instantiate_scMinimal

Create an scMinimal object. Generally, this should be done through calling the
make_new_container() wrapper function.

Single-cell Interpretable Tensor Decomposition (scITD) employs the
Tucker tensor decomposition to extract multicell-type gene expression patterns
that vary across donors/individuals. This tool is geared for use with single-cell
RNA-sequencing datasets consisting of many source donors. The method has a wide
range of potential applications, including the study of inter-individual variation
at the population-level, patient sub-grouping/stratification, and the analysis
of sample-level batch effects. Each "multicellular process" that is extracted
consists of (A) a multi cell type gene loadings matrix and (B) a
corresponding donor scores vector indicating the level at which the corresponding
loadings matrix is expressed in each donor. Additional methods are implemented
to aid in selecting an appropriate number of factors and to evaluate stability
of the decomposition. Additional tools are provided for downstream analysis,
including integration of gene set enrichment analysis and ligand-receptor analysis.
Tucker, L.R. (1966) <doi:10.1007/BF02289464>. Unkel, S., Hannachi, A., Trendafilov, N. T., & Jolliffe, I. T. (2011) <doi:10.1007/s13253-011-0055-9>. Zhou, G., & Cichocki, A. (2012) <doi:10.2478/v10175-012-0051-4>.

Jonathan Mitchel

scITD

Single-Cell Interpretable Tensor Decomposition

Evan Biederstedt

Peter Kharchenko

instantiate_scMinimal function

<dl><dt>count_data</dt>
<dd>sparseMatrix Matrix of raw counts with genes as rows
and cells as columns</dd>
<dt>meta_data</dt>
<dd>data.frame Metadata with cells as rows and variables
as columns. Number of rows in metadata should equal number of columns
in count matrix.</dd>
<dt>metadata_cols</dt>
<dd>character The names of the metadata columns to use
(default=NULL)</dd>
<dt>metadata_col_nm</dt>
<dd>character New names for the selected metadata columns
if wish to change their names. If NULL, then the preexisting column names are
used. (default=NULL)</dd></dl>

Arguments

Create an scMinimal object. Generally, this should be done through calling the
make_new_container() wrapper function. — instantiate_scMinimal

<dl>

<dt>count_data</dt>
<dd>sparseMatrix Matrix of raw counts with genes as rows
and cells as columns</dd>


<dt>meta_data</dt>
<dd>data.frame Metadata with cells as rows and variables
as columns. Number of rows in metadata should equal number of columns
in count matrix.</dd>


<dt>metadata_cols</dt>
<dd>character The names of the metadata columns to use
(default=NULL)</dd>


<dt>metadata_col_nm</dt>
<dd>character New names for the selected metadata columns
if wish to change their names. If NULL, then the preexisting column names are
used. (default=NULL)</dd>

</dl>

instantiate_scMinimal: Create an scMinimal object. Generally, this should be done through calling the make_new_container() wrapper function.

Description

Usage

Value

Arguments

Examples