mag

Assembly and binning of metagenomes

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 15 DOI reference(s) in README
○
Academic publication links
✓
Committers with academic emails
7 of 42 committers (16.7%) from academic institutions
○
Institutional organization owner
○
JOSS paper metadata
○
Scientific vocabulary similarity
Low similarity (12.3%) to scientific vocabulary

Keywords

annotation assembly binning bioinformatics long-read-sequencing metagenomes metagenomics nanopore nanopore-sequencing nextflow nf-core pipeline workflow

Keywords from Contributors

workflows pipelines nf-test dsl2 taxonomic-profiling taxonomic-classification illumina microbiome rrna qiime2

Last synced: 6 months ago · JSON representation ·

Repository

Assembly and binning of metagenomes

Basic Info

Host: GitHub
Owner: nf-core
License: mit
Language: Nextflow
Default Branch: main
Homepage: https://nf-co.re/mag
Size: 37.1 MB

Statistics

Stars: 247
Watchers: 175
Forks: 135
Open Issues: 67
Releases: 30

Topics

annotation assembly binning bioinformatics long-read-sequencing metagenomes metagenomics nanopore nanopore-sequencing nextflow nf-core pipeline workflow

Created almost 8 years ago · Last pushed 6 months ago

Metadata Files

Readme Changelog Contributing License Code of conduct Citation Codeowners

Introduction

nf-core/mag is a bioinformatics best-practise analysis pipeline for assembly, binning and annotation of metagenomes.

nf-core/mag workflow overview

Pipeline summary

Usage

[!NOTE] If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

By default, the pipeline currently performs the following: it supports both short and long reads, quality trims the reads and adapters with fastp, AdapterRemoval, or trimmomatic and Porechop, and performs basic QC with FastQC, and merges multiple sequencing runs.

The pipeline then:

assigns taxonomy to reads using Centrifuge and/or Kraken2
performs assembly using MEGAHIT and SPAdes, and checks their quality using Quast
(optionally) performs ancient DNA assembly validation using PyDamage and contig consensus sequence recalling with Freebayes and BCFtools
predicts protein-coding genes for the assemblies using Prodigal, and bins with Prokka and optionally MetaEuk
performs metagenome binning using MetaBAT2, MaxBin2, and/or with CONCOCT, and checks the quality of the genome bins using Busco, CheckM, or CheckM2 and optionally GUNC.
Performs ancient DNA validation and repair with pyDamage and freebayes
optionally refines bins with DAS Tool
assigns taxonomy to bins using GTDB-Tk and/or CAT and optionally identifies viruses in assemblies using geNomad, or Eukaryotes with Tiara

Furthermore, the pipeline creates various reports in the results directory specified, including a MultiQC report summarizing some of the findings and software versions.

Usage

[!NOTE] If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

bash nextflow run nf-core/mag -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> --input '*_R{1,2}.fastq.gz' --outdir <OUTDIR>

bash nextflow run nf-core/mag -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> --input samplesheet.csv --outdir <OUTDIR>

[!WARNING] Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

For more details and further functionality, please refer to the usage documentation and the parameter documentation.

Pipeline output

To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.

Group-wise co-assembly and co-abundance computation

Each sample has an associated group ID (see input specifications). This group information can be used for group-wise co-assembly with MEGAHIT or SPAdes and/or to compute co-abundances for the binning step with MetaBAT2. By default, group-wise co-assembly is disabled, while the computation of group-wise co-abundances is enabled. For more information about how this group information can be used see the documentation for the parameters --coassemble_group and --binning_map_mode.

When group-wise co-assembly is enabled, SPAdes is run on accordingly pooled read files, since metaSPAdes does not yet allow the input of multiple samples or libraries. In contrast, MEGAHIT is run for each group while supplying lists of the individual readfiles.

Credits

nf-core/mag was written by Hadrien Gourlé at SLU, Daniel Straub and Sabrina Krakau at the Quantitative Biology Center (QBiC). James A. Fellows Yates and Maxime Borry at the Max Planck Institute for Evolutionary Anthropology joined in version 2.2.0.

Other code contributors include:

Long read processing was inspired by caspargross/HybridAssembly written by Caspar Gross @caspargross

We thank the following people for their extensive assistance in the development of this pipeline:

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don't hesitate to get in touch on the Slack #mag channel (you can join with this invite).

