permMclustCov | R Documentation |
Function to obtain bayes factor for permutations of one gene's residuals
permMclustCov(y, nperms, C, condition, remove.zeroes = TRUE, log.transf = TRUE, restrict = FALSE, alpha, m0, s0, a0, b0, ref, min.size)
y |
Numeric data vector for one gene |
nperms |
Number of permutations of residuals to evaulate |
C |
Matrix of confounder variables, where there is one row for each sample and one column for each covariate. |
condition |
Vector of condition indicators for each sample |
remove.zeroes |
Logical indicating whether zeroes need to be removed
from |
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
|
Obtains bayes factor numerator for data vector y
representing one gene
Bayes factor numerator for the current permutation
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
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