permMclust: permMclust

In scDD: Mixture modeling of single-cell RNA-seq data to identify genes with differential distributions

Description

Function to obtain bayes factor numerator for permutations of one gene

Usage

permMclust(y, nperms, condition, remove.zeroes = TRUE, log.transf = TRUE,
  restrict = FALSE, alpha, m0, s0, a0, b0, ref, min.size)

Arguments

y	Numeric data vector for one gene
nperms	Number of permutations of residuals to evaulate
condition	Vector of condition indicators for each sample
remove.zeroes	Logical indicating whether zeroes need to be removed from y
log.transf	Logical indicating whether the data is in the raw scale (if so, will be log-transformed)
restrict	Logical indicating whether to perform restricted Mclust clustering where close-together clusters are joined.
alpha	Value for the Dirichlet concentration parameter
m0	Prior mean value for generating distribution of cluster means
s0	Prior precision value for generating distribution of cluster means
a0	Prior shape parameter value for the generating distribution of cluster precision
b0	Prior scale parameter value for the generating distribution of cluster precision
ref	one of two possible values in condition; represents the referent category.
min.size	a positive integer that specifies the minimum size of a cluster (number of cells) for it to be used during the classification step. Any clusters containing fewer than min.size cells will be considered an outlier cluster and ignored in the classfication algorithm. The default value is three.

Details

Obtains bayes factor numerator for data vector y representing one gene

Value

Bayes factor numerator for the current permutation

References

Korthauer KD, Chu LF, Newton MA, Li Y, Thomson J, Stewart R, Kendziorski C. A statistical approach for identifying differential distributions in single-cell RNA-seq experiments. Genome Biology. 2016 Oct 25;17(1):222. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-1077-y

scDD documentation built on Nov. 8, 2020, 7:10 p.m.