run.mnn: Run MNN alignment on the main data.
In iCellR: Analyzing High-Throughput Single Cell Sequencing Data

This function takes an object of class iCellR and runs MNN alignment. It's a wrapper for scran.

run.mnn(
  x = NULL,
  method = "base.mean.rank",
  top.rank = 500,
  gene.list = "character",
  data.type = "main",
  k = 20,
  cos.norm = TRUE,
  ndist = 3,
  d = 50,
  approximate = FALSE,
  irlba.args = list(),
  subset.row = NULL,
  auto.order = FALSE,
  pc.input = FALSE,
  compute.variances = FALSE,
  assay.type = "logcounts",
  get.spikes = FALSE,
  BNPARAM = NULL,
  BPPARAM = SerialParam()
)

`x`	An object of class iCellR.
`method`	Choose from "base.mean.rank" or "gene.model", default is "base.mean.rank". If gene.model is chosen you need to provide gene.list.
`top.rank`	A number taking the top genes ranked by base mean, default = 500.
`gene.list`	A charactor vector of genes to be used for PCA. If "clust.method" is set to "gene.model", default = "my_model_genes.txt".
`data.type`	Choose from "main" and "imputed", default = "main"
`k`	An integer scalar specifying the number of nearest neighbors to consider when identifying MNNs.
`cos.norm`	A logical scalar indicating whether cosine normalization should be performed on the input data prior to calculating distances between cells.
`ndist`	A numeric scalar specifying the threshold beyond which neighbours are to be ignored when computing correction vectors. Each threshold is defined in terms of the number of median distances.
`d`	Number of dimentions to pass to ‘multiBatchPCA’.
`approximate`	Further arguments to pass to ‘multiBatchPCA’. Setting ‘approximate=TRUE’ is recommended for large data sets with many cells.
`irlba.args`	Further arguments to pass to ‘multiBatchPCA’. Setting ‘approximate=TRUE’ is recommended for large data sets with many cells.
`subset.row`	See ‘?"scran-gene-selection"’.
`auto.order`	Logical scalar indicating whether re-ordering of batches should be performed to maximize the number of MNN pairs at each step. Alternatively an integer vector containing a permutation of ‘1:N’ where ‘N’ is the number of batches.
`pc.input`	Logical scalar indicating whether the values in ‘...’ are already low-dimensional, e.g., the output of ‘multiBatchPCA’.
`compute.variances`	Logical scalar indicating whether the percentage of variance lost due to non-orthogonality should be computed.
`assay.type`	A string or integer scalar specifying the assay containing the expression values, if SingleCellExperiment objects are present in ‘...’.
`get.spikes`	See ‘?"scran-gene-selection"’. Only relevant if ‘...’ contains SingleCellExperiment objects.
`BNPARAM`	A BiocNeighborParam object specifying the nearest neighbor algorithm. Defaults to an exact algorithm if ‘NULL’, see ‘?findKNN’ for more details.
`BPPARAM`	A BiocParallelParam object specifying whether the PCA and nearest-neighbor searches should be parallelized.