autoProcessRawSerObjs.basic: autoProcessRawSerObjs.basic: An automated and basic pipeline...
In eisascience/scCustFx: single-cell custom fxs Package

autoProcessRawSerObjs.basic

R Documentation

autoProcessRawSerObjs.basic: An automated and basic pipeline to process raw Seurat objects CellMembrane package.

Description

This is the entry point for processing raw scRNAseq data with Seurat & CellMembrane.

Usage

autoProcessRawSerObjs.basic(
  SerObjLS,
  verbose = T,
  doDoubletFinder = T,
  dropDoublets = F,
  featureData = NULL,
  doRawCountFilter = T,
  doMergeObjects = F,
  mergeObjectName = "MergedObjs",
  doNomalizeAndScale = T,
  doRegressBasic = T,
  doRegresspmito = T,
  doRemoveCellCycle = F,
  doDimReduxTrio = T,
  doSingleR = T,
  nCount_RNA.low = 0,
  nFeature.low = 200,
  pMito.low = 0,
  nCount_RNA.high = 20000,
  nFeature.high = 5000,
  pMito.high = 0.15,
  variableFeatureSelectionMethod = "vst",
  nVariableFeatures = 2000,
  mean.cutoff = c(0.0125, 3),
  dispersion.cutoff = c(0.5, Inf),
  block.size = 1000,
  variableGenesInclusion = NULL,
  variableGenesExclusion = NULL,
  npcs = 50,
  minDimsToUse = 15
)

Arguments

`SerObjLS`	A named list of Seurat object.
`verbose`	set T/F for print to screen msgs
`doDoubletFinder`	removed doublets from the seurat objects
`doRawCountFilter`	filter cells based on defined parameters
`doMergeObjects`	filter cells based on defined parameters
`doNomalizeAndScale`	filter cells based on defined parameters
`doRegressBasic`	filter cells based on defined parameters
`doRegresspmito`	filter cells based on defined parameters
`doRemoveCellCycle`	filter cells based on defined parameters
`doDimReduxTrio`	filter cells based on defined parameters
`doSingleR`	filter cells based on defined parameters
`nCount_RNA.low`	If doCellFilter=T, cells with nCount_RNA below this value will be filtered
`nFeature.low`	If doCellFilter=T, cells with nFeature below this value will be filtered
`pMito.low`	If doCellFilter=T, cells with percent mito below this value will be filtered
`nCount_RNA.high`	If doCellFilter=T, cells with nCount_RNA above this value will be filtered
`nFeature.high`	If doCellFilter=T, cells with nFeature above this value will be filtered
`pMito.high`	If doCellFilter=T, cells with percent mito above this value will be filtered
`variableFeatureSelectionMethod`	If doCellFilter=T, cells with percent mito below this value will be filtered
`nVariableFeatures`	If doCellFilter=T, cells with percent mito below this value will be filtered
`mean.cutoff`	If doCellFilter=T, cells with percent mito below this value will be filtered
`dispersion.cutoff`	If doCellFilter=T, cells with percent mito below this value will be filtered
`block.size`	If doCellFilter=T, cells with percent mito below this value will be filtered
`variableGenesInclusion`	If doCellFilter=T, cells with percent mito below this value will be filtered
`variableGenesExclusion`	If doCellFilter=T, cells with percent mito below this value will be filtered
`npcs`	If doCellFilter=T, cells with percent mito below this value will be filtered
`minDimsToUse`	If doCellFilter=T, cells with percent mito below this value will be filtered