Philympics 2021: Prophage Predictions Perplex Programs
نویسندگان
چکیده
Background Most bacterial genomes contain integrated bacteriophages—prophages—in various states of decay. Many are active and able to excise from the genome replicate, while others cryptic prophages, remnants their former selves. Over last two decades, many computational tools have been developed identify prophage components genomes, it is a particularly area for application machine learning approaches. However, progress hindered comparisons thwarted because there no manually curated that can be used test new prediction algorithms. Methods We present library gold-standard with annotations, framework compare predictions different algorithms. use this suite all extant stand-alone algorithms strengths weaknesses. provide FAIR dataset identification, demonstrate accuracy, precision, recall, f 1 score analysis ten prophages. Results identified weaknesses between tools. Several exhibit exceptional scores, better recall at expense more false positives. The vary greatly in runtime performance few exhibiting desirable qualities large-scale analyses. Conclusions Our annotations benchmarking valuable resource exploring current future annotation discuss caveats concerns analysis, how those may mitigated, avenues improvements. This will help developers opportunities improvement updates. It also users determining best suited analysis.
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ژورنال
عنوان ژورنال: F1000Research
سال: 2022
ISSN: ['2046-1402']
DOI: https://doi.org/10.12688/f1000research.54449.2