plotPCElbow: Plot PC Elbow

In roryk/bcbioSinglecell: Single-Cell RNA-Seq Utilities

Description

Calculate the principal component (PC) cutoff using a heuristic approach.

Usage

plotPCElbow(object, ...)

## S4 method for signature 'seurat'
plotPCElbow(object, minSD = 1L, minPct = 0.025,
  maxCumPct = 0.9, trans = c("identity", "sqrt"), plot = TRUE)

Arguments

object	Object.
...	Additional arguments.
minSD	Minimum standard deviation.
minPct	Minimum percent standard deviation.
maxCumPct	Maximum cumulative percent standard deviation.
trans	Name of the axis scale transformation to apply. See help("scale_x_continuous", "ggplot2") for more information.
plot	Include plot.

Details

Automatically return the smallest number of PCs that match the minSD, minPct, and maxCumPct cutoffs.

Value

• Show graphical output of elbow plots.

• Invisibly return numeric sequence vector of PCs to include for dimensionality reduction analysis.

Author(s)

Michael Steinbaugh

See Also

• Seurat::PCElbowPlot().

Other Clustering Functions: cellTypesPerCluster, knownMarkersDetected, plotCellTypesPerCluster, plotFeatureTSNE, plotKnownMarkersDetected, plotTSNE, sanitizeMarkers, topMarkers

Examples

# seurat ====
plotPCElbow(seurat_small)

roryk/bcbioSinglecell documentation built on May 27, 2019, 10:44 p.m.