https://github.com/soedinglab/bamm-benchmark
Scripts and data for generating the benchmarks in the W Ge, et al. paper.
https://github.com/soedinglab/bamm-benchmark
Last synced: 11 months ago
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Scripts and data for generating the benchmarks in the W Ge, et al. paper.
- Host: GitHub
- URL: https://github.com/soedinglab/bamm-benchmark
- Owner: soedinglab
- License: agpl-3.0
- Created: 2020-07-03T16:59:05.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2020-07-13T09:35:41.000Z (almost 6 years ago)
- Last Synced: 2025-02-26T14:16:13.498Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 11.4 MB
- Stars: 0
- Watchers: 7
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# About BaMM benchmark repository
This repository stores the scripts and data for generating the results in the W Ge, et al. paper (DOI: https://doi.org/10.1101/2020.07.12.197053).
# Installing
## 1. Clone this repository
git clone https://github.com/soedinglab/BaMM_benchmark
cd BaMM_benchmark
## 2. (optional) Download the pre-processed data from our cluster
Bash scripts:
mkdir -p data/raw
curl -o data/raw/ENCODE.zip http://wwwuser.gwdg.de/~compbiol/bamm/benchmark/ENCODE.zip
curl -o data/raw/HTSELEX.zip http://wwwuser.gwdg.de/~compbiol/bamm/benchmark/HTSELEX.zip
# unzip files
unzip data/raw/ENCODE.zip -d data/raw/ENCODE/
unzip data/raw/HTSELEX.zip -d data/raw/HTSELEX/
# download data for CTCF analysis (data size: 320G)
curl -o data/processed/CTCF.zip http://wwwuser.gwdg.de/~compbiol/bamm/benchmark/CTCF/
unzip data/processed/CTCF.zip -d data/processed/CTCF/
## 3. Prerequisites for installing BaMMmotif2
To compile from source code, you need:
* [GCC](https://gcc.gnu.org/) compiler 4.7 or later (we suggest GCC-5.x)
* [CMake](http://cmake.org/) 2.8.11 or later
C++ packages
* [Boost](http://www.boost.org/)
R and several R packages
* [R](https://cran.r-project.org/) 2.14.1 or later
Download R packages by running:
Rscript ./script/install_packages.R
## 4. Install tools
#### I. Install the fast seeding program PEnGmotif
[PEnG-motif](https://github.com/soedinglab/PEnG-motif)
#### II. Install the refinement program BaMMmotif2
[BaMMmotif2](https://github.com/soedinglab/BaMMmotif2)
#### III. Other tools that are included in this benchmark:
* [MEME](http://meme-suite.org/doc/download.html), version 5.1.1
* [CisFinder](https://lgsun.grc.nia.nih.gov/CisFinder/download.html)
* [ChIPMunk](http://autosome.ru/ChIPMunk/), version 8
* [di-ChIPMunk](http://autosome.ru/ChIPMunk/), version 8
* [InMoDe](http://www.jstacs.de/index.php/InMoDe)
## 5. Edit paths
Edit paths in this path file `./script/bench/paths.cluster.sh`
## 6. Submit jobs to the cluster
./script/bench/start_benchmark.slurm.sh
## 7. Summarize the motif evaluations to get runtime and AvRec score
./script/bench/summary_benchmark.sh