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).
