Why DESeq2 filter and remove genes with high count?
0 answers
No answers yet.
Log in to answer this question.
More posts like this
-
Differential Gene Expression Analysis with DESeq2: Is it correct to just get a subset of genes that…
written by Savindu •
-
what can cause high(> 80%) spike-ins and low read count (<100 reads) in low complexity ampseq run
written by eli_bayat •
-
Removal of 'low' counts before DESeq2 - what threshold?
written by dnljmrs •
-
Expression thresholds for enrichment analysis of RNA-Seq data
written by James Cook •
-
Deduplication using UMItools
written by Ati •
-
Survival plot between low and high expression of gene
written by Biologist
-
From read counts to genotypes, or even better, a vcf
written by Joanna.ilska •
-
number of grouping affect log2 fold change in DESeq2 analysis?
written by star
-
DESeq2 with 2 factors: problem to fit the negative binomial and weird p-value distributions
written by Aurelie MLB
-
Why Is Overdispersion Worse At Higher Coverage?
written by Stan Letovsky •
Outliers are removed, on both sides. Are those genes highly expressed in all samples or just a few?
If removed genes have high counts in all samples what is your explanation? @WouterDeCoster
How high is "high coverage"? DESeq2 performs a few different kinds of filtering. At the gene level, though, it only filters for maximal power. Regardless of how high the counts are, presumably that's why the gene got filtered. You can disable that (look for "independent filtering" in the documentation) if it's a problem.