MeanVarPlot: Identify variable genes

In nukappa/seurat_v2: Seurat : R toolkit for single cell genomics

Description

Identifies genes that are outliers on a 'mean variability plot'. First, uses a function to calculate average expression (fxn.x) and dispersion (fxn.y) for each gene. Next, divides genes into num.bin (deafult 20) bins based on their average expression, and calculates z-scores for dispersion within each bin. The purpose of this is to identify variable genes while controlling for the strong relationship between variability and average expression.

Usage

MeanVarPlot(object, fxn.x = expMean, fxn.y = logVarDivMean,
  do.plot = TRUE, set.var.genes = TRUE, do.text = TRUE,
  x.low.cutoff = 0.1, x.high.cutoff = 8, y.cutoff = 2,
  y.high.cutoff = Inf, cex.use = 0.5, cex.text.use = 0.5,
  do.spike = FALSE, pch.use = 16, col.use = "black",
  spike.col.use = "red", plot.both = FALSE, do.contour = TRUE,
  contour.lwd = 3, contour.col = "white", contour.lty = 2, num.bin = 20,
  do.recalc = TRUE)

Arguments

object	Seurat object
fxn.x	Function to compute x-axis value (average expression). Default is to take the mean of the detected (i.e. non-zero) values
fxn.y	Function to compute y-axis value (dispersion). Default is to take the standard deviation of all values/
do.plot	Plot the average/dispersion relationship
set.var.genes	Set [e-mail] to the identified variable genes (default is TRUE)
do.text	Add text names of variable genes to plot (default is TRUE)
x.low.cutoff	Bottom cutoff on x-axis for identifying variable genes
x.high.cutoff	Top cutoff on x-axis for identifying variable genes
y.cutoff	Bottom cutoff on y-axis for identifying variable genes
y.high.cutoff	Top cutoff on y-axis for identifying variable genes
cex.use	Point size
cex.text.use	Text size
do.spike	FALSE by default. If TRUE, color all genes starting with ^ERCC a different color
pch.use	Pch value for points
col.use	Color to use
spike.col.use	if do.spike, color for spike-in genes
plot.both	Plot both the scaled and non-scaled graphs.
do.contour	Draw contour lines calculated based on all genes
contour.lwd	Contour line width
contour.col	Contour line color
contour.lty	Contour line type
num.bin	Total number of bins to use in the scaled analysis (default is 20)
do.recalc	TRUE by default. If FALSE, plots and selects variable genes without recalculating statistics for each gene.

Details

Exact parameter settings may vary empirically from dataset to dataset, and based on visual inspection of the plot. Setting the y.cutoff parameter to 2 identifies genes that are more than two standard deviations away from the average dispersion within a bin. The default X-axis function is the mean expression level, and for Y-axis it is the log(Variance/mean). All mean/variance calculations are not performed in log-space, but the results are reported in log-space - see relevant functions for exact details.

Value

Returns a Seurat object, placing variable genes in [e-mail]. The result of all analysis is stored in [e-mail]

nukappa/seurat_v2 documentation built on May 24, 2019, 9:57 a.m.