https://github.com/chapmanb/bcbb

Incubator for useful bioinformatics code, primarily in Python and R
https://github.com/chapmanb/bcbb

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Incubator for useful bioinformatics code, primarily in Python and R

• Host: GitHub
• URL: https://github.com/chapmanb/bcbb
• Owner: chapmanb
• Created: 2008-12-09T21:05:22.000Z (about 16 years ago)
• Default Branch: master
• Last Pushed: 2024-01-29T13:59:57.000Z (12 months ago)
• Last Synced: 2025-01-10T17:07:24.787Z (7 days ago)
• Language: Python
• Homepage: http://bcbio.wordpress.com
• Size: 79.4 MB
• Stars: 612
• Watchers: 58
• Forks: 242
• Open Issues: 19
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-python-resources - GitHub - 19% open · ⏱️ 18.11.2021): (科学计算和数据分析)

README

        
Collection of useful code related to biological analysis. Much of this is 

discussed with examples at [Blue collar bioinformatics][1].

All code, images and documents in this repository are freely available for all

uses. Code is available under the [MIT license](https://opensource.org/licenses/MIT)

and images, documentations and talks under the [Creative Commons No Rights

Reserved (CC0) license](https://creativecommons.org/share-your-work/public-domain/cc0/).

Some projects which may be especially interesting:

* CloudBioLinux -- An automated environment to install useful biological software and

  libraries. This is used to bootstrap blank machines, such as those you'd

  find on Cloud providers like Amazon, to ready to go analysis workstations.

  See the [CloudBioLinux][2] effort for more details. This project

  moved to its own repository at https://github.com/chapmanb/cloudbiolinux.

* gff -- A GFF parsing library in Python, aimed for inclusion into Biopython.

* nextgen -- A python toolkit providing best-practice pipelines for fully 

  automated high throughput sequencing analysis.  This project has 

  moved into its own repository: https://github.com/chapmanb/bcbio-nextgen

* distblast -- A distributed BLAST analysis running for identifying best hits in

  a wide variety of organisms for downstream phylogenetic analyses. The code

  is generalized to run on local multi-processor and distributed Hadoop

  clusters.

[1]: http://bcbio.wordpress.com

[2]: http://cloudbiolinux.org/