ctFilter: Create a filtered subset of count matrix based on supplied...

In Dudemanguy/RNASeqSuite: Convenient R wrapper of popular RNAseq pipelines designed to simplify data analysis

Description

Subsets and filters the count matrix based on supplied group and filters.

Usage

ctFilter(data, frame, group, htsfilter=TRUE, cfilter=0, cutoff=0)

Arguments

data	A data frame of the raw counts
frame	A data frame containing the selected samples and their respective groups
group	The factor created from grpSelection containing the different group names
htsfilter	A boolean determining whether or not to use HTSFilter to filter count matrix
cfilter	A numeric value controlling the use of cfilter, a custom outlier detector
cutoff	Filters based on a hard cutoff of read counts

Details

htsfilter calls the HTSFilter library if set to TRUE. This will remove genes based on a similarity ranking via a Jaccard index. Genes with constant, low counts will be removed.

cfilter is a custom outlier detector. cfilter normalizes the count vectors and then takes the difference between the two groups. The standard deviation and mean of the difference vector is stored and the genes are subsequently filtered based on the value of cfilter. Gene count values that lie outside of the standard deviation times the cfilter will be filtered. The lower the value of cfilter, the more stringent the filter will be. The default value of 0 disables this filter.

cutoff is a hard count cutoff. The average of every group is calculated and if the average for all groups falls below the specified cutoff value, the gene is removed. The default value of 0 disables this filter.

Examples

ct <- ctFilter(data, frame, group, htsfilter=TRUE, cfilter=2, cutoff=100)

Dudemanguy/RNASeqSuite documentation built on Dec. 5, 2019, 12:45 a.m.