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2. Philympics 2021: Prophage Predictions Perplex Programs

Author

Roach, Michael J, McNair, Katelyn, Giles, Sarah K, Inglis, Laura, Pargin, Evan, Roux, Simon, Decewicz, Przemysław, and Edwards, Robert A

Subjects
Prevention, Genetics, Human Genome
Abstract

AbstractMost bacterial genomes contain integrated bacteriophages—prophages—in various states of decay. Many are active and able to excise from the genome and replicate, while others are cryptic prophages, remnants of their former selves. Over the last two decades, many computational tools have been developed to identify the prophage components of bacterial genomes, and it is a particularly active area for the application of machine learning approaches. However, progress is hindered and comparisons thwarted because there are no manually curated bacterial genomes that can be used to test new prophage prediction algorithms.Here, we present a library of gold-standard bacterial genome annotations that include manually curated prophage annotations, and a computational framework to compare the predictions from different algorithms. We use this suite to compare all extant stand-alone prophage prediction algorithms to identify their strengths and weaknesses.We provide a FAIR dataset for prophage identification, and demonstrate the accuracy, precision, recall, and f1 score from the analysis of seven different algorithms for the prediction of prophages. We discuss caveats and concerns in this analysis and how those concerns may be mitigated.

Published
2021

7. Host interactions of novel Crassvirales species belonging to multiple families infecting bacterial host, Bacteroides cellulosilyticus WH2

Author

Papudeshi, Bhavya, primary, Vega, Alejandro A., additional, Souza, Cole, additional, Giles, Sarah K., additional, Mallawaarachchi, Vijini, additional, Roach, Michael J., additional, An, Michelle, additional, Jacobson, Nicole, additional, McNair, Katelyn, additional, Fernanda Mora, Maria, additional, Pastrana, Karina, additional, Boling, Lance, additional, Leigh, Christopher, additional, Harker, Clarice, additional, Plewa, Will S., additional, Grigson, Susanna R., additional, Bouras, George, additional, Decewicz, Przemysław, additional, Luque, Antoni, additional, Droit, Lindsay, additional, Handley, Scott A., additional, Wang, David, additional, Segall, Anca M., additional, Dinsdale, Elizabeth A., additional, and Edwards, Robert A., additional

Published
2023
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9. Host interactions of novelCrassviralesspecies belonging to multiple families infecting bacterial host,Bacteroides cellulosilyticusWH2

Author

Papudeshi, Bhavya, primary, Vega, Alejandro A., additional, Souza, Cole, additional, Giles, Sarah K., additional, Mallawaarachchi, Vijini, additional, Roach, Michael J., additional, An, Michelle, additional, Jacobson, Nicole, additional, McNair, Katelyn, additional, Mora, Maria Fernanda, additional, Pastrana, Karina, additional, Boling, Lance, additional, Leigh, Christopher, additional, Harker, Clarice, additional, Plewa, Will S., additional, Grigson, Susanna R., additional, Bouras, George, additional, Decewicz, Przemysław, additional, Luque, Antoni, additional, Droit, Lindsay, additional, Handley, Scott A., additional, Wang, David, additional, Segall, Anca M., additional, Dinsdale, Elizabeth A., additional, and Edwards, Robert A., additional

Published
2023
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10. Philympics 2021: Prophage Predictions Perplex Programs

Author

Roach, Michael J., primary, McNair, Katelyn, additional, Michalczyk, Maciej, additional, Giles, Sarah K, additional, Inglis, Laura K, additional, Pargin, Evan, additional, Barylski, Jakub, additional, Roux, Simon, additional, Decewicz, Przemysław, additional, and Edwards, Robert A., additional

Published
2022
Full Text
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13. Philympics 2021: Prophage Predictions Perplex Programs

Author

Roach, Michael, Roach, Michael, McNair, Katelyn, Giles, Sarah, Inglis, Laura, Pargin, Evan, Roux, Simon, Decewicz, Przemysław, Edwards, Robert, Roach, Michael, Roach, Michael, McNair, Katelyn, Giles, Sarah, Inglis, Laura, Pargin, Evan, Roux, Simon, Decewicz, Przemysław, and Edwards, Robert

Abstract

Most bacterial genomes contain integrated bacteriophages—prophages—in various states of decay. Many are active and able to excise from the genome and replicate, while others are cryptic prophages, remnants of their former selves. Over the last two decades, many computational tools have been developed to identify the prophage components of bacterial genomes, and it is a particularly active area for the application of machine learning approaches. However, progress is hindered and comparisons thwarted because there are no manually curated bacterial genomes that can be used to test new prophage prediction algorithms. Here, we present a library of gold-standard bacterial genome annotations that include manually curated prophage annotations, and a computational framework to compare the predictions from different algorithms. We use this suite to compare all extant stand-alone prophage prediction algorithms to identify their strengths and weaknesses. We provide a FAIR dataset for prophage identification, and demonstrate the accuracy, precision, recall, and f 1 score from the analysis of seven different algorithms for the prediction of prophages. We discuss caveats and concerns in this analysis and how those concerns may be mitigated.

Published
2021

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