pp_preprocess: A wrapper function to quickly run standard processing...

In zzwch/convgene: This package is designed to conveniently convert gene between human and mouse.

Description

Run NormalizeData, CellCycleScoring, FindVariableFeatures, ScaleData, RunUMAP/TSNE and FindClusters.

Usage

pp_preprocess(
  object,
  scale.factor = 10000,
  s.features = cc.genes$s.genes,
  g2m.features = cc.genes$g2m.gene,
  do.regress.cc = T,
  pp = c("SCT", "RNA"),
  nfeatures = 2000,
  ndim = 20,
  skip_tsne = F,
  resolution = 0.5
)

Arguments

object	a Seurat object
scale.factor	Sets the scale factor for cell-level normalization. (NormalizeData)
s.features	A vector of features associated with S phase (CellCycleScoring)
g2m.features	A vector of features associated with G2M phase (CellCycleScoring)
do.regress.cc	regress out cell cycle scores (ScaleData)
pp	do SCTransform or standard RNA process
nfeatures	Number of features to return (SCTransform/FindVariableFeatures)
ndim	Number of dimensions to use for dimensionality reduction and clustering (RunUMAP/TSNE/FindClusters)
skip_tsne	you may set TRUE to skip RunTSNE step for large dataset.
resolution	Value of the resolution parameter (FindClusters)

Value

a Seurat object

zzwch/convgene documentation built on July 11, 2021, 9:41 a.m.