sparseSolver2: Fast Calculation of "Dropout" values

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)

Fast Calculation of "Dropout" values

Description

Fast Calculation of "Dropout" values

Usage

sparseSolver2(cm, em, ids, n_cores)

Arguments

cm	A numeric matrix representing the consensus matrix.
em	A sparse numeric matrix representing the gene expression data, where rows are genes and columns are samples.
ids	An integer matrix specifying the row and column indices of entries for which to calculate importance scores. Each row of 'ids' should contain two integers: the row index (gene) and column index (sample) in the 'em' matrix.
n_cores	The number of cores to use for parallel processing.

Value

A numeric vector of imputed dropout values, corresponding to the entries specified in the 'ids' matrix.

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