SHARP_small: Run SHARP for small-size (< 5000) single-cell RNA datasets

In shibiaowan/SHARP: hyperfast and accurate single-cell RNA-Seq data clustering

Description

For small-size (< 5000) datasets, we don't need to partition the datasets into several groups. Instead, we simply use ensemble random projection and weighted ensemble meta-clustering algorithms.

Usage

SHARP_small(
  scExp,
  ncells,
  ensize.K,
  reduced.ndim,
  hmethod,
  N.cluster,
  indN.cluster,
  minN.cluster,
  maxN.cluster,
  sil.thre,
  height.Ntimes,
  flashmark,
  flag,
  n.cores,
  forview,
  rN.seed
)

Arguments

scExp	input single-cell expression matrix
ncells	number of single cells
ensize.K	number of applications of random projection for ensemble
reduced.ndim	the dimension to be reduced to

Examples

enresults = SHARP_small(scExp, ncells, ensize.K, reduced.ndim)

shibiaowan/SHARP documentation built on April 28, 2021, 1:56 p.m.