permMclustGene: permMclustGene

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

permMclustGene

Description

Function to obtain bayes factor for all permutations of one gene (not parallelized; to be used when parallelizing over Genes)

Usage

permMclustGene(y, adjust.perms, nperms, condition, remove.zeroes = TRUE,
  log.transf = TRUE, restrict = TRUE, alpha, m0, s0, a0, b0, C, ref,
  min.size)

Arguments

y	Numeric data vector for one gene
adjust.perms	Logical indicating whether or not to adjust the permutation tests for the sample detection rate (proportion of nonzero values). If true, the residuals of a linear model adjusted for detection rate are permuted, and new fitted values are obtained using these residuals.
nperms	Number of permutations of residuals to evaulate
condition	A character object that contains the name of the column in colData that represents the biological group or condition of interest (e.g. treatment versus control). Note that this variable should only contain two possible values since scDD can currently only handle two-group comparisons. The default option assumes that there is a column named "condition" that contains this variable.
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
C	Matrix of confounder variables, where there is one row for each sample and one column for each covariate.
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 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

kdkorthauer/scDD documentation built on March 27, 2022, 5:11 a.m.