Citations

If you use nf-core/mag for your analysis, please cite the preprint as follows:

nf-core/mag: a best-practice pipeline for metagenome hybrid assembly and binning

Sabrina Krakau, Daniel Straub, Hadrien Gourlé, Gisela Gabernet, Sven Nahnsen.

NAR Genom Bioinform. 2022 Feb 2;4(1):lqac007. doi: 10.1093/nargab/lqac007.

Additionally you can cite the pipeline directly with the following doi: 10.5281/zenodo.3589527

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.

Owner

Name: nf-core
Login: nf-core
Kind: organization
Email: core@nf-co.re

Website: http://nf-co.re
Twitter: nf_core
Repositories: 84
Profile: https://github.com/nf-core

A community effort to collect a curated set of analysis pipelines built using Nextflow.

Citation (CITATIONS.md)

# nf-core/mag: Citations

## [nf-core](https://pubmed.ncbi.nlm.nih.gov/32055031/)

> Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Mar;38(3):276-278. doi: 10.1038/s41587-020-0439-x. PubMed PMID: 32055031.

## [Nextflow](https://pubmed.ncbi.nlm.nih.gov/28398311/)

> Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 28398311.

## Pipeline tools

- [AdapterRemoval2](https://doi.org/10.1186/)

  > Schubert, M., Lindgreen, S., and Orlando, L. 2016. "AdapterRemoval v2: Rapid Adapter Trimming, Identification, and Read Merging." BMC Research Notes 9 (February): 88. doi: 10.1186/s13104-016-1900-2

- [BBnorm/BBTools](http://sourceforge.net/projects/bbmap/)

- [BCFtools](https://doi.org/10.1093/gigascience/giab008)

  > Danecek, Petr, et al. "Twelve years of SAMtools and BCFtools." Gigascience 10.2 (2021): giab008. doi: 10.1093/gigascience/giab008

- [Bowtie2](https:/dx.doi.org/10.1038/nmeth.1923)

  > Langmead, B. and Salzberg, S. L. 2012 Fast gapped-read alignment with Bowtie 2. Nature methods, 9(4), p. 357–359. doi: 10.1038/nmeth.1923.

- [Busco](https://doi.org/10.1007/978-1-4939-9173-0_14)

  > Seppey, M., Manni, M., & Zdobnov, E. M. (2019). BUSCO: assessing genome assembly and annotation completeness. In Gene prediction (pp. 227-245). Humana, New York, NY. doi: 10.1007/978-1-4939-9173-0_14.

- [CAT](https://doi.org/10.1186/s13059-019-1817-x)

  > von Meijenfeldt, F. B., Arkhipova, K., Cambuy, D. D., Coutinho, F. H., & Dutilh, B. E. (2019). Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT. Genome biology, 20(1), 1-14. doi: 10.1186/s13059-019-1817-x.

- [Centrifuge](https://doi.org/10.1101/gr.210641.116)

  > Kim, D., Song, L., Breitwieser, F. P., & Salzberg, S. L. (2016). Centrifuge: rapid and sensitive classification of metagenomic sequences. Genome research, 26(12), 1721-1729. doi: 10.1101/gr.210641.116.

- [CheckM](https://doi.org/10.1101/gr.186072.114)

  > Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P., & Tyson, G. W. (2015). CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Research, 25(7), 1043–1055. doi: 10.1101/gr.186072.114

- [CheckM2](https://doi.org/10.1038/s41592-023-01940-w)

  > Chklovski, A., Parks, D. H., Woodcroft, B. J., & Tyson, G. W. (2023). CheckM2: a rapid, scalable and accurate tool for assessing microbial genome quality using machine learning. Nature Methods, 20(8), 1203-1212. doi: https://doi.org/10.1038/s41592-023-01940-w

- [Chopper](https://doi.org/10.1093/bioinformatics/bty149)

  > De Coster W, D'Hert S, Schultz DT, Cruts M, Van Broeckhoven C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics. 2018 Aug 1;34(15):2666-2669. doi: 10.1093/bioinformatics/bty149

- [CONCOCT](https://doi.org/10.1038/nmeth.3103)

