Changes in version 1.16.0                        

    o   Bugfix to rownames of mnnCorrect() output when using
	correct.all=TRUE with subset.row=.

                        Changes in version 1.8.0                        

    o   Migrate findMutualNN() to BiocNeighbors.

    o   Support d=NA in multiBatchPCA() for more convenient disabling
	of PCA in calling functions.

    o   Bugfix for d=NA with specified subset.row= in fastMNN().

    o   Added the applyMultiSCE() function to easily apply functions
	across main/alternative Experiments from multiple
	SingleCellExperiment inputs.

    o   Added the mnnDeltaVariance() function to compute diagnostics
	from the variances of the differences between MNN pairs.

    o   Added the quickCorrect() function to quickly perform
	intersection, normalization, feature selection and correction.

    o   Added some clustering-based diagnostics (clusterAbundanceVar(),
	clusterAbundanceTest() and compareMergedClusters()) from the
	OSCA book.

    o   File-backed matrices are now realized into memory prior to
	multiBatchPCA().

                        Changes in version 1.6.0                        

    o   Allow regressBatches() to operate without batch= when design=
	is provided. Added d= and related options to conveniently
	perform a PCA on the ResidualMatrix.

    o   Added correct.all= option to all correction functions for
	consistency.

    o   Added a deferred=TRUE default to multiBatchPCA and its callers,
	to encourage use of deferred matrix multiplication for speed.

    o   Switched default PCA algorithm in multiBatchPCA to IrlbaParam.

    o   Added add.single= mode for endomorphic addition of correction
	results in correctExperiments().

                        Changes in version 1.4.0                        

    o   Support the use of arbitrary design matrices in
	regressBatches().

    o   Allow lists of objects to be directly passed into the ... for
	many functions.

    o   Added the clusterMNN() function for performing MNN on cluster
	centroids.

    o   Added get.variance= option to fastMNN() to return variance
	explained from PCA. Support d=NA to skip the PCA step
	altogether.

    o   Modified correctExperiments() to preserve non-conflicting
	rowData() fields.

                        Changes in version 1.2.0                        

    o   Deprecated rotate.all= in favour of get.all.genes= in
	multiBatchPCA().

    o   Switched BSPARAM= to use IrlbaParam(deferred=TRUE) by default
	in fastMNN(), so that the default behaviour is actually fast.

    o   Deprecated auto.order= in favor of merge.order= and auto.merge=
	in fastMNN() and mnnCorrect(). Automatic merging now detects
	potential tree-based merges. Merge trees can also be specified
	as input.

    o   Added the correctExperiments() function to cbind the original
	assays alongside the merged values.

    o   Added the subset.row= argument to cosineNorm() for in-place
	subsetting.

    o   Added batch= and preserve.single= arguments to
	multiBatchNorm(). Standardized behavior of subset.row= by
	adding a normalize.all= argument.

    o   Added the regressBatches() function for correction via standard
	linear regression.

    o   Added the prop.k= argument in all MNN-related functions, to
	allow the value of k to adapt asymmetrically to the size of
	each batch.

                        Changes in version 1.0.0                        

    o   
	New package batchelor, for batch correction of single-cell (RNA
	sequencing) data.