Nextflow

Last updated
Nextflow
Original author(s) Paolo Di Tommaso
Developer(s) Seqera Labs, Centre for Genomic Regulation
Initial release April 9, 2013;11 years ago (2013-04-09)
Stable release
v23.10.1 / January 12, 2024;4 months ago (2024-01-12)
Preview release
v24.02.0-edge / March 9, 2024;2 months ago (2024-03-09)
Repository https://github.com/nextflow-io/nextflow
Written in Groovy, Java
Operating system Linux, macOS, WSL
Type Scientific workflow system, Dataflow programming, Big data
License Apache License 2.0
Website nextflow.io

Nextflow is a scientific workflow system predominantly used for bioinformatic data analyses. It imposes standards on how to programmatically author a sequence of dependent compute steps and enables their execution on various local and cloud resources. [1] [2] Nextflow was conceived at the Centre for Genomic Regulation in Barcelona, Spain, but has since found world-wide adoption in biomedical and genomics research facilities and laboratories.

Contents

Purpose

Many scientific data analyses require a significant amount of sequential processing steps. Custom scripts may suffice when developing new methods or infrequently running a particular analysis, but scale poorly to complex task successions or many samples. [3] [4] [5]

Scientific workflow systems like Nextflow allow formalizing an analysis as a data analysis pipeline. Pipelines, also known as workflows, are instructions that specify order and conditions of computing steps to be performed. They are carried out by special purpose programs, so-called workflow executors, which ensure predictable and reproducible behavior in various compute environments. [3] [6] [7] [8]

Workflow systems also provide built-in solutions to common challenges of workflow development, such as the application to multiple samples, the validation of input and intermediate results, conditional execution of steps, error handling, and report generation. Advanced features of workflow systems may also include scheduling capabilities, graphical user interfaces for monitoring workflow executions, and the management of dependencies by containerizing the whole workflow or its components. [9] [10]

Typically, scientific workflow systems initially present a steep learning challenge as all their features and complexities are added on top of and in addition to the actual analysis. However, the standards and abstraction imposed by workflow systems ultimately improve the traceability of analysis steps, which is particularly relevant when collaborating on pipeline development, as is customary in scientific settings. [11]

Characteristics

Specification of workflows

In Nextflow, pipelines are constructed from individual processes that correspond to computational tasks. Each process is set up with input requirements and output declarations. Rather than running in a fixed succession, the execution of a process commences when all its input requirements are met. By specifying the output of one process as the input of another step, a logical and sequential connection between processes is created. [12]

This reactive implementation of processes is a characteristic design pattern of Nextflow and also known as functional dataflow model. [13] It allows for the efficient parallelization of independent compute steps.

Processes and whole workflows are programmed in a domain-specific language (DSL) that is provided by Nextflow and based on Apache Groovy. [14] While Nextflow's DSL is used to declare the workflow logic, developers can use their scripting language of choice within a process and mix multiple languages in a workflow. Porting existing scripts and workflows to Nextflow is therefore possible. Supported scripting languages include bash, csh, ksh, Python, Ruby, and R. Any scripting language that uses the standard Unix shebang declaration (#!/bin/bash) is supported in Nextflow.

An exemplary workflow consisting of only one process is shown below:

processhello_world{input:valgreetingoutput:path"${greeting}.txt"script:"""    echo "${greeting} World!" > ${greeting}.txt    """}workflow{Channel.of("Hello","Ciao","Hola","Bonjour")|hello_world}

To facilitate straightforward collaboration on workflows, Nextflow has native support for source-code management systems and DevOps-platforms including GitHub, GitLab, and others. [15]

Execution of workflows

Workflows written in Nextflow's DSL can be deployed and run across diverse computing environments without modifications to the pipeline code.

To enable portability, Nextflow ships with dedicated executors for a variety of platforms [16] including those of major cloud providers. Because Nextflow decouples individual process steps, it can optionally be configured to spread execution across multiple computing platforms. It supports the following environments for pipeline execution:

Containers for portability across computing environments

A fundamental concept of Nextflow is its tight integration with software containers. Whole workflows and, in later versions, also single processes can harness containers to allow their execution across various compute environments without tedious installation and configuration routines. [3]

This design choice was strongly influenced by Solomon Hyke's talk at dotScale in 2013, [20] which had a significant impact on Nextflow's principal developer, Paolo Di Tommaso. [21]

Container frameworks supported by Nextflow include Docker, Singularity, Charliecloud, Podman, and Shifter. [22] Those type of containers can be utilized in a workflow and are automatically retrieved from external repositories when the pipeline is executed. At Nextflow Summit 2022, it was unveiled that future versions of Nextflow will support a dedicated container provisioning service for an improved integration of customized containers into workflows. [23]

Developmental history

Nextflow was originally developed at the Centre for Genomic Regulation in Spain and released as an open-source project on GitHub in July 2013. [24] In October 2018, the project license for Nextflow was changed from GPLv3 to Apache 2.0. [25]

In July 2018, Seqera Labs was launched as a spin-off from the Centre for Genomic Regulation. [21] The company employs many of Nextflow's core developers and maintainers and provides commercial services [26] and consulting with a focus on Nextflow.

