countland: Analysis of Biological Count Data, Especially from Single-Cell
RNA-Seq
A set of functions for applying a
restricted linear algebra to the analysis of
count-based data. See the accompanying preprint
manuscript: "Normalizing need not be the norm:
count-based math for analyzing single-cell data"
Church et al (2022) <doi:10.1101/2022.06.01.494334>
This tool is specifically designed to analyze
count matrices from single cell RNA sequencing
assays. The tools implement several count-based
approaches for standard steps in single-cell
RNA-seq analysis, including scoring genes and cells,
comparing cells and clustering, calculating differential
gene expression, and several methods for rank
reduction. There are many opportunities for further
optimization that may prove useful in the analysis of
other data. We provide the source code freely
available at <https://github.com/shchurch/countland>
and encourage users and developers to fork the code for
their own purposes.
| Version: |
0.1.1 |
| Imports: |
methods, rlang, Matrix, ggplot2 |
| Suggests: |
tidyverse, viridis, gridExtra, igraph, RSpectra, matrixTests, rdist, stats, Seurat, testthat (≥ 3.0.0) |
| Published: |
2022-08-17 |
| Author: |
Church Samuel H. 
[aut, cre] |
| Maintainer: |
Church Samuel H. <samuelhchurch at gmail.com> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| CRAN checks: |
countland results |
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