cytof_dimReduction {cytofkit} | R Documentation

## Dimension reduction for high dimension data

### Description

Apply dimension reduction on the cytof expression data, with method `pca`, `tsne`, `diffusionmap` or `isomap`.

### Usage

    cytof_dimReduction(data, markers = NULL, method = c("tsne", "pca", "isomap",
      "diffusionmap", "NULL"), distMethod = "euclidean", out_dim = 2,
      tsneSeed = 42, isomap_k = 5, isomap_ndim = NULL,
      isomapFragmentOK = TRUE, ...)

### Arguments

`data` | Input expression data matrix.
`markers` | Selected markers for dimension reduction, either marker names/descriptions or marker IDs.
`method` | Method chosen for dimensition reduction, must be one of `isomap`, `pca` , `diffusionmap` or `tsne`.
`distMethod` | Method for distance calcualtion, default is "euclidean", other choices like "manhattan", "cosine", "rankcor"....
`out_dim` | The dimensionality of the output.
`tsneSeed` | Set a seed if you want reproducible t-SNE results.
`isomap_k` | Number of shortest dissimilarities retained for a point, parameter for `isomap` method.
`isomap_ndim` | Number of axes in metric scaling, parameter for `isomap` method.
`isomapFragmentOK` | What to do if dissimilarity matrix is fragmented, parameter for `isomap` method.
`...` | Other parameters passed to the method, check `Rtsne`, `DiffusionMap`, `isomap`.

### Value

A matrix of the dimension reduced data, with colnames method_ID, and rownames same as the input data.

### Note

Currently, `diffusionmap` will not work with R 3.4.0, due to an issue with the latest CRAN release of its dependency `igraph` If this is the case, consider manually updating `igraph` using; `install.packages("https://github.com/igraph/rigraph/releases/download/v1.1.0/igraph_1.1.0.zip", repos=NULL, method="libcurl")`

### Examples

    data(iris)
    in_data <- iris[, 1:4]
    markers <- colnames(in_data[, 1:4])
    out_data <- cytof_dimReduction(in_data, markers = markers, method = "tsne")

[Package cytofkit version 1.12.0 Index]