impute: Performs imputation of dropout values in scRNA-seq data using...

In khazum/ccImpute_exp: ccImpute: an accurate and scalable consensus clustering based approach to impute dropout events in the single-cell RNA-seq data

Performs imputation of dropout values in scRNA-seq data using ccImpute algorithm

Description

Performs imputation of dropout values in scRNA-seq data using ccImpute algorithm

Usage

impute(
    logX,
    useRanks = TRUE,
    pcaMin,
    pcaMax,
    k,
    consMin = 0.65,
    nCores,
    kmNStart,
    kmMax = 1000
)

Arguments

logX	A normalized and log transformed scRNA-seq expression matrix.
useRanks	A Boolean specifying if non-parametric version of weighted Pearson correlation should be used.
pcaMin	This is used to establish the number of minimum PCA features used for generating subsets. For small datasets up to 500 cells this equals pcaMin*n minimum features, where n is number of cells. For large datasets, this corresponds to the feature count that has proportion of variance less than pcaMin. Both pcaMin and pcaMax must be specified to be considered.
pcaMax	This is used to establish the number of maximum PCA features used for generating subsets. For small datasets up to 500 cells this equals pcaMax*n maximum features, where n is number of cells. For large datasets, this corresponds to the feature count that has proportion of variance less than pcaMax. Both pcaMin and pcaMax must be specified to be considered.
k	centers parameter passed to kmeans function
consMin	the low-pass filter threshold for processing consensus matrix.
nCores	the number of cores to be used on the user's machine. If not set, ccImpute will use all but one cores of your machine.
kmNStart	nstart parameter passed to kmeans. function. Can be set manually. By default it is 1000 for up to 2000 cells and 50 for more than 2000 cells.
kmMax	iter.max parameter passed to kmeans.

Value

A normalized and log transformed scRNA-seq expression matrix with imputed missing values.

Examples

exp_matrix <- log(abs(matrix(rnorm(1000000),nrow=10000))+1)
impute(exp_matrix, k = 2, nCores = 2)

khazum/ccImpute_exp documentation built on May 25, 2022, 6:15 a.m.