  > Alneberg, J., Bjarnason, B. S., de Bruijn, I., Schirmer, M., Quick, J., Ijaz, U. Z., Lahti, L., Loman, N. J., Andersson, A. F., & Quince, C. (2014). Binning metagenomic contigs by coverage and composition. Nature Methods, 11(11), 1144–1146. doi: 10.1038/nmeth.3103

- [DAS Tool](https://doi.org/10.1038/s41564-018-0171-1)

  > Sieber, C. M. K., et al. 2018. "Recovery of Genomes from Metagenomes via a Dereplication, Aggregation and Scoring Strategy." Nature Microbiology 3 (7): 836-43. doi: 10.1038/s41564-018-0171-1

- [FastP](https://doi.org/10.1093/bioinformatics/bty560)

  > Chen, S., Zhou, Y., Chen, Y., & Gu, J. (2018). fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics , 34(17), i884–i890. doi: 10.1093/bioinformatics/bty560.

- [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)

  > Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online].

- [Filtlong](https://github.com/rrwick/Filtlong)

- [Freebayes](https://arxiv.org/abs/1207.3907)

  > Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. arXiv preprint arXiv:1207.3907 [q-bio.GN] 2012

- [geNomad](https://doi.org/10.1101/2023.03.05.531206)

  > Camargo, A. P., et al. (2023). You can move, but you can’t hide: identification of mobile genetic elements with geNomad. bioRxiv preprint. doi: 10.1101/2023.03.05.531206

- [GTDB-Tk](https://doi.org/10.1093/bioinformatics/btz848)

  > Chaumeil, P. A., Mussig, A. J., Hugenholtz, P., & Parks, D. H. (2020). GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics , 36(6), 1925–1927. doi: 10.1093/bioinformatics/btz848.

- [GUNC](https://doi.org/10.1186/s13059-021-02393-0.)

  > Orakov, A., Fullam, A., Coelho, A. P., Khedkar, S., Szklarczyk, D., Mende, D. R., Schmidt, T. S. B., and Bork, P.. 2021. “GUNC: Detection of Chimerism and Contamination in Prokaryotic Genomes.” Genome Biology 22 (1): 178. doi: 10.1186/s13059-021-02393-0.

- [Kraken2](https://doi.org/10.1186/s13059-019-1891-0)

  > Wood, D et al., 2019. Improved metagenomic analysis with Kraken 2. Genome Biology volume 20, Article number: 257. doi: 10.1186/s13059-019-1891-0.

- [Krona](https://doi.org/10.1186/1471-2105-12-385)

  > Ondov, B. D., Bergman, N. H., & Phillippy, A. M. (2011). Interactive metagenomic visualization in a Web browser. BMC bioinformatics, 12(1), 1-10. doi: 10.1186/1471-2105-12-385.

- [MaxBin2](https://doi.org/10.1093/bioinformatics/btv638)

  > Yu-Wei, W., Simmons, B. A. & Singer, S. W. (2015) MaxBin 2.0: An Automated Binning Algorithm to Recover Genomes from Multiple Metagenomic Datasets. Bioinformatics 32 (4): 605–7. doi: 10.1093/bioinformatics/btv638.

- [MEGAHIT](https://doi.org/10.1016/j.ymeth.2016.02.020)

  > Li, D., Luo, R., Liu, C. M., Leung, C. M., Ting, H. F., Sadakane, K., ... & Lam, T. W. (2016). MEGAHIT v1. 0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods, 102, 3-11. doi: 10.1016/j.ymeth.2016.02.020.

- [MetaBAT2](https://doi.org/10.7717/peerj.7359)

  > Kang, D. D., Li, F., Kirton, E., Thomas, A., Egan, R., An, H., & Wang, Z. (2019). MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ, 7, e7359. doi: 10.7717/peerj.7359.

- [MetaEuk](https://doi.org/10.1186/s40168-020-00808-x)

  > Levy Karin, E., Mirdita, M. & Söding, J. MetaEuk—sensitive, high-throughput gene discovery, and annotation for large-scale eukaryotic metagenomics. Microbiome 8, 48 (2020). 10.1186/s40168-020-00808-x

- [MMseqs2](https://www.nature.com/articles/nbt.3988)

  > Steinegger, M., Söding, J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol 35, 1026–1028 (2017).10.1038/nbt.3988

- [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/)

  > Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924.

