compare_decompositions

Plot a pairwise comparison of factors from two separate decompositions

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

compare_decompositions function

<dl><dt>tucker_res1</dt>
<dd>list The container$tucker_res from first decomposition</dd>
<dt>tucker_res2</dt>
<dd>list The container$tucker_res from first decomposition</dd>
<dt>decomp_names</dt>
<dd>character Names of the two decompositions that will go
on the axes of the heatmap</dd>
<dt>meta_anno1</dt>
<dd>matrix The result of calling get_meta_associations()
corresponding to the first decomposition, which is stored in
container$meta_associations (default=NULL)</dd>
<dt>meta_anno2</dt>
<dd>matrix The result of calling get_meta_associations()
corresponding to the second decomposition, which is stored in
container$meta_associations (default=NULL)</dd>
<dt>use_text</dt>
<dd>logical If TRUE, then displays correlation coefficients in cells
(default=TRUE)</dd></dl>

Arguments

Plot a pairwise comparison of factors from two separate decompositions — compare_decompositions

<dl>

<dt>tucker_res1</dt>
<dd>list The container$tucker_res from first decomposition</dd>


<dt>tucker_res2</dt>
<dd>list The container$tucker_res from first decomposition</dd>


<dt>decomp_names</dt>
<dd>character Names of the two decompositions that will go
on the axes of the heatmap</dd>


<dt>meta_anno1</dt>
<dd>matrix The result of calling get_meta_associations()
corresponding to the first decomposition, which is stored in
container$meta_associations (default=NULL)</dd>


<dt>meta_anno2</dt>
<dd>matrix The result of calling get_meta_associations()
corresponding to the second decomposition, which is stored in
container$meta_associations (default=NULL)</dd>


<dt>use_text</dt>
<dd>logical If TRUE, then displays correlation coefficients in cells
(default=TRUE)</dd>

</dl>

compare_decompositions: Plot a pairwise comparison of factors from two separate decompositions

Description

Usage

Value

Arguments

Examples