In July 2020, a major extension and revision of Nextflow's domain-specific language was introduced to allow for sub-workflows and additional improvements. [27] In the same year, monthly downloads of Nextflow sat at approximately 55,000 per month. [21]

Adoption and reception

The nf-core community

In addition to the Centre for Genomic Regulation, [28] other sequencing facilities have adopted Nextflow as their preferred Scientific workflow system, among them the Quantitative Biology Center in Tübingen, the Francis Crick Institute, A*STAR Genome Institute of Singapore, and the Swedish National Genomics Infrastructure. [21]

Efforts to share, harmonize, and curate the bioinformatic pipelines used by those facilities [29] [30] [31] [32] eventually turned into the nf-core project. [33] Spearheaded by Phil Ewels from the Swedish National Genomics Infrastructure [34] [35] the focus of the nf-core project is to ensure that pipelines are reproducible and portable across different hardware, operating systems, and software versions. In July 2020, Nextflow and nf-core were awarded a grant from the Chan Zuckerberg Initiative, recognizing its role as a vital open-source software. [36]

As of 2022, the nf-core organization hosts 73 Nextflow pipelines for the biosciences and more than 700 process modules. Uniting more than 500 developers and scientists, it is the largest collaborative effort and community to develop bioinformatic data analysis pipelines. [37]

By domain and research subject

Nextflow is preferred in sequencing data processing and genomic data analysis. Over the last five years, numerous pipelines for many different applications and analyses in the field of genomics have been published.

A notable use case in this regard was for pathogen surveillance during the COVID-19 pandemic. [38] Monitoring the emergence of new virus variants and retracing its global spread required the swift and highly automatized, yet accurate, processing of raw data, variant analysis, and the designation of lineages, which was enabled by pipelines written in Nextflow. [39] [40] [41] [42] [43] [44] [45]

Nextflow also plays an important role for the non-profit plasmid repository Addgene, which uses it to corroborate the integrity of all deposited plasmids. [46]

Apart from genomics, Nextflow is gaining popularity in other domains of biomedical data processing, which also require the application of complex workflows on large amounts of primary data: Drug screening, [47] Diffusion magnetic resonance imaging (dMRI) in radiology, [48] and mass spectrometry data processing, [49] [50] [51] the latter with a particular focus on proteomics [52] [53] [54] [55] [56] [57] [58] [59]

Related Research Articles

<span class="mw-page-title-main">Bioinformatics</span> Computational analysis of large, complex sets of biological data

Bioinformatics is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. The subsequent process of analyzing and interpreting data is referred to as computational biology.

<span class="mw-page-title-main">Genomics</span> Discipline in genetics

Genomics is an interdisciplinary field of molecular biology focusing on the structure, function, evolution, mapping, and editing of genomes. A genome is an organism's complete set of DNA, including all of its genes as well as its hierarchical, three-dimensional structural configuration. In contrast to genetics, which refers to the study of individual genes and their roles in inheritance, genomics aims at the collective characterization and quantification of all of an organism's genes, their interrelations and influence on the organism. Genes may direct the production of proteins with the assistance of enzymes and messenger molecules. In turn, proteins make up body structures such as organs and tissues as well as control chemical reactions and carry signals between cells. Genomics also involves the sequencing and analysis of genomes through uses of high throughput DNA sequencing and bioinformatics to assemble and analyze the function and structure of entire genomes. Advances in genomics have triggered a revolution in discovery-based research and systems biology to facilitate understanding of even the most complex biological systems such as the brain.

In bioinformatics, sequence analysis is the process of subjecting a DNA, RNA or peptide sequence to any of a wide range of analytical methods to understand its features, function, structure, or evolution. It can be performed on the entire genome, transcriptome or proteome of an organism, and can also involve only selected segments or regions, like tandem repeats and transposable elements. Methodologies used include sequence alignment, searches against biological databases, and others.

