addUMAP: Add a UMAP embedding of a reduced dimensions object to an...
In haibol2016/ArchR_debug: Analyzing single-cell regulatory chromatin in R.

addUMAP

R Documentation

Add a UMAP embedding of a reduced dimensions object to an ArchRProject

Description

This function will compute a UMAP embedding and add it to an ArchRProject.

Usage

addUMAP(
  ArchRProj = NULL,
  reducedDims = "IterativeLSI",
  name = "UMAP",
  nNeighbors = 40,
  minDist = 0.4,
  metric = "cosine",
  dimsToUse = NULL,
  scaleDims = NULL,
  corCutOff = 0.75,
  sampleCells = NULL,
  outlierQuantile = 0.9,
  saveModel = TRUE,
  verbose = TRUE,
  seed = 1,
  force = FALSE,
  threads = 1,
  ...
)

Arguments

`ArchRProj`	An `ArchRProject` object.
`reducedDims`	The name of the `reducedDims` object (i.e. "IterativeLSI") to use from the designated `ArchRProject`.
`name`	The name for the UMAP embedding to store in the given `ArchRProject` object.
`nNeighbors`	An integer describing the number of nearest neighbors to compute a UMAP. This argument is passed to `n_neighbors` in `uwot::umap()`.
`minDist`	A number that determines how tightly the UMAP is allowed to pack points together. This argument is passed to `min_dist` in `uwot::umap()`. For more info on this see https://jlmelville.github.io/uwot/abparams.html.
`metric`	A number that determines how distance is computed in the `reducedDims` to compute a UMAP. This argument is passed to `metric` in `uwot::umap()`.
`dimsToUse`	A vector containing the dimensions from the `reducedDims` object to use in computing the embedding.
`scaleDims`	A boolean value that indicates whether to z-score the reduced dimensions for each cell. This is useful for minimizing the contribution of strong biases (dominating early PCs) and lowly abundant populations. However, this may lead to stronger sample-specific biases since it is over-weighting latent PCs. If set to `NULL` this will scale the dimensions based on the value of `scaleDims` when the `reducedDims` were originally created during dimensionality reduction. This idea was introduced by Timothy Stuart.
`corCutOff`	A numeric cutoff for the correlation of each dimension to the sequencing depth. If the dimension has a correlation to sequencing depth that is greater than the `corCutOff`, it will be excluded from analysis.
`sampleCells`	An integer specifying the number of cells to subsample and perform UMAP Embedding on. The remaining cells that were not subsampled will be re-projected using uwot::umap_transform to the UMAP Embedding. This enables a decrease in run time and memory but can lower the overal quality of the UMAP Embedding. Only recommended for extremely large number of cells.
`outlierQuantile`	A numeric (0 to 1) describing the distance quantile in the subsampled cels (see `sampleCells`) to use to filter poor quality re-projections. This is necessary because there are lots of outliers if undersampled significantly.
`saveModel`	A boolean value indicating whether or not to save the UMAP model in an RDS file for downstream usage such as projection of data into the UMAP embedding.
`verbose`	A boolean value that indicates whether printing UMAP output.
`seed`	A number to be used as the seed for random number generation. It is recommended to keep track of the seed used so that you can reproduce results downstream.
`force`	A boolean value that indicates whether to overwrite the relevant data in the `ArchRProject` object if the embedding indicated by `name` already exists.
`threads`	The number of threads to be used for parallel computing. Default set to 1 because if set to high can cause C stack usage errors.
`...`	Additional parameters to pass to `uwot::umap()`