README.md

In benstory/mitoClone2: Clonal Population Identification in Single-Cell RNA-Seq Data using Mitochondrial and Somatic Mutations

mitoClone2

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:

## 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:

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)

benstory/mitoClone2 documentation built on Nov. 8, 2023, 12:13 a.m.