- [NanoLyse](https://doi.org/10.1093/bioinformatics/bty149)

  > De Coster, W., D’Hert, S., Schultz, D. T., Cruts, M., & Van Broeckhoven, C. (2018). NanoPack: visualizing and processing long-read sequencing data. Bioinformatics, 34(15), 2666-2669. doi: 10.1093/bioinformatics/bty149.

- [NanoPlot](https://doi.org/10.1093/bioinformatics/bty149)

  > De Coster, W., D’Hert, S., Schultz, D. T., Cruts, M., & Van Broeckhoven, C. (2018). NanoPack: visualizing and processing long-read sequencing data. Bioinformatics, 34(15), 2666-2669. doi: 10.1093/bioinformatics/bty149.

- [Nanoq](https://doi.org/10.21105/joss.02991)

  > Steinig, E., Coin, L. (2022). Nanoq: ultra-fast quality control for nanopore reads. Journal of Open Source Software, 7(69), 2991, doi: 10.21105/joss.02991

- [Porechop](https://github.com/rrwick/Porechop)

- [Porechop-abi](https://github.com/bonsai-team/Porechop_ABI)

  > Bonenfant, Q., Noé, L., & Touzet, H. (2022). Porechop_ABI: discovering unknown adapters in ONT sequencing reads for downstream trimming. bioRxiv. 10.1101/2022.07.07.499093

- [Prodigal](https://pubmed.ncbi.nlm.nih.gov/20211023/)

  > Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010 Mar 8;11:119. doi: 10.1186/1471-2105-11-119. PMID: 20211023; PMCID: PMC2848648.

- [Prokka](https://pubmed.ncbi.nlm.nih.gov/24642063/)

  > Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014 Jul 15;30(14):2068-9. doi: 10.1093/bioinformatics/btu153. Epub 2014 Mar 18. PMID: 24642063.

- [PyDamage](https://doi.org/10.7717/peerj.11845)

  > Borry M, Hübner A, Rohrlach AB, Warinner C. 2021. PyDamage: automated ancient damage identification and estimation for contigs in ancient DNA de novo assembly. PeerJ 9:e11845 doi: 10.7717/peerj.11845

- [SAMtools](https://doi.org/10.1093/bioinformatics/btp352)

  > Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., … 1000 Genome Project Data Processing Subgroup. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics , 25(16), 2078–2079. doi: 10.1093/bioinformatics/btp352.

- [Seqtk](https://github.com/lh3/seqtk)

- [SPAdes](https://doi.org/10.1101/gr.213959.116)

  > Nurk, S., Meleshko, D., Korobeynikov, A., & Pevzner, P. A. (2017). metaSPAdes: a new versatile metagenomic assembler. Genome research, 27(5), 824-834. doi: 10.1101/gr.213959.116.

- [Tiara](https://doi.org/10.1093/bioinformatics/btab672)

  > Karlicki, M., Antonowicz, S., Karnkowska, A., 2022. Tiara: deep learning-based classification system for eukaryotic sequences. Bioinformatics 38, 344–350. doi: 10.1093/bioinformatics/btab672

## Data

- [Full-size test data](https://doi.org/10.1038/s41587-019-0191-2)

  > Bertrand, D., Shaw, J., Kalathiyappan, M., Ng, A. H. Q., Kumar, M. S., Li, C., ... & Nagarajan, N. (2019). Hybrid metagenomic assembly enables high-resolution analysis of resistance determinants and mobile elements in human microbiomes. Nature biotechnology, 37(8), 937-944. doi: 10.1038/s41587-019-0191-2.

## Software packaging/containerisation tools

- [Anaconda](https://anaconda.com)

  > Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.

- [Bioconda](https://pubmed.ncbi.nlm.nih.gov/29967506/)

  > Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018 Jul;15(7):475-476. doi: 10.1038/s41592-018-0046-7. PubMed PMID: 29967506.

- [BioContainers](https://pubmed.ncbi.nlm.nih.gov/28379341/)

  > da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-Riverol Y. BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics. 2017 Aug 15;33(16):2580-2582. doi: 10.1093/bioinformatics/btx192. PubMed PMID: 28379341; PubMed Central PMCID: PMC5870671.

