Article ; Online: Metagenomics workflow for hybrid assembly, differential coverage binning, metatranscriptomics and pathway analysis (MUFFIN).
2021 Volume 17, Issue 2, Page(s) e1008716
Abstract: Metagenomics has redefined many areas of microbiology. However, metagenome-assembled genomes (MAGs) are often fragmented, primarily when sequencing was performed with short reads. Recent long-read sequencing technologies promise to improve genome ... ...
| Abstract | Metagenomics has redefined many areas of microbiology. However, metagenome-assembled genomes (MAGs) are often fragmented, primarily when sequencing was performed with short reads. Recent long-read sequencing technologies promise to improve genome reconstruction. However, the integration of two different sequencing modalities makes downstream analyses complex. We, therefore, developed MUFFIN, a complete metagenomic workflow that uses short and long reads to produce high-quality bins and their annotations. The workflow is written by using Nextflow, a workflow orchestration software, to achieve high reproducibility and fast and straightforward use. This workflow also produces the taxonomic classification and KEGG pathways of the bins and can be further used for quantification and annotation by providing RNA-Seq data (optionally). We tested the workflow using twenty biogas reactor samples and assessed the capacity of MUFFIN to process and output relevant files needed to analyze the microbial community and their function. MUFFIN produces functional pathway predictions and, if provided de novo metatranscript annotations across the metagenomic sample and for each bin. MUFFIN is available on github under GNUv3 licence: https://github.com/RVanDamme/MUFFIN. |
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| MeSH term(s) | Algorithms ; Bioreactors ; Computational Biology/methods ; Computer Simulation ; Genomics ; Humans ; Metagenome ; Metagenomics ; RNA-Seq ; Reproducibility of Results ; Sequence Analysis, DNA ; Software ; Workflow |
| Language | English |
| Publishing date | 2021-02-09 |
| Publishing country | United States |
| Document type | Journal Article ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 2193340-6 |
| ISSN | 1553-7358 ; 1553-734X |
| ISSN (online) | 1553-7358 |
| ISSN | 1553-734X |
| DOI | 10.1371/journal.pcbi.1008716 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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