runScCombination: runScCombination

In wguo-research/scCancer: A package for automated processing of single cell RNA-seq data in cancer

runScCombination

Description

Perform multi-samples analyses.

Usage

runScCombination(
  single.savePaths,
  sampleNames,
  savePath,
  combName,
  authorName = NULL,
  comb.method = "NormalMNN",
  harmony.theta = NULL,
  harmony.lambda = NULL,
  harmony.sigma = 0.1,
  vars.to.regress = c("nCount_RNA", "mito.percent", "ribo.percent"),
  pc.use = 30,
  resolution = 0.8,
  clusterStashName = "comb.cluster",
  show.features = NULL,
  bool.add.features = T,
  bool.runDiffExpr = T,
  n.markers = 5,
  sample.colors = NULL,
  species = "human",
  genome = "hg19",
  hg.mm.mix = F,
  bool.runCellClassify = T,
  ct.templates = NULL,
  coor.names = c("tSNE_1", "tSNE_2"),
  bool.runMalignancy = T,
  cnv.ref.data = NULL,
  cnv.referAdjMat = NULL,
  cutoff = 0.1,
  p.value.cutoff = 0.5,
  bool.intraTumor = T,
  bool.runCellCycle = T,
  bool.runStemness = T,
  bool.runGeneSets = T,
  geneSets = NULL,
  geneSet.method = "average",
  bool.runExprProgram = T,
  nmf.rank = 50,
  genReport = T
)

Arguments

single.savePaths	A vecotr of paths containing the results files of step 'runScAnnotation' for each sample.
sampleNames	A vector of labels for all samples.
savePath	A path to save the results files. If NULL, the 'statPath' will be used instead.
combName	A label for the combined samples.
authorName	A character string for authors name and will be shown in the report.
comb.method	The method to combine samples. The default is "NormalMNN". "Harmony", "NormalMNN", "SeuratMNN", "Raw", "Regression" and "LIGER" are optional.
harmony.theta	The parameter 'theta' of function "RunHarmony" in the harmony package.
harmony.lambda	The parameter 'lambda' of function "RunHarmony" in the harmony package.
harmony.sigma	The parameter 'sigma' of function "RunHarmony" in the harmony package.
vars.to.regress	A vector indicating the variables to regress out in R package Seurat. The default is c("nCount_RNA", "mito.percent", "ribo.percent").
pc.use	An integer number indicating the number of PCs to use as input features. The default is 30.
resolution	A float number used in function 'FindClusters' in Seurat. The default is 0.8.
clusterStashName	A character string used as the name of cluster identies. The default is "default".
show.features	A list or vector for genes to be plotted in 'markerPlot'.
bool.add.features	A logical value indicating whether to add default features to 'show.features' or not.
bool.runDiffExpr	A logical value indicating whether to perform differential expressed analysis.
n.markers	An integer indicating the number of differential expressed genes showed in the plot. The defalut is 5.
sample.colors	The colors used for samples. The default is NULL, and the pre-set colors will be used.
species	A character string indicating what species the sample belong to. Only "human"(default) or "mouse" are allowed.
genome	A character string indicating the version of the reference gene annotation information. This information is mainly used to infer CNV profile and estimate malignancy. Only 'hg19' (defalut) or 'hg38' are allowed for "human" species, and only "mm10" is allowed for "mouse" species.
hg.mm.mix	A logical value indicating whether the sample is a mix of human cells and mouse cells(such as PDX sample). If TRUE, the arguments 'hg.mm.thres' and 'mix.anno' should be set to corresponding values.
bool.runCellClassify	A logical value indicating whether to predict the usual cell type. The default is TRUE.
ct.templates	A list of vectors of several cell type templates. The default is NULL and the templates prepared in this package will be used.
coor.names	A vector indicating the names of two-dimension coordinate used in visualization.
bool.runMalignancy	A logical value indicating whether to estimate malignancy.
cnv.ref.data	An expression matrix of gene by cell, which is used as the normal reference during estimating malignancy. The default is NULL, and an immune cells or bone marrow cells expression matrix will be used for human or mouse species, respectively.
cnv.referAdjMat	An adjacent matrix for the normal reference data. The larger the value, the closer the cell pair is. The default is NULL, and a SNN matrix of the default ref.data will be used.
cutoff	A threshold used in the CNV inference.
p.value.cutoff	A threshold to decide weather the bimodality distribution of malignancy score is significant.
bool.intraTumor	A logical value indicating whether to use the identified tumor clusters to perform following intra-tumor heterogeneity analyses.
bool.runCellCycle	A logical value indicating whether to estimate cell cycle scores.
bool.runStemness	A logical value indicating whether to estimate stemness scores.
bool.runGeneSets	A logical value indicating whether to estimate gene sets signature scores.
geneSets	A list of gene sets to be analyzed. The default is NULL and 50 hallmark gene sets from MSigDB will be used.
geneSet.method	The method to be used in calculate gene set scores. Currently, only "average" and "GSVA" are allowed.
bool.runExprProgram	A logical value indicating whether to run non-negative matrix factorization (NMF) to identify expression programs.
nmf.rank	An integer of decomposition rank used in NMF.
genReport	A logical value indicating whether to generate a .html/.md report (suggest to set TRUE).

Value

A results list with all useful objects used in the function.

wguo-research/scCancer documentation built on May 26, 2024, 9:12 p.m.