<span class="mw-page-title-main">Orange (software)</span> Open-source data analysis software

Orange is an open-source data visualization, machine learning and data mining toolkit. It features a visual programming front-end for explorative qualitative data analysis and interactive data visualization.

<span class="mw-page-title-main">Generic Model Organism Database</span>

The Generic Model Organism Database (GMOD) project provides biological research communities with a toolkit of open-source software components for visualizing, annotating, managing, and storing biological data. The GMOD project is funded by the United States National Institutes of Health, National Science Foundation and the USDA Agricultural Research Service.

GenePattern is a freely available computational biology open-source software package originally created and developed at the Broad Institute for the analysis of genomic data. Designed to enable researchers to develop, capture, and reproduce genomic analysis methodologies, GenePattern was first released in 2004. GenePattern is currently developed at the University of California, San Diego.

<span class="mw-page-title-main">Galaxy (computational biology)</span>

Galaxy is a scientific workflow, data integration, and data and analysis persistence and publishing platform that aims to make computational biology accessible to research scientists that do not have computer programming or systems administration experience. Although it was initially developed for genomics research, it is largely domain agnostic and is now used as a general bioinformatics workflow management system.

<span class="mw-page-title-main">Pan-genome</span> All genes of all strains in a clade

In the fields of molecular biology and genetics, a pan-genome is the entire set of genes from all strains within a clade. More generally, it is the union of all the genomes of a clade. The pan-genome can be broken down into a "core pangenome" that contains genes present in all individuals, a "shell pangenome" that contains genes present in two or more strains, and a "cloud pangenome" that contains genes only found in a single strain. Some authors also refer to the cloud genome as "accessory genome" containing 'dispensable' genes present in a subset of the strains and strain-specific genes. Note that the use of the term 'dispensable' has been questioned, at least in plant genomes, as accessory genes play "an important role in genome evolution and in the complex interplay between the genome and the environment". The field of study of pangenomes is called pangenomics.

A scientific workflow system is a specialized form of a workflow management system designed specifically to compose and execute a series of computational or data manipulation steps, or workflow, in a scientific application.

LabKey Server is a software suite available for scientists to integrate, analyze, and share biomedical research data. The platform provides a secure data repository that allows web-based querying, reporting, and collaborating across a range of data sources. Specific scientific applications and workflows can be added on top of the basic platform and leverage a data processing pipeline.

<span class="mw-page-title-main">Anduril (workflow engine)</span> Data analysis framework

Anduril is an open source component-based workflow framework for scientific data analysis developed at the Systems Biology Laboratory, University of Helsinki.

De novo transcriptome assembly is the de novo sequence assembly method of creating a transcriptome without the aid of a reference genome.

Integromics was a global bioinformatics company headquartered in Granada, Spain and Madrid. The company had subsidiaries in the United States and United Kingdom, and distributors in 10 countries. Integromics specialised in bioinformatics software for data management and data analysis in genomics and proteomics. The company provided a line of products that serve gene expression, sequencing, and proteomics markets. Customers include genomic research centers, pharmaceutical companies, academic institutions, clinical research organizations, and biotechnology companies.

A bioinformatics workflow management system is a specialized form of workflow management system designed specifically to compose and execute a series of computational or data manipulation steps, or a workflow, that relate to bioinformatics.

The High-performance Integrated Virtual Environment (HIVE) is a distributed computing environment used for healthcare-IT and biological research, including analysis of Next Generation Sequencing (NGS) data, preclinical, clinical and post market data, adverse events, metagenomic data, etc. Currently it is supported and continuously developed by US Food and Drug Administration, George Washington University, and by DNA-HIVE, WHISE-Global and Embleema. HIVE currently operates fully functionally within the US FDA supporting wide variety (+60) of regulatory research and regulatory review projects as well as for supporting MDEpiNet medical device postmarket registries. Academic deployments of HIVE are used for research activities and publications in NGS analytics, cancer research, microbiome research and in educational programs for students at GWU. Commercial enterprises use HIVE for oncology, microbiology, vaccine manufacturing, gene editing, healthcare-IT, harmonization of real-world data, in preclinical research and clinical studies.

The BioCompute Object (BCO) project is a community-driven initiative to build a framework for standardizing and sharing computations and analyses generated from High-throughput sequencing. The project has since been standardized as IEEE 2791-2020, and the project files are maintained in an open source repository. The July 22nd, 2020 edition of the Federal Register announced that the FDA now supports the use of BioCompute in regulatory submissions, and the inclusion of the standard in the Data Standards Catalog for the submission of HTS data in NDAs, ANDAs, BLAs, and INDs to CBER, CDER, and CFSAN.