- [Docker](https://dl.acm.org/doi/10.5555/2600239.2600241)

  > Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239), 2. doi: 10.5555/2600239.2600241.

- [Singularity](https://pubmed.ncbi.nlm.nih.gov/28494014/)

  > Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; PubMed Central PMCID: PMC5426675.

Committers

Last synced: over 2 years ago

All Time

Total Commits: 1,521
Total Committers: 42
Avg Commits per committer: 36.214
Development Distribution Score (DDS): 0.766

Past Year

Commits: 489
Committers: 28
Avg Commits per committer: 17.464
Development Distribution Score (DDS): 0.519

Top Committers

Name	Email	Commits
Sabrina Krakau	s**c@g**m	356
James Fellows Yates	j**3@g**m	345
Sabrina Krakau	s**u@q**e	179
d4straub	d**b@u**e	140
Hadrien Gourlé	g**n@g**m	114
prototaxites	j**e@f**g	57
Daniel Straub	4****b	39
maxibor	m**y@g**m	36
nf-core-bot	c**e@n**e	35
PhilPalmer	p**l@g**m	28
Daniel Lundin	e**l@g**m	27
gregorysprenger	4****r	24
AntoniaSchuster	a**r@q**e	24
Jim Downie	1****s	17
Carson J Miller	6****M	12
Alex Huebner	a**r@g**m	9
MaxUlysse	m**a@g**m	8
Jim Downie	j**e@b**k	7
William Rosenbaum	w**8@g**m	6
@alxndrdiaz	r**z@g**m	6
Sabrina Krakau	s**u@g**m	6
Maxime Borry	m**y@e**e	5
AntoniaSchuster	5****r	5
Carson J Miller	c**r@o**m	5
Gisela Gabernet	g**t@g**m	4
Williams UMU-MacBook	w**m@u**e	3
Mark Lubberts	m****r	3
Till Englert	t**6@g**m	2
Paul Cantalupo	p**o@g**m	2
Harshil Patel	d**h@g**m	2
and 12 more...

Committer Domains (Top 20 + Academic)

qbic.uni-tuebingen.de: 3 seqera.io: 2 kth.se: 1 acm.org: 1 t-online.de: 1 example.org: 1 umu.se: 1 eva.mpg.de: 1 bangor.ac.uk: 1 nf-co.re: 1 fastmail.org: 1 uni-tuebingen.de: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 197
Total pull requests: 243
Average time to close issues: 5 months
Average time to close pull requests: 12 days
Total issue authors: 93
Total pull request authors: 30
Average comments per issue: 2.4
Average comments per pull request: 2.62
Merged pull requests: 177
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 59
Pull requests: 110
Average time to close issues: 20 days
Average time to close pull requests: 7 days
Issue authors: 30
Pull request authors: 15
Average comments per issue: 1.41
Average comments per pull request: 2.45
Merged pull requests: 72
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

jfy133 (32)
prototaxites (13)
amizeranschi (11)
skrakau (9)
alexhbnr (8)
CarsonJM (5)
s-junguy (5)
Thomieh73 (4)
dialvarezs (4)
d4straub (3)
rialc13 (3)
mjfi2sb3 (3)
muniheart (3)
erikrikarddaniel (3)
maxibor (2)

Pull Request Authors

jfy133 (131)
nf-core-bot (32)
dialvarezs (17)
prototaxites (14)
maxibor (9)
muabnezor (4)
erikrikarddaniel (3)
vinisalazar (3)
muniheart (3)
amizeranschi (2)
harper357 (2)
alxndrdiaz (2)
willros (2)
vagkaratzas (2)
IceGreb (2)

Top Labels

Issue Labels

bug (90) enhancement (78) question (3) low-priority (3) support (2) WIP (1) good first issue (1) wontfix (1)

Pull Request Labels

ready to review (4) do not merge (3) enhancement (3) bug (2) WIP (1) good first issue (1)

