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README.Rmd
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---
title: "MOBSTER: Source Data"
author: "Giulio Caravagna"
date: "24/5/2020"
output:
github_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
require(tidyverse)
```
---
<center>
<a href="https://caravagn.github.io/mobster"><img src="https://caravagn.github.io/mobster/reference/figures/logo.png" width=77px height=91px></img></a>
<a href="https://caravagn.github.io/VIBER"><img src="https://caravagn.github.io/VIBER/reference/figures/logo.png" width=77px height=91px></img></a>
<a href="https://caravagn.github.io/BMix"><img src="https://caravagn.github.io/BMix/reference/figures/logo.png" width=77px height=91px></img></a>
<a href="https://caravagn.github.io/CNAqc"><img src="https://caravagn.github.io/CNAqc/reference/figures/logo.png" width=77px height=91px></img></a>
<a href="https://t-heide.github.io/TEMULATOR"><img src="https://t-heide.github.io/TEMULATOR/reference/figures/logo.png" width=77px height=91px></img></a>
</center>
---
This is the material released with the paper:
* _Subclonal reconstruction of tumors using machine learning and population genetics_. Giulio Caravagna, Timon Heide, Marc Williams, Luis Zapata, Daniel Nichol, Ketevan Chkhaidze, William Cross, George D. Cresswell, Benjamin Werner, Ahmet Acar, Chris P. Barnes, Guido Sanguinetti, Trevor A. Graham, Andrea Sottoriva. Nature Genetics, 2020 (to appear).
The following R packages are required to run the analyses.
* [MOBSTER](https://caravagn.github.io/mobster), to cluster the tumour site frequency spectrum with Beta and Pareto distributions;
* [BMix](https://caravagn.github.io/BMix) and [VIBER](https://caravagn.github.io/VIBER), to model read counts data with Binomial mixtures;
* [CNAqc](https://caravagn.github.io/CNAqc), to integrate mutation and copy number data from bulk sequencing;
* [TEMULATOR](https://t-heide.github.io/TEMULATOR/), to simulated non-spatial tumour growth dynamics;
* [CHESS](https://github.com/sottorivalab/CHESS.cpp), to simulated spatial tumour growth dynamics;
---
The vignettes are rendered in HTML. To visualise them correctly it is best to open the HTML files locally with your browser. As an alternative, you can [use a preview website](https://htmlpreview.github.io/).
**Note** that vignettes 6 and 7 use `DT` tables ad cannot be rendered by the preview website.
* [MOBSTER](https://caravagn.github.io/mobster) (version `0.1.1`) installable sources are available in folder `R_package`.
```
install.packages("./R_package/mobster_0.1.1.tar.gz, repos = NULL, type = 'sources', dependencies = TRUE)
```
**1. [Example subclonal dynamics](https://caravagn.github.io/mobster/articles/Example_tumour_simulation.html).**
Simulated example of tumour subclonal evolution with snapshots of tumour
dynamics at different timepoints, and MOBSTER analysis (hosted at [MOBSTER](https://caravagn.github.io/mobster) website).
**2. [Simulated single-sample data analysis](http://htmlpreview.github.io/?https://github.com/caravagn/mobster_supp_data/blob/master/Tumor_sim_nospace/Simulated_onesample.html).** `n = 150` cases with `0` or `1` subclone, with simulated WGS at median coverage 120x. Mutation calls are simulated without copy num data; the coverage is Poisson-distributed.
**3. [Simulated multi-sample data analysis](http://htmlpreview.github.io/?https://github.com/caravagn/mobster_supp_data/blob/master/Tumor_sim_space/Simulated_multisample.html).** `n = 15` cases of spatially growing tumours (2D) with `0`, `1` or `2` subclones, with simulated WGS at median coverage 120x. Mutation calls are simulated without copy num data; the coverage is Poisson-distributed.
**4. [Single-sample cross-sectional lung cases](http://htmlpreview.github.io/?https://github.com/caravagn/mobster_supp_data/blob/master/Lungs/Real_data_lungs.html).** `n = 2` lung cancer cases with `0` subclones, with WGS at median coverage ~100x. Mutation calls are and copy num data are available from the [COALA](http://genome.kaist.ac.kr/). Code in this vignette can be used also to re-analyse the breast and AML case samples that we discuss in the paper (see the papers for data availability).
**5. [Multi-region cross-sectional colorectal carcinomas](http://htmlpreview.github.io/?https://github.com/caravagn/mobster_supp_data/blob/master/CRC/CRC_vignette.html).** 2 colorectal cancer cases with multiple biopsies each, with WGS at median coverage ~100x. These are new data first released with this paper. Code in this vignette can be used also to replicate the results that we discuss in the paper; a further vignette is available to [replicate Supplementary Figures](http://htmlpreview.github.io/?https://github.com/caravagn/mobster_supp_data/blob/master/CRC/CRC_vignette_SM.html).
**6. [PCAWG analysis](http://htmlpreview.github.io/?https://github.com/caravagn/mobster_supp_data/blob/master/PCAWG/PCAWG_analysis_table.html).** Summary statistics for `n = 2566` cases of different cancers (pan-cancer). This cohort has WGS single-samples with coverage ~45x. Mutation and copy number calls that we used have been generated by the PCAWG consortium.
**7. [GBM analysis](http://htmlpreview.github.io/?https://github.com/caravagn/mobster_supp_data/blob/master/GBM/GBM_analysis_table.html).** Summary statistics for `n = 71` longitudinal GBM biopsies This cohort has WGS primary/ relapse samples with coverage ~100x. Mutation and copy number calls that we used have been generated by the orugunal authors
---
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/)