reduceGenes_var: Reduce number of genes in expression matrix based on variance

In joeburns06/hocuspocus: A Suite of Single-Cell RNA-Seq Analysis Tools Built for Dummy Biologists

Description

Takes ExpressionSet object and (optionally) 1) eliminates genes that are expressed below the LOD in a specified number of samples, 2) eliminates genes whose coefficient of variation (CV) across cells is below a set limit, and 3) eliminates genes using the CV z-score/binning method within the Seurat package.

Usage

reduceGenes_var(cellData, exprGenes = TRUE, exprThresh = 1,
  cellThresh = 2, varThresh = TRUE, cv = 0.5, seuratThresh = FALSE,
  z_cutoff = 1.5, ...)

Arguments

cellData	ExpressionSet object created with readCells (and preferably transformed with prepCells)
exprGenes	Boolean specifying whether to remove genes that are expressed above the expression threshold (exprThresh) in fewer than the number of samples specified with cellThresh.
exprThresh	Numeric specifying the the threshold for considering a gene to be expressed. Note that if prepCells has been run, expression values will be on a log2 scale, so exprThresh = 1 corresponds to an expression level of 2 in untransformed space.
cellThresh	Integer indicating the number of cells in which a gene has to be expressed above the expression threshold (exprThresh) in order to be kept.
varThresh	Boolean specifying whether to remove genes whose CV across samples is less than the threshold specified with cv. If exprGenes and varThresh are both TRUE, exprGenes is performed prior to varThresh.
cv	Numeric specifying the CV threshold for varThresh. Values ranging from 0.1 to 0.5 are typically effective.
seuratThresh	Boolean specifying whether the Seurat package's method of elminating genes by variance is to be used. See the Seurat package documentation for more details. If exprThresh, varThresh, and seuratThresh are all TRUE, they are performed in that order.
z_cutoff	Numeric specifying the z-score cutoff for the Seurat method.
...	Pass more options to the Seurat function mean.var.plot()

Value

ExpressionSet object with genes removed from the expression matrix according to the optional parameters specified above. Note that the original list of genes will still be present within fData. Genes that pass filter will be stored in fData as TRUE, genes that do not pass filter will be stored as FALSE.

joeburns06/hocuspocus documentation built on May 19, 2019, 2:59 p.m.