# 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)](https://www.nature.com/articles/s41467-021-21650-1).
## 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](https://github.com/cbg-ethz/SCITE) 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)
