CatKernel: Categorical Kernel function

In rikenbit/fuchikoma: Revealing differentially expressed genes using nonlinear dimensionality reduction for single cell RNA-Seq data

Description

CatKernel calculate gram matrix by using label information (e.g., cell label or sample label such as c(1,1,1,2,2,2,3,3)).

Usage

CatKernel(label, type = c("simple", "two", "one_vs_rest", "each"))

Arguments

label	Label vector descrbing which cells are sample cell type and which cells are different (e.g., c(1,1,1,2,2,2,3,3) (default:simple)).
type	Categorical kernel functions. simple could be specified even the number of class is two or more. When the number of class is two, only two parameter is accessible. When the number of class is three or more, one_vs_rest and each is accessible.

Value

A data frame is returned.

Author(s)

Koki Tsuyuzaki, Haruka Ozaki, Mika Yoshimura, Itoshi Nikaido

Maintainer: Koki Tsuyuzaki <[e-mail]>

References

Le Song et al. (2007) Gene selection via the BAHSIC family of algorithms, Bioinformatics, 23(13), i490-i498

Y-h Taguchi et al. (2015) Principal component analysis-based unsupervised feature extraction applied to in silico drug discovery for posttraumatic stress disorder-mediated heart disease, BMC Bioinformatics, 16(139)

Examples

data(label.MARS)
L <- CatKernel(label.MARS)
dim(L)

rikenbit/fuchikoma documentation built on May 27, 2019, 9:09 a.m.