tSNE

Source: R/DimReduction.R

calculate tSNE from top variable genes

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))

#> Preparing PCA inputs using the top 1500 genes ...
#> Computing PCA values...
#> Running tSNE ...