wCor_fast: Computes a Weighted Pearson
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)
wCor_fast R Documentation
Computes a Weighted Pearson
Description
This function calculates weighted Pearson correlation matrix
Usage
wCor_fast(x, w, n_cores)
Arguments
x
The input matrix (dense), where each column represents a set of
observations.
w
A vector of weights, one for each observation (must have the same
number of elements as rows in 'x').
n_cores
The number of CPU cores to utilize for parallel computation.
Value
A weighted Pearson correlation matrix
khazum/ccImpute documentation built on July 26, 2024, 1:13 a.m.
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| wCor_fast | R Documentation |
Computes a Weighted Pearson
Description
This function calculates weighted Pearson correlation matrix
Usage
wCor_fast(x, w, n_cores)
Arguments
x |
The input matrix (dense), where each column represents a set of observations. |
w |
A vector of weights, one for each observation (must have the same number of elements as rows in 'x'). |
n_cores |
The number of CPU cores to utilize for parallel computation. |
Value
A weighted Pearson correlation 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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