PT  - JOURNAL ARTICLE
AU  - Madison Caballero
AU  - Jill Wegrzyn
TI  - gFACs: Filtering, analysis, and conversion to unify genome annotations across alignment and gene prediction frameworks
AID  - 10.1101/402396
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 402396
4099  - http://biorxiv.org/content/early/2018/09/10/402396.short
4100  - http://biorxiv.org/content/early/2018/09/10/402396.full
AB  - Motivation 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.Summary 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.Availability and Implementation gFACs is freely available and implemented in Perl with support from BioPerl libraries: https://gitlab.com/PlantGenomicsLab/gFACsContact Corresponding Authors: Madison.Caballero{at}uconn.edu and jill.wegrzyn{at}uconn.eduSupplementary data Supplemental table 1 and supplemental figure 1.