https://github.com/karchinlab/pictograph
A Bayesian hierarchical model to build tumor evolutionary trees
https://github.com/karchinlab/pictograph
Last synced: 3 months ago
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A Bayesian hierarchical model to build tumor evolutionary trees
- Host: GitHub
- URL: https://github.com/karchinlab/pictograph
- Owner: KarchinLab
- Created: 2019-05-09T21:13:46.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2024-10-21T17:58:43.000Z (over 1 year ago)
- Last Synced: 2024-10-22T08:47:10.684Z (over 1 year ago)
- Language: R
- Homepage:
- Size: 609 MB
- Stars: 5
- Watchers: 10
- Forks: 0
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
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README
# PICTograph
PICTograph is a computational tool developed to infer the clonal evolution of tumors from multi-region sequencing data. It models uncertainty in assigning mutations to subclones using a Bayesian hierarchical model and reduces the space of possible evolutionary trees by using constraints based on principles of sample-presence, lineage precedence, and sum condition. Highly probable evolutionary relationships that are recovered in multiple models can be highlighted using ensemble-based visualizations.
## Installation
PICTograph uses the JAGS library for Bayesian data analysis, which is installed outside of R. JAGS can be downloaded and installed for your OS [here](https://mcmc-jags.sourceforge.io/).
To install PICTograph from GitHub, start R and enter:
```
devtools::install_github("KarchinLab/pictograph", build_vignettes = TRUE)
```
## Tutorial
Demo code on a toy example can be found in the vignette:
```
library(pictograph)
vignette("pictograph", package = "pictograph")
```