Plot comparison of batch corrected result against original assay

plotBatchCorrCompare(
  inSCE,
  corrMat,
  batch = NULL,
  condition = NULL,
  origAssay = NULL,
  origLogged = NULL,
  method = NULL,
  matType = NULL
)

Arguments

inSCE: SingleCellExperiment inherited object.
corrMat: A single character indicating the name of the corrected matrix.
batch: A single character. The name of batch annotation column in colData(inSCE).
condition: A single character. The name of an additional covariate annotation column in colData(inSCE).
origAssay: A single character indicating what the original assay used for batch correction is.
origLogged: Logical scalar indicating whether origAssay is log-normalized.
method: A single character indicating the name of the batch correction method. Only used for the titles of plots.
matType: A single character indicating the type of the batch correction result matrix, choose from "assay", "altExp", "reducedDim".

Value

An object of class "gtable", combining four ggplots.

Details

Four plots will be combined. Two of them are violin/box-plots for percent variance explained by the batch variation, and optionally the covariate, for original and corrected. The other two are UMAPs of the original assay and the correction result matrix. If SCTK batch correction methods are performed in advance, this function will automatically detect necessary input. Otherwise, users can also customize the input. Future improvement might include solution to reduce redundant UMAP calculation.

Author

Yichen Wang

Examples

data("sceBatches")
sceBatches <- scaterlogNormCounts(sceBatches, "logcounts")
sceBatches <- runLimmaBC(sceBatches)
plotBatchCorrCompare(sceBatches, "LIMMA", condition = "cell_type")
#> Warning: Removed 1 rows containing missing values (geom_point).
#> Warning: Removed 55 rows containing missing values (geom_point).