expression data frame that has been properly normalized but NOT centered. It returns a list with the slot dat.ft being the data set that satisfies the pre-set thresholds on minumum mean, standard deviation (sd), and proportion of zeros (n0prop) for each gene.

If the data has already been centered, one can still apply the filters of mean and sd but not n0prop.

Examples

# NOT RUN {
dat <- matrix(rnbinom(300*60, mu = 2, size = 1), 300, 60)
dat_filtered <- filter_gene(dat, minmean=2, n0prop=0.2, minsd=1)
# }