Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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✓DOI references
Found 1 DOI reference(s) in README -
○Academic publication links
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✓Committers with academic emails
7 of 22 committers (31.8%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (9.6%) to scientific vocabulary
Keywords from Contributors
bioinformatics
metagenomics
annotation
epigenome
genomics
Last synced: 11 months ago
·
JSON representation
Repository
Clustering cONtigs with COverage and ComposiTion
Basic Info
Statistics
- Stars: 132
- Watchers: 7
- Forks: 48
- Open Issues: 73
- Releases: 0
Created about 13 years ago
· Last pushed over 6 years ago
https://github.com/BinPro/CONCOCT/blob/develop/
## CONCOCT 1.1.0 [](https://travis-ci.org/BinPro/CONCOCT) A program for unsupervised binning of metagenomic contigs by using nucleotide composition, coverage data in multiple samples and linkage data from paired end reads. ## Please Cite ## If you use CONCOCT in your publication, please cite: Johannes Alneberg, Brynjar Smri Bjarnason, Ino de Bruijn, Melanie Schirmer, Joshua Quick, Umer Z Ijaz, Leo Lahti, Nicholas J Loman, Anders F Andersson & Christopher Quince. 2014. Binning metagenomic contigs by coverage and composition. *Nature Methods*, doi: 10.1038/nmeth.3103 ## Documentation ## A comprehensive documentation for concoct is hosted on [readthedocs](https://concoct.readthedocs.org). ## Basic Usage ## Cut contigs into smaller parts ```bash cut_up_fasta.py original_contigs.fa -c 10000 -o 0 --merge_last -b contigs_10K.bed > contigs_10K.fa ``` Generate table with coverage depth information per sample and subcontig. This step assumes the directory 'mapping' contains sorted and indexed bam files where each sample has been mapped against the original contigs. ```bash concoct_coverage_table.py contigs_10K.bed mapping/Sample*.sorted.bam > coverage_table.tsv ``` Run concoct ```bash concoct --composition_file contigs_10K.fa --coverage_file coverage_table.tsv -b concoct_output/ ``` Merge subcontig clustering into original contig clustering ```bash merge_cutup_clustering.py concoct_output/clustering_gt1000.csv > concoct_output/clustering_merged.csv ``` Extract bins as individual FASTA ```bash mkdir concoct_output/fasta_bins extract_fasta_bins.py original_contigs.fa concoct_output/clustering_merged.csv --output_path concoct_output/fasta_bins ``` ## Support ## [](https://gitter.im/BinPro/CONCOCT) If you are having trouble running CONCOCT or interpretting any results, please don't hesitate to write a question in our gitter channel. ## Contribute ## - Issue Tracker: [github](https://github.com/binpro/CONCOCT/issues) - Source Code: [github](https://github.com/binpro/CONCOCT)
Owner
- Name: BinPro
- Login: BinPro
- Kind: organization
- Repositories: 7
- Profile: https://github.com/BinPro
GitHub Events
Total
- Issues event: 3
- Watch event: 6
- Issue comment event: 11
Last Year
- Issues event: 3
- Watch event: 6
- Issue comment event: 11
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Johannes Alneberg | a****g@k****e | 269 |
| Brynjar Smari Bjarnason | b****i@b****m | 110 |
| Johannes Alneberg | j****g@g****m | 105 |
| Ino de Bruijn | i****n@s****e | 71 |
| Chris Quince | c****q@q****k | 46 |
| Chris Quince | c****e@g****k | 32 |
| Johannes Alneberg | j****g@s****e | 18 |
| Christopher Quince | u****8@0****e | 14 |
| chrisquince | c****e@w****k | 11 |
| antagomir | a****r@o****p | 6 |
| Ino de Bruijn | i****s@h****m | 5 |
| Anders Andersson | d****s@g****m | 4 |
| Nick Loman | n****n@b****k | 2 |
| chrisquince | c****e@w****k | 2 |
| linsalrob | r****s@g****m | 2 |
| Ahmed Kachkach | a****h@g****m | 1 |
| Sebastian Jaenicke | s****k@C****E | 1 |
| zhujie | z****e@g****n | 1 |
| Christopher Quince | u****8@0****l | 1 |
| Sean Jungbluth | j****n@g****m | 1 |
| Frédéric Mahé | f****e@c****r | 1 |
| Ubuntu | u****u@m****r | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 83
- Total pull requests: 32
- Average time to close issues: over 1 year
- Average time to close pull requests: about 2 months
- Total issue authors: 68
- Total pull request authors: 6
- Average comments per issue: 2.76
- Average comments per pull request: 0.56
- Merged pull requests: 27
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 5
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 5
- Pull request authors: 0
- Average comments per issue: 0.8
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- franciscozorrilla (6)
- alneberg (5)
- jfrank87 (2)
- EricDeveaud (2)
- vinisalazar (2)
- yoyohashao (2)
- SarahIsme (2)
- ramnageena11 (2)
- Rahimlou (1)
- gavinmdouglas (1)
- Jigyasa3 (1)
- gelomerase (1)
- Marlinski95 (1)
- tangminBio (1)
- jiangshf5 (1)
Pull Request Authors
- alneberg (27)
- openpaul (2)
- linsalrob (1)
- Sebastien-Raguideau (1)
- jungbluth (1)
- sjaenick (1)
Top Labels
Issue Labels
enhancement (4)
question (2)
Pull Request Labels
in progress (4)
Packages
- Total packages: 1
-
Total downloads:
- pypi 18 last-month
- Total dependent packages: 0
- Total dependent repositories: 3
- Total versions: 7
- Total maintainers: 1
pypi.org: concoct
Clustering cONtigs with COverage and ComposiTion
- Homepage: https://github.com/BinPro/CONCOCT
- Documentation: https://concoct.readthedocs.io/
- License: FreeBSD
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Latest release: 0.4.0
published almost 12 years ago
Rankings
Docker downloads count: 3.7%
Forks count: 5.9%
Stargazers count: 6.8%
Dependent repos count: 9.0%
Dependent packages count: 10.0%
Average: 13.2%
Downloads: 44.0%
Maintainers (1)
Last synced:
11 months ago
Dependencies
doc/requirements.txt
pypi
- Sphinx >=1.3.1
- conf *
- mock >=1.0.1
- sphinx-rtd-theme >=0.1.6
- sphinxcontrib-programoutput >=0.8
requirements.txt
pypi
- argparse >=1.2.1
- bcbio-gff >=0.4,<=0.6.4
- bcbio-gff >=0.4
- biopython >=1.63,<=1.72
- biopython >=1.63
- cython >=0.28.5
- nose >=1.3.0
- numpy >=1.8.0
- pandas >=0.13.0
- python-dateutil >=2.2
- pytz >=2013.9
- scikit-learn >=0.14.1
- scipy >=0.13.3
setup.py
pypi
- biopython >=1.62b
- cython >=0.19.1
- nose *
- numpy >=1.7.1
- pandas >=0.11.0
- scikit-learn >=0.13.1
- scipy >=0.12.0