snhic

Snakemake pipeline for analysis and normalization of Hi-C data starting from fastq.gz files. It includes the possibility to perform grouped analyses, TAD, loops and stripes detections, as well as differential compartment and chromatin interaction analyses.

https://github.com/sebastian-gregoricchio/snhic

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: nature.com
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.4%) to scientific vocabulary

Keywords

compartments dchic genova hi-c hic hicexplorer loop selfish snakemake snakemake-pipeline stripenn tad
Last synced: 4 months ago · JSON representation ·

Repository

Snakemake pipeline for analysis and normalization of Hi-C data starting from fastq.gz files. It includes the possibility to perform grouped analyses, TAD, loops and stripes detections, as well as differential compartment and chromatin interaction analyses.

Basic Info
Statistics
  • Stars: 4
  • Watchers: 1
  • Forks: 0
  • Open Issues: 1
  • Releases: 4
Topics
compartments dchic genova hi-c hic hicexplorer loop selfish snakemake snakemake-pipeline stripenn tad
Created almost 4 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog License Citation

README.md

Snakemake release license forks <!-- update visits downloads--->

snHiC

Introduction

snHiC is a snakemake based end-to-end pipeline to analyze Hi-C data. The input files required to run the pipeline are Paired-End fastq files. The pipeline performs data quality control, normalization and correction. It also includes the possibility to perform grouped analyses (e.g, merging of replicates) besides TAD, loops and stripes detection and differential contacts and compartment analyses. Notabily, the latter is performed using dcHiC, a recently published method (A. Chakraborty, et al., Nat. Comm. 2022) that enables more precise and high-resolution differential compartment analyses.

Citation

If you use this pipeline, please cite:

S. Gregoricchio & W. Zwart. "snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis".
Bioinformatics Adavances, Volume 3, Issue 1, 2023, vbad080
DOI: 10.1093/bioadv/vbad080



Documentation

Details on the installation and usage of snHiC can be found at the dedicated Wiki.




Package history and releases

A list of all releases and respective description of changes applied could be found here.

Contact

For any suggestion, bug fixing, commentary please report it in the issues/request tab of this repository.

License

This repository is under a GNU General Public License (version 3).


Contributors

contributors

Owner

  • Name: Sebastian Gregoricchio
  • Login: sebastian-gregoricchio
  • Kind: user
  • Location: Amsterdam, NL
  • Company: Netherlands Cancer Institute

https://orcid.org/0000-0001-9209-5403

Citation (citation.cff)

cff-version: 1.2.0
message: "If you use snHiC, please cite this publication:"
authors:
- family-names: "Gregoricchio"
  given-names: "Sebastian"
  orcid: "https://orcid.org/0000-0001-9209-5403"
- family-names: "Zwart"
  given-names: "Wilbert"
  orcid: "https://orcid.org/0000-0002-9823-7289"
preferred-citation:
  authors:
  - family-names: "Gregoricchio"
    given-names: "Sebastian"
    orcid: "https://orcid.org/0000-0001-9209-5403"
  - family-names: "Zwart"
    given-names: "Wilbert"
    orcid: "https://orcid.org/0000-0002-9823-7289"
  title: "snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis"
  type: article
  doi: 10.1093/bioadv/vbad080
  issue: 1
  volume: 3
  year: 2023
  url: https://doi.org/10.1093/bioadv/vbad080
  journal: "Bioinformatics Advances"
title: "snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis"
issue: 1
volume: 3
doi: 10.1093/bioadv/vbad080
year: 2023
url: https://doi.org/10.1093/bioadv/vbad080

GitHub Events

Total
  • Issues event: 1
  • Watch event: 1
  • Issue comment event: 14
  • Push event: 7
Last Year
  • Issues event: 1
  • Watch event: 1
  • Issue comment event: 14
  • Push event: 7

Committers

Last synced: over 1 year ago

All Time
  • Total Commits: 138
  • Total Committers: 1
  • Avg Commits per committer: 138.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 5
  • Committers: 1
  • Avg Commits per committer: 5.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Sebastian Gregoricchio 5****o 138

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 1
  • Total pull requests: 0
  • Average time to close issues: about 2 months
  • Average time to close pull requests: N/A
  • Total issue authors: 1
  • Total pull request authors: 0
  • Average comments per issue: 2.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: about 2 months
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 2.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • bighawkin (1)
  • mano2991 (1)
Pull Request Authors
Top Labels
Issue Labels
bug (1) enhancement (1)
Pull Request Labels