dataFilter2: Filter low variance genes by given minimal 'mad' or 'var' or...

In Tong-Chen/ImageGP: For ImageGP cloud platform (https://www.bic.ac.cn/BIC)

Filter low variance genes by given minimal mad or var or other statistical value or keep top number/percent genes with bigger variances.

Description

Filter low variance genes by given minimal mad or var or other statistical value or keep top number/percent genes with bigger variances.

Usage

dataFilter2(
  datExpr,
  minimal_threshold = NULL,
  top_n = 1,
  rmVarZero = F,
  noLessThan = NULL,
  statistical_value_type = mad,
  keep_filtered_as_others = F,
  fillna = NULL
)

Arguments

datExpr	Normal gene expression matrix (gene x sample).
minimal_threshold	Minimal allowed statistical value.
top_n	An integer larger than 1 will be used to get top x genes (like top 5000). A float number less than 1 will be used to get top x fraction genes (like top 0.7 of all genes).
rmVarZero	Default TRUE. Remove genes with variance as 0. Normally for PCA or correlation analysis.
noLessThan	Specify the lowest number of genes to be kept. Default NULL meaning no lower limit.
statistical_value_type	Specify the way for statistical computation. Default mad, accept mean, var, sum, median.
keep_filtered_as_others	Get sums of all filtered items as an new item - Others. Default FALSE.
fillna	Fill NA with specified value.

Value

A dataframe.

Examples

df = generateAbundanceDF(nSample=30, nGrp=3)
dataFilter2(df)

Tong-Chen/ImageGP documentation built on April 14, 2025, 12:54 p.m.