runSCANORAMA {singleCellTK} | R Documentation

## Apply the mutual nearest neighbors (MNN) batch effect correction method to SingleCellExperiment object

### Description

SCANORAMA is analogous to computer vision algorithms for panorama stitching that identify images with overlapping content and merge these into a larger panorama.

### Usage

    runSCANORAMA(
      inSCE,
      useAssay = "logcounts",
      batch = "batch",
      SIGMA = 15,
      ALPHA = 0.1,
      KNN = 20L,
      assayName = "SCANORAMA"
    )

### Arguments

`inSCE` | SingleCellExperiment inherited object. Required.
`useAssay` | A single character indicating the name of the assay requiring batch correction. Scanorama requires a transformed normalized expression assay. Default `"logcounts"`.
`batch` | A single character indicating a field in `colData` that annotates the batches. Default `"batch"`.
`SIGMA` | A numeric scalar. Algorithmic parameter, correction smoothing parameter on Gaussian kernel. Default `15`.
`ALPHA` | A numeric scalar. Algorithmic parameter, alignment score minimum cutoff. Default `0.1`.
`KNN` | An integer. Algorithmic parameter, number of nearest neighbors to use for matching. Default `20L`.
`assayName` | A single characeter. The name for the corrected assay. Will be saved to `assay`. Default `"SCANORAMA"`.

### Value

The input SingleCellExperiment object with `assay(inSCE, assayName)` updated.

### References

Brian Hie et al, 2019

### Examples

    ## Not run:
    data('sceBatches', package = 'singleCellTK')
    sceBatches <- scaterlogNormCounts(sceBatches)
    sceCorr <- runSCANORAMA(sceBatches, "ScaterLogNormCounts")

    ## End(Not run)

[Package singleCellTK version 2.2.0 Index]