sparseColRanks_fast: Computes rankings for each column of a matrix in parallel.
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)
sparseColRanks_fast R Documentation
Computes rankings for each column of a matrix in parallel.
Description
Computes rankings for each column of a matrix in parallel.
Usage
sparseColRanks_fast(x, n_cores)
Arguments
x
The input matrix to be ranked.
n_cores
The number of CPU cores to use for parallel processing.
Value
A matrix where each column contains the rankings for the
corresponding column in the input matrix.
khazum/ccImpute documentation built on July 26, 2024, 1:13 a.m.
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| sparseColRanks_fast | R Documentation |
Computes rankings for each column of a matrix in parallel.
Description
Computes rankings for each column of a matrix in parallel.
Usage
sparseColRanks_fast(x, n_cores)
Arguments
x |
The input matrix to be ranked. |
n_cores |
The number of CPU cores to use for parallel processing. |
Value
A matrix where each column contains the rankings for the corresponding column in the input matrix.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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