The 'German Network for Bioinformatics Infrastructure – de.NBI' is a national, academic and non-profit infrastructure initiated by the Federal Ministry of Education and Research funding 2015-2021. The network provides bioinformatics services to users in life sciences research and biomedicine in Germany and Europe. The partners organize training events, courses and summer schools on tools, standards and compute services provided by de.NBI to assist researchers to more effectively exploit their data. From 2022, the network will be integrated into Forschungszentrum Jülich.

Debasis Dash is an Indian computational biologist and chief scientist at the Institute of Genomics and Integrative Biology (IGIB). Known for his research on proteomics and Big Data and Artificial Intelligence studies, his studies have been documented by way of a number of articles and ResearchGate, an online repository of scientific articles has listed 120 of them. The Department of Biotechnology of the Government of India awarded him the National Bioscience Award for Career Development, one of the highest Indian science awards, for his contributions to biosciences, in 2014. He was appointed as the director of Institute of Life Sciences, Bhubaneswar on 18 May 2023.

References

  1. ↑ Strozzi, Francesco; Janssen, Roel; Wurmus, Ricardo; Crusoe, Michael R.; Githinji, George; Di Tommaso, Paolo; Belhachemi, Dominique; Möller, Steffen; Smant, Geert; De Ligt, Joep; Prins, Pjotr (2019). "Scalable Workflows and Reproducible Data Analysis for Genomics". Evolutionary Genomics. Methods in Molecular Biology. Vol. 1910. pp. 723–745. doi:10.1007/978-1-4939-9074-0_24. ISBN   978-1-4939-9073-3. PMC   7613310 . PMID   31278683.
  2. ↑ Gao, Mingxuan; Ling, Mingyi; Tang, Xinwei; Wang, Shun; Xiao, Xu; Qiao, Ying; Yang, Wenxian; Yu, Rongshan (2021). "Comparison of high-throughput single-cell RNA sequencing data processing pipelines". Briefings in Bioinformatics. 22 (3). doi:10.1093/bib/bbaa116. PMID   34020539.
  3. 1 2 3 Wratten, Laura; Wilm, Andreas; Göke, Jonathan (October 2021). "Reproducible, scalable, and shareable analysis pipelines with bioinformatics workflow managers". Nature Methods. 18 (10): 1161–1168. doi:10.1038/s41592-021-01254-9. PMID   34556866. S2CID   237616424.
  4. ↑ Terrón-Camero, Laura C.; Gordillo-González, Fernando; Salas-Espejo, Eduardo; Andrés-León, Eduardo (2022). "Comparison of Metagenomics and Metatranscriptomics Tools: A Guide to Making the Right Choice". Genes. 13 (12): 2280. doi: 10.3390/genes13122280 . PMC   9777648 . PMID   36553546.
  5. ↑ Federico, Anthony; Karagiannis, Tanya; Karri, Kritika; Kishore, Dileep; Koga, Yusuke; Campbell, Joshua D.; Monti, Stefano (2019). "Pipeliner: A Nextflow-Based Framework for the Definition of Sequencing Data Processing Pipelines". Frontiers in Genetics. 10: 614. doi: 10.3389/fgene.2019.00614 . PMC   6609566 . PMID   31316552.
  6. ↑ Kolpakov, Fedor; Akberdin, Ilya; Kiselev, Ilya; Kolmykov, Semyon; Kondrakhin, Yury; Kulyashov, Mikhail; Kutumova, Elena; Pintus, Sergey; Ryabova, Anna; Sharipov, Ruslan; Yevshin, Ivan; Zhatchenko, Sergey; Kel, Alexander (2022). "BioUML—towards a universal research platform". Nucleic Acids Research. 50 (W1): W124–W131. doi:10.1093/nar/gkac286. PMC   9252820 . PMID   35536253.
  7. ↑ Yukselen, Onur; Turkyilmaz, Osman; Ozturk, Ahmet Rasit; Garber, Manuel; Kucukural, Alper (2020). "Dolphin Next: A distributed data processing platform for high throughput genomics". BMC Genomics. 21 (1): 310. doi: 10.1186/s12864-020-6714-x . PMC   7168977 . PMID   32306927.
