basicP2proc: Perform basic 'pagoda2' processing, i.e. adjust variance, calculate pca reduction, make knn graph, identify clusters with multilevel, and generate largeVis and tSNE embeddings.

Description

Perform basic 'pagoda2' processing, i.e. adjust variance, calculate pca reduction, make knn graph, identify clusters with multilevel, and generate largeVis and tSNE embeddings.

Usage

basicP2proc(
  cd,
  n.cores = 1,
  n.odgenes = 3000,
  nPcs = 100,
  k = 30,
  perplexity = 50,
  log.scale = TRUE,
  trim = 10,
  keep.genes = NULL,
  min.cells.per.gene = 0,
  min.transcripts.per.cell = 100,
  get.largevis = TRUE,
  get.tsne = TRUE,
  make.geneknn = TRUE
)

Value

a new 'Pagoda2' object

Arguments

cd: count matrix whereby rows are genes, columns are cells.
n.cores: numeric Number of cores to use (default=1)
n.odgenes: numeric Number of top overdispersed genes to use (dfault=3e3)
nPcs: numeric Number of PCs to use (default=100)
k: numeric Default number of neighbors to use in kNN graph (default=30)
perplexity: numeric Perplexity to use in generating tSNE and largeVis embeddings (default=50)
log.scale: boolean Whether to use log scale normalization (default=TRUE)
trim: numeric Number of cells to trim in winsorization (default=10)
keep.genes: optional set of genes to keep from being filtered out (even at low counts) (default=NULL)
min.cells.per.gene: numeric Minimal number of cells required for gene to be kept (unless listed in keep.genes) (default=0)
min.transcripts.per.cell: numeric Minimumal number of molecules/reads for a cell to be admitted (default=100)
get.largevis: boolean Whether to caluclate largeVis embedding (default=TRUE)
get.tsne: boolean Whether to calculate tSNE embedding (default=TRUE)
make.geneknn: boolean Whether pre-calculate gene kNN (for gene search) (default=TRUE)