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README.Rmd
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README.Rmd
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---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# evoverse <img src='man/figures/logo.png' align="right" height="139" />
<!-- badges: start -->
[](https://travis-ci.org/caravagn/evoverse)
[](https://caravagn.github.io/evoverse)
<!-- badges: end -->
The `evoverse` collects multiple R packages to implement Cancer Evolution analyses on cancer bulk sequencing data, which can be used to reconcile tumour heterogeneity (TH).
With the `evoverse` functions you can study TH across patients (inter-patient heterogeneity), or within a patient (intra-tumour heterogeneity).
#### Features
* functions to QC somatic calls (mutation and copy number segments) for a Cancer Evolution analysis;
* functions to determine subclonal architectures integrating both Population Genetics and Machine Learning (model based subclonal deconvolution);
* determine repeated evolution across patients, comparing tumours for their evolutionary trajectories (repeated evolutionary trajectories).
[](https://caravagn.github.io/evoverse/articles/pipelines.html)
[](https://caravagn.github.io/evoverse/articles/packages.html)
#### Help and support
[](https://caravagn.github.io/evoverse)
-----
### Installation
You can install the released version of `evoverse` from
[GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("caravagn/evoverse")
```
-----
#### Copyright and contacts
Giulio Caravagna, PhD. _Institute of Cancer Research, London, UK_.
[](mailto:gcaravagn@gmail.com)
[](https://github.com/caravagn)
[](https://twitter.com/gcaravagna)
[](https://sites.google.com/site/giuliocaravagna/)