gFACs: Filtering, analysis, and conversion to unify genome annotations across alignment and gene prediction frameworks.

Caballero, M.; Wegrzyn, J.

doi:10.1101/402396

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bioRxiv · 10.1101/402396

gFACs: Filtering, analysis, and conversion to unify genome annotations across alignment and gene prediction frameworks.

Caballero, M.·Wegrzyn, J.

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Abstract

Published genome annotations are filled with erroneous gene models that represent issues associated with frame, start side identification, splice sites, and related structural features. The source of these inconsistencies can often be traced to translated text file formats designed to describe long read alignments and predicted gene structures. The majority of gene prediction frameworks do not provide downstream filtering to remove problematic gene annotations, nor do they represent these annotations in a format consistent with current file standards. In addition, these frameworks lack consideration for functional attributes, such as the presence or absence of protein domains which can be used for gene model validation. To provide oversight to the increasing number of published genome annotations, we present gFACs as a software package to filter, analyze, and convert predicted gene models and alignments. gFACs operates across a wide range of alignment, analysis, and gene prediction software inputs with a flexible framework for defining gene models with reliable structural and functional attributes. gFACs supports common downstream applications, including genome browsers and generates extensive details on the filtering process, including distributions that can be visualized to further assess the proposed gene space.

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Caballero, M., Wegrzyn, J.. 2018-08-29. gFACs: Filtering, analysis, and conversion to unify genome annotations across alignment and gene prediction frameworks.. https://doi.org/10.1101/402396

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