group_cell

Group cells according to subject IDs

A fast negative binomial mixed model for conducting association analysis of multi-subject single-cell data. It can be used for identifying marker genes, differential expression and co-expression analyses. The model includes subject-level random effects to account for the hierarchical structure in multi-subject single-cell data. See He et al. (2021) <doi:10.1038/s42003-021-02146-6>.

Liang He

nebula

Negative Binomial Mixed Models Using Large-Sample Approximation
for Differential Expression Analysis of ScRNA-Seq Data

Raghav Sharma

group_cell function

<dl><dt>count</dt>
<dd>A raw count matrix of the single-cell data. The rows are the genes, and the columns are the cells. The matrix can be a matrix object or a sparse dgCMatrix object.</dd>
<dt>id</dt>
<dd>A vector of subject IDs. The length should be the same as the number of columns of the count matrix.</dd>
<dt>pred</dt>
<dd>A design matrix of the predictors. The rows are the cells and the columns are the predictors. If not specified, an intercept column will be generated by default.</dd>
<dt>offset</dt>
<dd>A vector of the scaling factor. The values must be strictly positive. If not specified, a vector of all ones will be generated by default.</dd></dl>

Arguments

Group cells according to subject IDs — group_cell

<dl>

<dt>count</dt>
<dd>A raw count matrix of the single-cell data. The rows are the genes, and the columns are the cells. The matrix can be a matrix object or a sparse dgCMatrix object.</dd>


<dt>id</dt>
<dd>A vector of subject IDs. The length should be the same as the number of columns of the count matrix.</dd>


<dt>pred</dt>
<dd>A design matrix of the predictors. The rows are the cells and the columns are the predictors. If not specified, an intercept column will be generated by default.</dd>


<dt>offset</dt>
<dd>A vector of the scaling factor. The values must be strictly positive. If not specified, a vector of all ones will be generated by default.</dd>

</dl>

group_cell: Group cells according to subject IDs

Description

Usage

Value

Arguments

Examples