  8. ↑ Yuen, Denis; Cabansay, Louise; Duncan, Andrew; Luu, Gary; Hogue, Gregory; Overbeck, Charles; Perez, Natalie; Shands, Walt; Steinberg, David; Reid, Chaz; Olunwa, Nneka; Hansen, Richard; Sheets, Elizabeth; o'Farrell, Ash; Cullion, Kim; o'Connor, Brian D; Paten, Benedict; Stein, Lincoln (2021). "The Dockstore: Enhancing a community platform for sharing reproducible and accessible computational protocols". Nucleic Acids Research. 49 (W1): W624–W632. doi:10.1093/nar/gkab346. PMC   8218198 . PMID   33978761.
  9. ↑ Ahmed, Azza E.; Allen, Joshua M.; Bhat, Tajesvi; Burra, Prakruthi; Fliege, Christina E.; Hart, Steven N.; Heldenbrand, Jacob R.; Hudson, Matthew E.; Istanto, Dave Deandre; Kalmbach, Michael T.; Kapraun, Gregory D.; Kendig, Katherine I.; Kendzior, Matthew Charles; Klee, Eric W.; Mattson, Nate; Ross, Christian A.; Sharif, Sami M.; Venkatakrishnan, Ramshankar; Fadlelmola, Faisal M.; Mainzer, Liudmila S. (2021). "Design considerations for workflow management systems use in production genomics research and the clinic". Scientific Reports. 11 (1): 21680. Bibcode:2021NatSR..1121680A. doi:10.1038/s41598-021-99288-8. PMC   8569008 . PMID   34737383.
  10. ↑ Baichoo, Shakuntala; Souilmi, Yassine; Panji, Sumir; Botha, Gerrit; Meintjes, Ayton; Hazelhurst, Scott; Bendou, Hocine; Beste, Eugene de; Mpangase, Phelelani T.; Souiai, Oussema; Alghali, Mustafa; Yi, Long; o'Connor, Brian D.; Crusoe, Michael; Armstrong, Don; Aron, Shaun; Joubert, Fourie; Ahmed, Azza E.; Mbiyavanga, Mamana; Heusden, Peter van; Magosi, Lerato E.; Zermeno, Jennie; Mainzer, Liudmila Sergeevna; Fadlelmola, Faisal M.; Jongeneel, C. Victor; Mulder, Nicola (2018). "Developing reproducible bioinformatics analysis workflows for heterogeneous computing environments to support African genomics". BMC Bioinformatics. 19 (1): 457. doi: 10.1186/s12859-018-2446-1 . PMC   6264621 . PMID   30486782.
  11. ↑ Jackson, Michael; Kavoussanakis, Kostas; Wallace, Edward W. J. (2021). "Using prototyping to choose a bioinformatics workflow management system". PLOS Computational Biology. 17 (2): e1008622. Bibcode:2021PLSCB..17E8622J. doi: 10.1371/journal.pcbi.1008622 . PMC   7906312 . PMID   33630841.
  12. ↑ Tommaso, Paolo Di; Floden, Evan W.; Magis, Cedrik; Palumbo, Emilio; Notredame, Cedric (2017). "Nextflow : Un outil efficace pour l'amélioration de la stabilité numérique des calculs en analyse génomique". Biologie Aujourd'hui. 211 (3): 233–237. doi:10.1051/jbio/2017029. PMID   29412134.
  13. ↑ "Nextflow Documentation - Channels". docs.nextflow.io. Retrieved 6 June 2022.
  14. ↑ "Nextflow Documentation - Domain Specific Language (DSL) 2". docs.nextflow.io. Retrieved 6 June 2022.
  15. ↑ "Nextflow Documentation - Pipeline Sharing". docs.nextflow.io. Retrieved 6 June 2022.
  16. ↑ "Nextflow Documentation - Executors". docs.nextflow.io. Retrieved 6 June 2022.
  17. ↑ "Nextflow Documentation - Amazon Cloud". docs.nextflow.io. Retrieved 6 June 2022.
  18. ↑ "Nextflow Documentation - Azure Cloud". docs.nextflow.io. Retrieved 6 June 2022.
  19. ↑ "Nextflow Documentation - Google Cloud". docs.nextflow.io. Retrieved 6 June 2022.
  20. ↑ Hykes, Solomon (7 June 2013). "Dot Scale 2013 - Why we built Docker". YouTube. Retrieved 6 June 2022.
  21. 1 2 3 4 Di Tomasso, Paolo (14 October 2021). "The story of Nextflow: Building a modern pipeline orchestrator". eLifeSciences.org. Retrieved 6 June 2022.
