bbknn: Run bbknn clustering algorithm

In TomKellyGenetics/bbknn: R implementation of the BBKNN package

Description

Implements the bbknn clustering algorithm in R using reticulate to run the Python version. Requires the python "bbknn" and "igraph" modules to be installed. Returns a vector of partition indices.

Usage

bbknn(data_matrix, batch, pca = TRUE, compute_pca = "python",
  nPcs = NULL)

Arguments

data_matrix	A matrix (genes x samples or cells) for expression data
batch	An integer vector of batches to correct for (converts factors or numeric vectors)
pca	whether to compute pca (defaults to TRUE) or apply correction to the raw matrix (FALSE)
compute_pca	whether to compute PCA in Python (defaults to TRUE, requires scanpy library) or with R functions (FALSE)
nPcs	number of principal components to compute (defaults to 50 if more than 50 genes)

Value

returns a list with the following components

corrected matrix	matrix of data corrected by the BBKNN (batch based K nearest neighbours)
pca	principal components(matrix with row for every sample and column for each component)
tsne	t-distributed stochastic neighbour embedding (matrix with row for every sample)
umap	uniform manifold approximation and projection (matrix with row for every sample)

TomKellyGenetics/bbknn documentation built on Sept. 23, 2019, 3:07 p.m.