runViz: Dimentionality Reduction for Visualization

In r3fang/SnapATAC: Single Nucleus Analysis Package for ATAC-Seq

Dimentionality Reduction for Visualization

Description

Wrapper for the implementation of Barnes-Hut t-Distributed Stochastic Neighbor Embedding and FFT-accelerated Interpolation-based t-SNE (FIt-SNE) t-SNE, and UMAP

Usage

runViz(obj, dims, eigs.dims, method, fast_tsne_path, Y.init, seed.use,
  num.cores, tmp.folder, ...)

Arguments

obj	A snap object.
dims	integer; Output dimensionality (default: 2)
eigs.dims	integer vector; principal components used for running tsne or umap
method	character; A character variable indicates what t-sne method to use ("Rtsne", "fast_tsne", "umap").
fast_tsne_path	character; A character variable indicates the path of the excutable FIt-sen located. Required only when method="fast_tsne"
Y.init	matrix; Initial locations of the objs. If NULL, random initialization will be used (default: NULL). Note that when using this, the initial stage with exaggerated perplexity values and a larger momentum term will be skipped.
seed.use	number; Random seeds to use.
num.cores	number; Number of CPU used for computing.
tmp.folder	Directory to store temporary files.
...	Arguments passed to Rtsne, umap or FIt-tsne

Value

Returns a snap obj with the visulization

Examples

data(demo.sp);
demo.sp = runViz(obj=demo.sp, tmp.folder=tempdir(), eigs.dims=1:5, method="Rtsne");

r3fang/SnapATAC documentation built on March 29, 2022, 4:33 p.m.