HTSFilter-package: Filter replicated high-throughput transcriptome sequencing...

In HTSFilter: Filter replicated high-throughput transcriptome sequencing data

Description

This package implements a filtering procedure for replicated transcriptome sequencing data based on a global Jaccard similarity index in order to identify genes with low, constant levels of expression across one or more experimental conditions.

Details

Package:	HTSFilter
Type:	Package
Version:	1.31.1
Date:	2020-11-26
License:	Artistic-2.0
LazyLoad:	yes

Author(s)

Andrea Rau, Melina Gallopin, Gilles Celeux, and Florence Jaffrezic

Maintainer: Andrea Rau <[e-mail]>

References

R. Bourgon, R. Gentleman, and W. Huber. (2010) Independent filtering increases detection power for high- throughput experiments. PNAS 107(21):9546-9551.

P. Jaccard (1901). Etude comparative de la distribution orale dans une portion des Alpes et des Jura. Bulletin de la Societe Vaudoise des Sciences Naturelles, 37:547-549.

A. Rau, M. Gallopin, G. Celeux, F. Jaffrezic (2013). Data-based filtering for replicated high-throughput transcriptome sequencing experiments. Bioinformatics, doi: 10.1093/bioinformatics/btt350.

Examples

library(Biobase)
data("sultan")
conds <- pData(sultan)$cell.line

########################################################################
## Matrix or data.frame
########################################################################

filter <- HTSFilter(exprs(sultan), conds, s.len=25, plot=FALSE)

########################################################################
## DGEExact
########################################################################

library(edgeR)
dge <- DGEList(counts=exprs(sultan), group=conds)
dge <- calcNormFactors(dge)
dge <- estimateCommonDisp(dge)
dge <- estimateTagwiseDisp(dge)
et <- exactTest(dge)
et <- HTSFilter(et, DGEList=dge, s.len=25, plot=FALSE)$filteredData
## topTags(et)


########################################################################
## DESeq2
########################################################################

library(DESeq2)
conds <- gsub(" ", ".", conds)
dds <- DESeqDataSetFromMatrix(countData = exprs(sultan),
                              colData = data.frame(cell.line = conds),
                              design = ~ cell.line)
## Not run:
##
## dds <- DESeq(dds)
## filter <- HTSFilter(dds, s.len=25, plot=FALSE)$filteredData
## class(filter)
## res <- results(filter, independentFiltering=FALSE)

HTSFilter documentation built on Dec. 18, 2020, 2 a.m.