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)

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Documentation for package ‘ccImpute’ version 1.6.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

ccImpute	Impute Dropout Values in Single-Cell RNA Sequencing Data
ccImpute-method	Impute Dropout Values in Single-Cell RNA Sequencing Data
ccImpute.SingleCellExperiment	Impute Dropout Values in Single-Cell RNA Sequencing Data
colRanks_fast	Computes rankings for each column of a matrix in parallel.
computeDropouts	Impute Dropout Values in a Log-normalized Expression Count Matrix
cor_fast	Computes a Pearson
doSVD	Perform Truncated Singular Value Decomposition (SVD)
estkTW	Estimate the Number of Clusters (k) Using the Tracy-Widom Bound
findDropouts	Identify Dropout Events in Single-Cell Expression Data
getConsMtx	This function calculates an average consensus matrix from a set of clustering solutions. It filters out values below a specified minimum threshold ('consMin') and normalizes the remaining non-zero columns to sum to 1.
getCorM	Calculate Column-wise Correlation Matrix
getScale	Computes Means and Standard Deviations for Scaling
rowVars_fast	Computes Row Variances Efficiently
runKM	Perform Consensus K-Means Clustering
solver	Computes imputed expression matrix using linear eq solver
solver2	Fast Calculation of "Dropout" values
sparseColRanks_fast	Computes rankings for each column of a matrix in parallel.
sparseSolver2	Fast Calculation of "Dropout" values
wCor_fast	Computes a Weighted Pearson