ssc.variableGene: Identify variable genes

View source: R/sscClust.R

ssc.variableGeneR Documentation

Identify variable genes

Description

Identify variable genes which will be used in downstream analysis. Multiple methods are available.

Usage

ssc.variableGene(
  obj,
  method = "HVG.sd",
  sd.n = 1500,
  mean.thre = 0.1,
  fdr.thre = 0.001,
  assay.name = "exprs",
  var.block = NULL,
  reuse = F,
  out.prefix = NULL
)

Arguments

obj

object of SingleCellExperiment

method

method to be used, can be one of "HVG.sd", "HVG.mean.sd", "HVG.trendVar". (default: "HVG.sd")

sd.n

top number of 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)

assay.name

which assay to be used (default "exprs")

var.block

character; specify the uninteresting factors by formula. E.g. "~patient" (default NULL)

reuse

logical; don't calculate if the query is already available. (default: F)

out.prefix

character; if not NULL, output prefix. (default: F)

Details

Method "sd": calculate the standard deviation of each gene and sort decreasingly, the top 'sd.n' genes are the variable genes. Method "trendVar": fit the trend between variance and mean, and decompose each gene's variance into 'tech' part(fitted value) and 'bio' part (residual value), then select genes according FDR and mean threshold. Note, when using "trendVar", will use expression data stored in "norm_exprs" slot of 'obj', no matter what 'assay.name' is.

Value

an object of SingleCellExperiment class


Japrin/sscClust documentation built on May 23, 2024, 7:12 a.m.