tSNE: tSNE

In IMB-Computational-Genomics-Lab/scGPS: A complete analysis of single cell subpopulations, from identifying subpopulations to analysing their relationship (scGPS = single cell Global Predictions of Subpopulation)

Description

calculate tSNE from top variable genes

Usage

tSNE(
  expression.mat = NULL,
  topgenes = 1500,
  scale = TRUE,
  thet = 0.5,
  perp = 30
)

Arguments

expression.mat	An expression matrix, with genes in rows
topgenes	number of genes used for clustering calculations.
scale	a logical of whether we want to scale the matrix
thet	numeric; Speed/accuracy trade-off (increase for less accuracy)
perp	numeric; Perplexity parameter (should not be bigger than 3 * perplexity < nrow(X) - 1, see details for interpretation)

Value

a tSNE reduced matrix containing three tSNE dimensions

Examples

day2 <- day_2_cardio_cell_sample
mixedpop1 <-new_scGPS_object(ExpressionMatrix = day2$dat2_counts, 
    GeneMetadata = day2$dat2geneInfo, CellMetadata = day2$dat2_clusters)
t <-tSNE(expression.mat = assay(mixedpop1))

IMB-Computational-Genomics-Lab/scGPS documentation built on Dec. 6, 2020, 3:20 p.m.