Dependencies

.github/workflows/awsfulltest.yml actions

nf-core/tower-action v3 composite

.github/workflows/awstest.yml actions

nf-core/tower-action v3 composite

.github/workflows/branch.yml actions

mshick/add-pr-comment v1 composite

.github/workflows/ci.yml actions

actions/checkout v2 composite

.github/workflows/fix-linting.yml actions

actions/checkout v3 composite
actions/setup-node v2 composite

.github/workflows/linting.yml actions

actions/checkout v2 composite
actions/setup-node v2 composite
actions/setup-python v3 composite
actions/upload-artifact v2 composite

.github/workflows/linting_comment.yml actions

dawidd6/action-download-artifact v2 composite
marocchino/sticky-pull-request-comment v2 composite

modules/nf-core/adapterremoval/meta.yml cpan

modules/nf-core/aria2/meta.yml cpan

modules/nf-core/bcftools/consensus/meta.yml cpan

modules/nf-core/bcftools/index/meta.yml cpan

modules/nf-core/bcftools/view/meta.yml cpan

modules/nf-core/checkm/lineagewf/meta.yml cpan

modules/nf-core/checkm/qa/meta.yml cpan

modules/nf-core/concoct/concoct/meta.yml cpan

modules/nf-core/concoct/concoctcoveragetable/meta.yml cpan

modules/nf-core/concoct/cutupfasta/meta.yml cpan

modules/nf-core/concoct/extractfastabins/meta.yml cpan

modules/nf-core/concoct/mergecutupclustering/meta.yml cpan

modules/nf-core/custom/dumpsoftwareversions/meta.yml cpan

modules/nf-core/dastool/dastool/meta.yml cpan

modules/nf-core/dastool/fastatocontig2bin/meta.yml cpan

modules/nf-core/fastp/meta.yml cpan

modules/nf-core/fastqc/meta.yml cpan

modules/nf-core/freebayes/meta.yml cpan

modules/nf-core/gunc/downloaddb/meta.yml cpan

modules/nf-core/gunc/mergecheckm/meta.yml cpan

modules/nf-core/gunc/run/meta.yml cpan

modules/nf-core/gunzip/meta.yml cpan

modules/nf-core/maxbin2/meta.yml cpan

modules/nf-core/metabat2/jgisummarizebamcontigdepths/meta.yml cpan

modules/nf-core/metabat2/metabat2/meta.yml cpan

modules/nf-core/multiqc/meta.yml cpan

modules/nf-core/prodigal/meta.yml cpan

modules/nf-core/prokka/meta.yml cpan

modules/nf-core/pydamage/analyze/meta.yml cpan

modules/nf-core/pydamage/filter/meta.yml cpan

modules/nf-core/samtools/faidx/meta.yml cpan

subworkflows/nf-core/fasta_binning_concoct/meta.yml cpan

pyproject.toml pypi

.github/workflows/clean-up.yml actions

actions/stale v7 composite

modules/nf-core/bbmap/bbnorm/meta.yml cpan

modules/nf-core/cat/fastq/meta.yml cpan

modules/nf-core/genomad/download/meta.yml cpan

modules/nf-core/genomad/endtoend/meta.yml cpan

modules/nf-core/gtdbtk/classifywf/meta.yml cpan

modules/nf-core/metaeuk/easypredict/meta.yml cpan

modules/nf-core/mmseqs/databases/meta.yml cpan

modules/nf-core/seqtk/mergepe/meta.yml cpan

modules/nf-core/tiara/tiara/meta.yml cpan

.github/workflows/download_pipeline.yml actions

actions/setup-python v5 composite
eWaterCycle/setup-singularity v7 composite
nf-core/setup-nextflow v1 composite

.github/workflows/release-announcements.yml actions

actions/setup-python v5 composite
rzr/fediverse-action master composite
zentered/bluesky-post-action v0.1.0 composite

modules/nf-core/custom/dumpsoftwareversions/environment.yml pypi

modules/nf-core/fastqc/environment.yml pypi

modules/nf-core/gtdbtk/classifywf/environment.yml pypi

modules/nf-core/multiqc/environment.yml pypi

mag

Science Score: 67.0%

Keywords

Keywords from Contributors

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

Introduction

Pipeline summary

Usage

Usage

Pipeline output

Group-wise co-assembly and co-abundance computation

Credits

Contributions and Support

Citations

Owner

Citation (CITATIONS.md)

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Dependencies