  22. ↑ "Nextflow Documentation - Containers". docs.nextflow.io. Retrieved 7 June 2022.
  23. ↑ Di Tommaso, Paolo (13 October 2022). "Nextflow and the future of containers". YouTube. Retrieved 17 November 2022.
  24. ↑ "Release Version 0.3.0 · nextflow-io/nextflow". GitHub. Retrieved 31 May 2022.
  25. ↑ Di Tomasso, Paolo (24 October 2018). "Goodbye zero, Hello Apache!". Nextflow.io/blog. Retrieved 7 June 2022.
  26. ↑ Di Tommaso, Paolo (8 October 2019). "Introducing Nextflow Tower - Seamless monitoring of data analysis workflows from anywhere". Seqera.IO. Retrieved 7 June 2022.
  27. ↑ Di Tommaso, Paolo (24 July 2020). "Nextflow DSL 2 is here!". Nextflow.IO/blog. Retrieved 7 June 2022.
  28. ↑ Di Tomasso, Paolo; Chatzou, Maria; Floden, Evan; Prieto Barja, Pablo; Palumbo, Emilio; Notredame, Cedric (11 April 2017). "Nextflow enables reproducible computational workflows". Nature Biotechnology. 35 (4): 316–319. doi:10.1038/nbt.3820. PMID   28398311. S2CID   9690740 . Retrieved 7 June 2022.
  29. ↑ Fellows Yates, James A.; Lamnidis, Thiseas C.; Borry, Maxime; Andrades Valtueña, Aida; Fagernäs, Zandra; Clayton, Stephen; Garcia, Maxime U.; Neukamm, Judith; Peltzer, Alexander (2021). "Reproducible, portable, and efficient ancient genome reconstruction with nf-core/Eager". PeerJ. 9: e10947. doi: 10.7717/peerj.10947 . PMC   7977378 . PMID   33777521.
  30. ↑ Krakau, Sabrina; Straub, Daniel; Gourlé, Hadrien; Gabernet, Gisela; Nahnsen, Sven (2022). "Nf-core/Mag: A best-practice pipeline for metagenome hybrid assembly and binning". Nar Genomics and Bioinformatics. 4: lqac007. doi:10.1093/nargab/lqac007. PMC   8808542 . PMID   35118380.
  31. ↑ Garcia, Maxime; Juhos, Szilveszter; Larsson, Malin; Olason, Pall I.; Martin, Marcel; Eisfeldt, Jesper; Dilorenzo, Sebastian; Sandgren, Johanna; Díaz De Ståhl, Teresita; Ewels, Philip; Wirta, Valtteri; Nistér, Monica; Käller, Max; Nystedt, Björn (2020). "Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants". F1000Research. 9: 63. doi: 10.12688/f1000research.16665.2 . PMC   7111497 . PMID   32269765.
  32. ↑ Digby, Barry; Finn, Stephen P.; ó Broin, Pilib (2023). "Nf-core/Circrna: A portable workflow for the quantification, miRNA target prediction and differential expression analysis of circular RNAs". BMC Bioinformatics. 24 (1): 27. doi: 10.1186/s12859-022-05125-8 . PMC   9875403 . PMID   36694127.
  33. ↑ Ewels, Philip; Peltzer, Alexander; Fillinger, Sven; Alneberg, Johannes; Patel, Harshil; Wilm, Andreas; Garcia, Maxime Ulysse; Di Tommaso, Paolo; Nahnsen, Sven (April 1, 2019). "Nf-core: Community curated bioinformatics pipelines". Research Gate. Retrieved June 30, 2022.
  34. ↑ Zapata Garin, Claire-Alix. "nf-core: a community-driven initiative to standardise Nextflow-based pipelines". Lifebit.ai. Retrieved June 30, 2022.
  35. ↑ "The nf-core community provides computational pipelines". SciLifeLab. February 14, 2020. Retrieved June 30, 2022.
  36. ↑ "Nextflow and nf-core: Reproducible Workflows for the Scientific Community". Chan Zuckerberg Initiative. 27 July 2020. Retrieved 15 June 2022.
  37. ↑ "nf-core Github organization". GitHub. Retrieved 18 November 2022.
  38. ↑ Floden, Evan (5 November 2021). "Genetic Sequencing Will Enable Us To Win The Global Battle Against COVID-19".
  39. ↑ Afolayan, Ayorinde O.; et al. (2021). "Overcoming Data Bottlenecks in Genomic Pathogen Surveillance". Clinical Infectious Diseases. 73 (Suppl_4): S267–S274. doi:10.1093/cid/ciab785. PMC   8634317 . PMID   34850839.
