ssc.run: Wrapper for running all the pipeline

In Japrin/sscClust: simpler single cell RNAseq data clustering

Wrapper for running all the pipeline

Description

Wrapper for running all the pipeline

Usage

ssc.run(
  obj,
  assay.name = "exprs",
  method.vgene = "HVG.sd",
  sd.n = 1500,
  mean.thre = 0.1,
  fdr.thre = 0.001,
  var.block = NULL,
  method.reduction = "iCor",
  method.clust = "kmeans",
  method.classify = "knn",
  method.tsne = "Rtsne",
  pca.npc = NULL,
  iCor.niter = 1,
  iCor.method = "spearman",
  tSNE.perplexity = 30,
  subsampling = F,
  sub.frac = 0.4,
  sub.use.proj = T,
  sub.vis.proj = F,
  k.batch = 2:6,
  refineGene = F,
  de.n = 1500,
  HSD.FC.THRESHOLD = 1,
  nIter = 1,
  out.prefix = NULL,
  parfile = NULL,
  reuse = F,
  ncore = NULL,
  seed = NULL,
  do.DE = F,
  ...
)

Arguments

obj	object of singleCellExperiment class
assay.name	character; which assay (default: "exprs")
method.vgene	character; variable gene identification method used. (default: "sd")
sd.n	integer; top number of genes as variable genes (default 1500)
mean.thre	numeric; threshold for mean, used in trendVar method (default 0.1)
fdr.thre	numeric; threshold for fdr, used in trendVar method (default 0.001)
var.block	character; specify the uninteresting factors by formula. E.g. "~patient". used in trendVar method (default NULL)
method.reduction	character; which dimention reduction method to be used, should be one of "iCor", "pca", and "none". (default: "iCor")
method.clust	character; clustering method to be used, should be one of "kmeans", "hclust", "SNN", "adpclust" and "SC3. (default: "kmeans")
method.classify	character; method used for classification, one of "knn" and "RF". (default: "knn")
method.tsne	character; method to run tsne, one of "Rtsne", "FIt-SNE". (default: "Rtsne")
pca.npc	integer; number of pc be used. Only for reduction method "pca". (default: NULL)
iCor.niter	integer; number of iteration of calculating the correlation. Used in reduction method "iCor". (default: 1)
iCor.method	character; correlation method, one of "spearman", "pearson" (default: "spearman")
tSNE.perplexity	double, perplexity parameter of tSNE. (default: 30)
subsampling	logical; whether cluster using the subsampling->cluster->classification method. (default: F)
sub.frac	numeric; subsample to frac of original samples. (default: 0.4)
sub.use.proj	logical; whether use the projected data for classification. (default: T)
sub.vis.proj	logical; whether get low dimensional representation for visualization, only used in downsample mode. (default: F)
k.batch	integer; number of clusters to be evaluated. (default: 2:6)
refineGene	logical; whether perform second round demension reduction and clustering pipeline using the differential genes found by the first round cluster result. (default: F)
de.n	integer; number of differential genes used for refined geneset for another run of clustering (default 1500)
HSD.FC.THRESHOLD	numeric; threshold for log2FoldChange, used in findDEGenesByAOV (default 1)
nIter	integer; number of iterative clustering in sub-cluster. (default: 1)
out.prefix	character; output prefix, if not NULL, some plots of intermediate result will be produced. (default: NULL)
parfile	character; parameter files, if not NULL, will use the settings. must contain a list named 'parlist'. (default: NULL)
reuse	logical; don't calculate if the query is already available. (default: F)
ncore	integer; nuber of CPU cores to use. if NULL, automatically detect the number. (default: NULL)
seed	integer; seed of random number generation. (default: NULL)
do.DE	logical; perform DE analysis when clustering finished. (default: F)
...	parameters pass to clustering methods

Details

run the pipeline of variable gene identification, dimension reduction, clustering.

Value

an object of SingleCellExperiment class with cluster labels added.

See Also

ssc.variableGene for variable genes' identification, ssc.reduceDim for dimension reduction, ssc.clust for clustering using all data and ssc.clustSubsamplingClassification for clustering with subsampling.

Japrin/sscClust documentation built on Dec. 15, 2022, 1:04 p.m.