findNDim: Establish what subsets of loadings from PCA distance measure...

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)

Establish what subsets of loadings from PCA distance measure are used for for measuring cluster instability

Description

Establish what subsets of loadings from PCA distance measure are used for for measuring cluster instability

Usage

findNDim(n, distPCA, pcaMin, pcaMax)

Arguments

n	number of samples
distPCA	PCA reduced distance matrix
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.

Value

list of numbers with each number corresponding to the number of loadings to use for clustering.

khazum/ccImpute documentation built on Nov. 28, 2022, 7:27 a.m.