plotPCACovariates: Find Correlation Between Principal Components (PCs) and...

In roryk/bcbioRnaseq: RNA-Seq Utilities

Description

DEGreport::degCovariates() wrapper supporting a bcbioRNASeq object.

Usage

plotPCACovariates(object, ...)

## S4 method for signature 'bcbioRNASeq'
plotPCACovariates(object, metrics = TRUE,
  normalized = c("rlog", "vst", "tmm", "tpm"), ...)

Arguments

object	Object.
...	Additional arguments, passed to DEGreport::degCovariates().
metrics	Include sample summary metrics as covariates. Defaults to include all metrics columns (TRUE), but desired columns can be specified here as a character vector.
normalized	Character indicating which normalization method to apply: "tpm": Transcripts per million (tximport). "tmm": edgeR trimmed mean of M-values. Calculated on the fly. "rlog": DESeq2 log2 regularized log transformation. "vst": DESeq2 log2 variance stabilizing transformation.

Value

ggplot.

Author(s)

Lorena Pantano, Michael Steinbaugh

See Also

• DEGreport::degCovariates().

• DESeq2::rlog().

• DESeq2::varianceStabilizingTransformation().

Other Quality Control Functions: plot5Prime3PrimeBias, plotCorrelationHeatmap, plotCountDensity, plotCountsPerGene, plotDispEsts, plotExonicMappingRate, plotGenderMarkers, plotGeneSaturation, plotGenesDetected, plotIntronicMappingRate, plotMappedReads, plotMappingRate, plotMeanSD, plotPCA, plotRRNAMappingRate, plotTotalReads

Examples

plotPCACovariates(
    object = bcb_small,
    metrics = c("exonicRate", "intronicRate")
)

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