Data analysis results for: "MoDLE: High-performance stochastic modeling of DNA loop extrusion interactions"

Data part of this archive was generated for the following publication: "MoDLE: High-performance stochastic modeling of DNA loop extrusion interactions". Preprint: https://www.biorxiv.org/content/10.1101/2022.04.13.488157v2

The data analysis pipeline used to generate the data is hosted on GitHub at paulsengroup/2021-modle-paper-001-data-analysis https://github.com/paulsengroup/2021-modle-paper-001-data-analysis/tree/v2.0.1 and is also archived on Zenodo 10.5281/zenodo.7072939 https://doi.org/10.5281/zenodo.7072939.

## Testing file integrity after download
Archives have been checksummed using SHA256.
To compare checksums, run the following command:

shasum -c checksums.sha256

NOTE 1: checksums should be checked before extracting the archives
NOTE 2: use option --ignore-missing when computing checksums for a subset of the TARs

## Extracting TAR files
Archived data consists of several compressed TAR files.
Extracting all the TAR files produces the file and folder layout listed in file 2021-modle-paper-001.tree.

TAR archives are compressed using the Zstandard (ZSTD) https://facebook.github.io/zstd/ compression algorithm.

TARs can be extracted as follows:

zstd -dc --long=31 2021-modle-paper-001-data-containers.tar.zst | tar -xf -

This will create a folder named 2021-modle-paper-001 and extract the Docker image files part of the archive inside 2021-modle-paper-001/data/containers/.

NOTE: Trying to extract archives directly won't work, as TARs were compressed using custom compression options.

## Navigating archived data
Each TAR archive contains a README.md file describing the archive content.
Archive 2021-modle-paper-001-readmes.tar contains a copy of all README files (note: this archive is not compressed).

Archives also contain a checksums.sha256 file which can be used to check file integrity after extraction (this is usually not necessary).

## Contact information
Inquiries regarding this dataset should be addressed to the corresponding author for "MoDLE: High-performance stochastic modeling of DNA loop extrusion interactions" (Jonas Paulsen).