Name Mode Size
R 040000
data 040000
inst 040000
man 040000
src 040000
tests 040000
vignettes 040000
DESCRIPTION 100644 1 kb
NAMESPACE 100755 1 kb
NEWS 100644 0 kb 100755 2 kb
# mitoClone2 <img src='man/figures/logo.png' align="right" height="139" /> The R package is used for performing the analysis of clonal heterogeneity based on nuclear and mitochondrial mutations in single cell RNA or DNA sequencing. It is a new and improved version of the package, mitoClone, originally described by [Velten et al. (2021)]( ## 1. System Requirements: - Linux/Mac - R 4.0+ - SCITE/PhISCS - Python 2.7, 3.6, or 3.7 (optional) - Gurobi 9.0.0+ (optional) Importantly, depending on the user's need for tree-building, an installation of PhiSCS may be necessary. For SCITE, the program should be installed automatically when the mitoClone2 package is installed. Please read the manual provided by the software authors [SCITE Installation Instructions]( to better understand the software. See **DESCRIPTION** file for specific R package requirements. The software has been successfully implemented and tested using: Python 3.6.5, R 4.0.0, and Gurobi 9.0.3 on CentOS 7. ## 2. Installation For manual package installation use the command: ``` r ## install via Bioconductor if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install('mitoClone2') ## use devtools to install ##devtools::install_github("benstory/mitoClone2") ``` Estimated installation time: < 1 hour* ## 3. Demo Please see R vignettes for further instructions and a demo using real data. Use the command `vignette("mitoClone2")` after loading the library (see Instructions) to list all available tutorials. Estimated demo completion time: < 1 hour ## 4. Usage Instructions After installing all dependencies, open an R session and load the library using the following command: ``` r library(mitoClone2) ``` *Notes:* Please make sure to set your environmental python variables correctly for use of gurobi. See for example the `python_env` parameter. Again please view the R vignettes for usage possibilities. - **overview**: Instructions on how to filter mitochondrial mutations using either a list of sites to be excluded or shared mutations across samples/patients (typical runtime: > 10 minutes) - **clustering**: Instructions on how to cluster mutations into a clonal hierarchy and how to assign cells to clones (typical runtime: < 1 hour)