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Opfi: A Python package for identifying gene clusters in large genomics and metagenomics data sets
Gene clusters are sets of co-localized, often contiguous genes that together perform specific functions, many of which are relevant to biotechnology. There is a need for software tools that can extract candidate gene clusters from vast amounts of available genomic data. Therefore, we developed Opfi:...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9017871/ https://www.ncbi.nlm.nih.gov/pubmed/35445164 http://dx.doi.org/10.21105/joss.03678 |
Sumario: | Gene clusters are sets of co-localized, often contiguous genes that together perform specific functions, many of which are relevant to biotechnology. There is a need for software tools that can extract candidate gene clusters from vast amounts of available genomic data. Therefore, we developed Opfi: a modular pipeline for identification of arbitrary gene clusters in assembled genomic or metagenomic sequences. Opfi contains functions for annotation, de-deduplication, and visualization of putative gene clusters. It utilizes a customizable rule-based filtering approach for selection of candidate systems that adhere to user-defined criteria. Opfi is implemented in Python, and is available on the Python Package Index and on Bioconda (Grüning et al., 2018). |
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