ArticleBMC bioinformatics2020
MetaLAFFA: a flexible, end-to-end, distributed computing-compatible metagenomic functional annotation pipeline.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 20 citations in OpenAlex.
- From functional annotation to functional meaning in microbiome research.Environmental microbiome · 2026Review
- Mapping the canine gut microbiome: insights from the Dog Aging Project.Nature communications · 2026Article
- Biofilm marker discovery with cloud-based dockerized metagenomics analysis of microbial communities.Briefings in bioinformatics · 2024Article
- KOunt: a reproducible KEGG orthologue abundance workflow.Bioinformatics (Oxford, England) · 2023Article
- Ten quick tips for bioinformatics analyses using an Apache Spark distributed computing environment.PLoS computational biology · 2023Article
- A data-driven approach for predicting the impact of drugs on the human microbiome.Nature communications · 2023Article
- ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization.Frontiers in genetics · 2023Article
- OMARU: a robust and multifaceted pipeline for metagenome-wide association study.NAR genomics and bioinformatics · 2022Article
- Infants with cystic fibrosis have altered fecal functional capacities with potential clinical and metabolic consequences.BMC microbiology · 2021Observational
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundMicrobial communities have become an important subject of research across multiple disciplines in recent years. These communities are often examined via shotgun metagenomic sequencing, a technology which can offer unique insights into the genomic content of a microbial community. Functional annotation of shotgun metagenomic data has become an increasingly popular method for identifying the aggregate functional capacities encoded by the community's constituent microbes. Currently available metagenomic functional annotation pipelines, however, suffer from several shortcomings, including limited pipeline customization options, lack of standard raw sequence data pre-processing, and insufficient capabilities for integration with distributed computing systems.
resultsHere we introduce MetaLAFFA, a functional annotation pipeline designed to take unfiltered shotgun metagenomic data as input and generate functional profiles. MetaLAFFA is implemented as a Snakemake pipeline, which enables convenient integration with distributed computing clusters, allowing users to take full advantage of available computing resources. Default pipeline settings allow new users to run MetaLAFFA according to common practices while a Python module-based configuration system provides advanced users with a flexible interface for pipeline customization. MetaLAFFA also generates summary statistics for each step in the pipeline so that users can better understand pre-processing and annotation quality.
conclusionsMetaLAFFA is a new end-to-end metagenomic functional annotation pipeline with distributed computing compatibility and flexible customization options. MetaLAFFA source code is available at https://github.com/borenstein-lab/MetaLAFFA and can be installed via Conda as described in the accompanying documentation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.