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

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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