rowVars_fast: Computes Row Variances Efficiently

In khazum/ccImpute: ccImpute: an accurate and scalable consensus clustering based approach to impute dropout events in the single-cell RNA-seq data (https://doi.org/10.1186/s12859-022-04814-8)

Computes Row Variances Efficiently

Description

Computes Row Variances Efficiently

Usage

rowVars_fast(x, n_cores)

Arguments

x	A numeric dense matrix for which to compute row variances.
n_cores	The number of cores to utilize for parallel processing.

Value

A numeric vector containing the variance for each row of the input matrix.

Examples

library(Matrix)
rand_vals <- sample(0:10,1e4,replace=TRUE, p=c(0.99,rep(0.001,10)))
x <- as.matrix(Matrix(rand_vals,ncol=5))
cores <- 2
vars_vector <- rowVars_fast(x, cores)

khazum/ccImpute documentation built on July 26, 2024, 1:13 a.m.