Find correlation between principal components (PCs) and covariates

Find correlation between principal components (PCs) and covariates

plotPCACovariates(object, ...)

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

Arguments

object	Object.
metrics	boolean. 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(1) or logical(1). Normalization method to apply: FALSE: Raw counts. When using a tximport-compatible caller, these are length scaled by default (see countsFromAbundance argument). When using a featureCounts-compatible caller, these are integer. tximport caller-specific normalizations: "tpm": Transcripts per million. Additional gene-level-specific normalizations: TRUE / "sf": Size factor (i.e. library size) normalized counts. See DESeq2::sizeFactors() for details. "fpkm": Fragments per kilobase per million mapped fragments. Requires fpkm = TRUE in bcbioRNASeq() call and gene annotations in rowRanges() with defined width. See DESeq2::fpkm() for details. "vst": Variance-stabilizing transformation (log2). Requires vst = TRUE to be set during bcbioRNASeq() call. See DESeq2::varianceStabilizingTransformation for more information. "rlog": Regularized log transformation (log2). Requires rlog = TRUE to be set during bcbioRNASeq() call. See DESeq2::rlog() for details. "tmm": Trimmed mean of M-values. Calculated on the fly. See edgeR::calcNormFactors() for details. "rle": Relative log expression transformation. Calculated on the fly. See relativeLogExpression() for details. Note that logical(1) support only applies to counts(). Other functions in the package require character(1) and use match.arg() internally.
...	Additional arguments, passed to DEGreport::degCovariates().

Value

ggplot.

Note

Requires the DEGreport package to be installed.

Updated 2019-10-30.

See also

• DEGreport::degCovariates().

• DESeq2::rlog().

• DESeq2::varianceStabilizingTransformation().

Examples

data(bcb)
if (requireNamespace("DEGreport", quietly = TRUE)) {
    plotPCACovariates(bcb)
}
#> 
#> running pca and calculating correlations for:
#> un-scaled  data in pca;
#> pve >= 5%;
#> kendall cor