DICE: Cell lineage reconstruction from single-cell CNA data
DICE (short for Distance-based Inference of Copy-number Evolution) is a collection of fast and accurate methods for reconstructing cell lineage trees from single-cell copy number aberration data. Most notable among these methods are DICE-star and DICE-bar, which use standard-root and breakpoint-root distances, respectively, and reconstruct the phylogeny using a balanced minimum evolution criteria. DICE-star and DICE-bar have both been found to be generally more accurate and far more scalable than other, more complex, model-based approaches for reconstructing cell lineage trees from single-cell somatic copy number alteration data. Both approaches, along with several variants, are implemented in a single Python file, DICE.py, and can be easily run using a python interpreter.
DICE.py is written in Python and requires the Python packages numpy and pandas. DICE also requires the fastme package. DICE.py takes as input a single file with the copy number profiles of all cells and outputs the corresponding cell lineage tree. Further technical details appear in the manual and in the paper cited below.
DICE was implemented by Samson Weiner and is available open source under GNU GPL. The latest version of DICE, along with usage instructions and a sample dataset, are available through the GitHub link below:
- GitHub repository for DICE: https://github.com/samsonweiner/DICE
In case you are unable to access the software through GitHub, the software (possibly an older version), user manual, and sample dataset can be downloaded using the links below:
- Software and sample dataset: DICE-main.zip
- User manual: DICE_manual.pdf
The simulated datasets used for evaluating DICE and other related methods can be downloaded from Zenodo using the following link:
- Simulated datasets: https://doi.org/10.5281/zenodo.10108731
This software can be cited as follows:
- DICE: Fast and Accurate Distance-Based Reconstruction of Single-Cell Copy Number Phylogenies
Samson Weiner, Mukul S. Bansal
Under review.
Funding: Development of the software resource(s) available from this webpage was funded in part by U.S. National Science Foundation award IIS 2212511.
Contact: Please feel free to contact Samson Weiner (samson.weiner@uconn.edu) or Mukul Bansal (mukul.bansal@uconn.edu) if you have any questions, concerns, or suggestions.