atlas

Single-file quality control prototyping pipeline for diverse mass spectrometry workflows.

https://github.com/proteomicsunitcrg/atlas

Science Score: 26.0%

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  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (8.4%) to scientific vocabulary

Keywords

computational-proteomics mass-spectrometry nextflow-pipeline quality-control
Last synced: 6 months ago · JSON representation

Repository

Single-file quality control prototyping pipeline for diverse mass spectrometry workflows.

Basic Info
  • Host: GitHub
  • Owner: proteomicsunitcrg
  • License: other
  • Language: Nextflow
  • Default Branch: main
  • Homepage: https://demo-qsample.crg.eu
  • Size: 191 MB
Statistics
  • Stars: 1
  • Watchers: 4
  • Forks: 0
  • Open Issues: 8
  • Releases: 13
Topics
computational-proteomics mass-spectrometry nextflow-pipeline quality-control
Created almost 5 years ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

Atlas

Introduction

Atlas is a Nextflow-based pipeline developed for the processing and analysis of mass spectrometry data, specifically designed to assist proteomics laboratories with daily quality assessments across various proteomics applications. It supports multiple workflows, such as regular proteomes, phosphoproteomes, and independent acquisition modes, among others.

With these diverse workflows, Atlas extracts critical quality control parameters, simplifying the evaluation of mass spectrometry experiments. Atlas can be configured to use various search engines, including:

The pipeline is implemented using the latest Nextflow DSL2 syntax and is designed to operate efficiently in HPC (High-Performance Computing) environments.

For more detailed information, please refer to the documentation.


Credits

The Atlas pipeline was initially developed by @rolivella.

We would like to express our gratitude to the following individuals for their valuable contributions during the development:

  • Eduard Sabid (@edunivers)
  • Cristina Chiva
  • Eva Borrs
  • Guadalupe Espadas
  • Olga Pastor
  • Enrique Alonso
  • Selena Fernndez

Citations

A comprehensive list of references for the tools utilized in the pipeline can be found in the CITATIONS.md file.

Owner

  • Name: CRG/UPF Protemics Unit
  • Login: proteomicsunitcrg
  • Kind: organization
  • Location: Barcelona

GitHub Events

Total
  • Create event: 3
  • Release event: 2
  • Issues event: 19
  • Issue comment event: 53
  • Push event: 39
  • Public event: 1
  • Gollum event: 29
  • Pull request event: 16
Last Year
  • Create event: 3
  • Release event: 2
  • Issues event: 19
  • Issue comment event: 53
  • Push event: 39
  • Public event: 1
  • Gollum event: 29
  • Pull request event: 16

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 12
  • Total pull requests: 10
  • Average time to close issues: 4 months
  • Average time to close pull requests: 30 minutes
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 5.33
  • Average comments per pull request: 0.0
  • Merged pull requests: 6
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 10
  • Pull requests: 10
  • Average time to close issues: 27 days
  • Average time to close pull requests: 30 minutes
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.5
  • Average comments per pull request: 0.0
  • Merged pull requests: 6
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • rolivella (12)
Pull Request Authors
  • rolivella (10)
Top Labels
Issue Labels
High priority (4) Low priority (3) enhancement (2) documentation (1) bug (1)
Pull Request Labels