filter_RNA_seq: Filtering of low counts

In Kumquatum/GWENA: Pipeline for augmented co-expression analysis

Filtering of low counts

Description

Keeping genes with at least one sample with count above min_count in RNA-seq data.

Usage

filter_RNA_seq(
  data_expr,
  min_count = 5,
  method = c("at least one", "mean", "all")
)

Arguments

data_expr	matrix or data.frame or SummarizedExperiment, table of expression values (either microarray or RNA-seq), with genes as column and samples as row.
min_count	integer, minimal number of count to be considered in method.
method	string, name of the method for filtering. Must be one of "at least one", "mean", or " all"

Details

Low counts in RNA-seq can bring noise to gene co-expression module building, so filtering them help to improve quality.

Value

A data.frame of filtered genes

Examples

df <- matrix(abs(rnorm(15*45)), 15) * 3
colnames(df) <- paste0("gene_", seq_len(ncol(df)))
rownames(df) <- paste0("sample_", seq_len(nrow(df)))
df_filtered <- filter_RNA_seq(df)

Kumquatum/GWENA documentation built on July 7, 2023, 3:41 p.m.