  40. ↑ Tilloy, Valentin; Cuzin, Pierre; Leroi, Laura; Guérin, Emilie; Durand, Patrick; Alain, Sophie (2022). "ASPICov: An automated pipeline for identification of SARS-Cov2 nucleotidic variants". PLOS ONE. 17 (1): e0262953. Bibcode:2022PLoSO..1762953T. doi: 10.1371/journal.pone.0262953 . PMC   8791494 . PMID   35081137.
  41. ↑ Petit, Robert A.; Read, Timothy D. (2020). "Bactopia: A Flexible Pipeline for Complete Analysis of Bacterial Genomes". mSystems. 5 (4). doi:10.1128/mSystems.00190-20. PMC   7406220 . PMID   32753501.
  42. ↑ Pandolfo, Mattia; Telatin, Andrea; Lazzari, Gioele; Adriaenssens, Evelien M.; Vitulo, Nicola (2022). "Meta Phage: An Automated Pipeline for Analyzing, Annotating, and Classifying Bacteriophages in Metagenomics Sequencing Data". mSystems. 7 (5): e0074122. doi:10.1128/msystems.00741-22. PMC   9599279 . PMID   36069454.
  43. ↑ Gauthier, Marie-Emilie A.; Lelwala, Ruvini V.; Elliott, Candace E.; Windell, Craig; Fiorito, Sonia; Dinsdale, Adrian; Whattam, Mark; Pattemore, Julie; Barrero, Roberto A. (2022). "Side-by-Side Comparison of Post-Entry Quarantine and High Throughput Sequencing Methods for Virus and Viroid Diagnosis". Biology. 11 (2): 263. doi: 10.3390/biology11020263 . PMC   8868628 . PMID   35205129.
  44. ↑ Brandt, Christian; Krautwurst, Sebastian; Spott, Riccardo; Lohde, Mara; Jundzill, Mateusz; Marquet, Mike; Hölzer, Martin (2021). "Pore Cov-An Easy to Use, Fast, and Robust Workflow for SARS-CoV-2 Genome Reconstruction via Nanopore Sequencing". Frontiers in Genetics. 12: 711437. doi: 10.3389/fgene.2021.711437 . PMC   8355734 . PMID   34394197.
  45. ↑ Afiahayati; Bernard, Stefanus; Gunadi; Wibawa, Hendra; Hakim, Mohamad Saifudin; Marcellus; Parikesit, Arli Aditya; Dewa, Chandra Kusuma; Sakakibara, Yasubumi (2022). "A Comparison of Bioinformatics Pipelines for Enrichment Illumina Next Generation Sequencing Systems in Detecting SARS-CoV-2 Virus Strains". Genes. 13 (8): 1330. doi: 10.3390/genes13081330 . PMC   9394340 . PMID   35893066.
  46. ↑ Niehaus, Jason (14 July 2022). "Bioinformatics at Addgene". Addgene corporate blog. Retrieved 25 February 2023.
  47. ↑ Ssekagiri, Alfred; Jjingo, Daudi; Lujumba, Ibra; Bbosa, Nicholas; Bugembe, Daniel L.; Kateete, David P.; Jordan, I King; Kaleebu, Pontiano; Ssemwanga, Deogratius (2022). "Quasi Flow: A Nextflow pipeline for analysis of NGS-based HIV-1 drug resistance data". Bioinformatics Advances. 2: vbac089. doi:10.1093/bioadv/vbac089. PMC   9722223 . PMID   36699347.
  48. ↑ Theaud, Guillaume; Houde, Jean-Christophe; Boré, Arnaud; Rheault, François; Morency, Felix; Descoteaux, Maxime (2020). "Tracto Flow: A robust, efficient and reproducible diffusion MRI pipeline leveraging Nextflow & Singularity". NeuroImage. 218: 116889. doi: 10.1016/j.neuroimage.2020.116889 . PMID   32447016. S2CID   164318811.
  49. ↑ Van Maldegem, Febe; Valand, Karishma; Cole, Megan; Patel, Harshil; Angelova, Mihaela; Rana, Sareena; Colliver, Emma; Enfield, Katey; Bah, Nourdine; Kelly, Gavin; Tsang, Victoria Siu Kwan; Mugarza, Edurne; Moore, Christopher; Hobson, Philip; Levi, Dina; Molina-Arcas, Miriam; Swanton, Charles; Downward, Julian (2021). "Characterisation of tumour microenvironment remodelling following oncogene inhibition in preclinical studies with imaging mass cytometry". Nature Communications. 12 (1): 5906. Bibcode:2021NatCo..12.5906V. doi:10.1038/s41467-021-26214-x. PMC   8501076 . PMID   34625563.
