Changes in version 1.10                         

    o   .subset2index now converts factor inputs to character vectors,
	rather than treating them as integers.

                        Changes in version 1.8.0                        

    o   Removed support for use.altexps= in aggregateAcrossCells() and
	logNormCounts().

    o   Added swap.rownames= option to makePerCellDF() to allow easy
	access by rowData aliases. Also moved the extracted features to
	the end of the data frame for consistency.

                        Changes in version 1.2.0                        

    o   Migrated whichNonZero() to beachmat.

    o   Bugfixes for factor-based colData aggregation in
	aggregateAcrossCells(). Added proper support for Vectors.

    o   Bugfix for correct response to use.altexps= in
	perCellQCMetrics(), perFeatureQCMetrics().

    o   Added a normalize.all= option to normalizeCounts(). Removed
	unnecessary warning when down.target= is not specified. Exposed
	the default size.factors= in the SingleCellExperiment method.

    o   Modified the SingleCellExperiment method of logNormCounts() so
	that manually specified size factors do not apply to
	alternative Experiments. Only relevant if size.factors= and
	use.altexps= are specified.

    o   Deprecated use.altexps= in favor of applySCE() in
	logNormCounts() and aggregateAcrossCells().

    o   Renamed addPerCellQC() and addPerFeatureQC() to
	addPerCellQCMetrics() and addPerCellFeatureMetrics(), for
	consistency. Soft-deprecated the old functions.

    o   Moved most of quickPerCellQC() functionality into the new
	perCellQCFilters() function. Repurposed the former to directly
	return a filtered SummarizedExperiment object.

    o   Migrated scran's normalization-related functions into this
	package. Added pooledSizeFactors(), computePooledFactors(),
	cleanSizeFactors() and computeSpikeFactors().

    o   Added transform="asinh" to normalizeCounts() and
	logNormCounts() for inverse hyperbolic transformations of
	CITE-seq data.

    o   Modified isOutlier() to now return outlier.filter objects.
	These are simply logical vectors that preseve the "thresholds"
	attribute upon subsetting.

    o   Migrated correctGroupSummary() from scater, to compute
	corrected versions of group-level summary statistics.

                        Changes in version 1.0.0                        

    o   Split off scuttle from scater by migrating all
	non-visualization code from the latter.

    o   Began transition to dot-separate argument names from original
	snake case format.

    o   Added a geometricSizeFactors() function, deprecated
	geometric=TRUE in librarySizeFactors().

    o   Single-object downsampling in downsampleBatches() now behaves
	more consistently with multi-object downsampling.