  50. ↑ Li, Chenxin; Gao, Mingxuan; Yang, Wenxian; Zhong, Chuanqi; Yu, Rongshan (2021). "Diamond: A multi-modal DIA mass spectrometry data processing pipeline". Bioinformatics. 37 (2): 265–267. doi:10.1093/bioinformatics/btaa1093. PMID   33416868.
  51. ↑ Luu, Gordon T.; Freitas, Michael A.; Lizama-Chamu, Itzel; McCaughey, Catherine S.; Sanchez, Laura M.; Wang, Mingxun (2022). "TIMSCONVERT: A workflow to convert trapped ion mobility data to open data formats". Bioinformatics. 38 (16): 4046–4047. doi:10.1093/bioinformatics/btac419. PMC   9991885 . PMID   35758608.
  52. ↑ Perez-Riverol, Yasset; Moreno, Pablo (2020). "Scalable Data Analysis in Proteomics and Metabolomics Using Bio Containers and Workflows Engines". Proteomics. 20 (9): e1900147. doi:10.1002/pmic.201900147. PMC   7613303 . PMID   31657527.
  53. ↑ Vlasova, Anna; Hermoso Pulido, Toni; Camara, Francisco; Ponomarenko, Julia; Guigó, Roderic (2021). "FA-nf: A Functional Annotation Pipeline for Proteins from Non-Model Organisms Implemented in Nextflow". Genes. 12 (10): 1645. doi: 10.3390/genes12101645 . PMC   8535801 . PMID   34681040.
  54. ↑ Miller, Rachel M.; Jordan, Ben T.; Mehlferber, Madison M.; Jeffery, Erin D.; Chatzipantsiou, Christina; Kaur, Simi; Millikin, Robert J.; Dai, Yunxiang; Tiberi, Simone; Castaldi, Peter J.; Shortreed, Michael R.; Luckey, Chance John; Conesa, Ana; Smith, Lloyd M.; Deslattes Mays, Anne; Sheynkman, Gloria M. (2022). "Enhanced protein isoform characterization through long-read proteogenomics". Genome Biology. 23 (1): 69. doi: 10.1186/s13059-022-02624-y . PMC   8892804 . PMID   35241129.
  55. ↑ Othman, Houcemeddine; Jemimah, Sherlyn; Da Rocha, Jorge Emanuel Batista (2022). "SWAAT Bioinformatics Workflow for Protein Structure-Based Annotation of ADME Gene Variants". Journal of Personalized Medicine. 12 (2): 263. doi: 10.3390/jpm12020263 . PMC   8875676 . PMID   35207751.
  56. ↑ Bichmann, Leon; Gupta, Shubham; Rosenberger, George; Kuchenbecker, Leon; Sachsenberg, Timo; Ewels, Phil; Alka, Oliver; Pfeuffer, Julianus; Kohlbacher, Oliver; Röst, Hannes (2021). "DIAproteomics: A Multifunctional Data Analysis Pipeline for Data-Independent Acquisition Proteomics and Peptidomics". Journal of Proteome Research. 20 (7): 3758–3766. doi: 10.1021/acs.jproteome.1c00123 . PMID   34153189. S2CID   235597603.
  57. ↑ Walzer, Mathias; García-Seisdedos, David; Prakash, Ananth; Brack, Paul; Crowther, Peter; Graham, Robert L.; George, Nancy; Mohammed, Suhaib; Moreno, Pablo; Papatheodorou, Irene; Hubbard, Simon J.; Vizcaíno, Juan Antonio (2022). "Implementing the reuse of public DIA proteomics datasets: From the PRIDE database to Expression Atlas". Scientific Data. 9 (1): 335. Bibcode:2022NatSD...9..335W. doi:10.1038/s41597-022-01380-9. PMC   9197839 . PMID   35701420.
  58. ↑ Hulstaert, Niels; Shofstahl, Jim; Sachsenberg, Timo; Walzer, Mathias; Barsnes, Harald; Martens, Lennart; Perez-Riverol, Yasset (2020). "ThermoRawFile Parser: Modular, Scalable, and Cross-Platform RAW File Conversion". Journal of Proteome Research. 19 (1): 537–542. doi:10.1021/acs.jproteome.9b00328. PMC   7116465 . PMID   31755270.
  59. ↑ Li, Kai; Jain, Antrix; Malovannaya, Anna; Wen, Bo; Zhang, Bing (2020). "Deep Rescore: Leveraging Deep Learning to Improve Peptide Identification in Immunopeptidomics". Proteomics. 20 (21–22): e1900334. doi:10.1002/pmic.201900334. PMC   7718998 . PMID   32864883.

See also

Galaxy Snakemake

This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.