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Semi-supervised segmentation and genome annotation

View ORCID ProfileRachel C.W. Chan, View ORCID ProfileMatthew McNeil, View ORCID ProfileEric G. Roberts, View ORCID ProfileMickaël Mendez, View ORCID ProfileMaxwell W. Libbrecht, View ORCID ProfileMichael M. Hoffman
doi: https://doi.org/10.1101/2020.01.30.926923
Rachel C.W. Chan
1University of Toronto
2Princess Margaret Cancer Centre
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Matthew McNeil
1University of Toronto
2Princess Margaret Cancer Centre
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  • ORCID record for Matthew McNeil
Eric G. Roberts
2Princess Margaret Cancer Centre
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Mickaël Mendez
1University of Toronto
2Princess Margaret Cancer Centre
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Maxwell W. Libbrecht
3Simon Fraser University
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Michael M. Hoffman
1University of Toronto
2Princess Margaret Cancer Centre
4Vector Institute
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  • For correspondence: michael.hoffman@utoronto.ca
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Abstract

Segmentation and genome annotation methods automatically discover joint signal patterns in whole genome datasets. Previously, researchers trained these algorithms in a fully unsupervised way, with no prior knowledge of the functions of particular regions. Adding information provided by expert-created annotations to supervise training could improve the annotations created by these methods. We implemented semi-supervised learning using virtual evidence in the annotation method Segway. Additionally, we defined a positionally tolerant precision and recall metric for scoring genome annotations based on the proximity of each annotation feature to the truth set. We demonstrate semi-supervised Segway’s ability to learn patterns corresponding to provided transcription start sites on a specified supervision label, and subsequently recover other transcription start sites in unseen data on the same supervision label.

Footnotes

  • https://segway.hoffmanlab.org

  • https://doi.org/10.5281/zenodo.3630670

  • https://doi.org/10.5281/zenodo.3627261

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted February 01, 2020.
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Semi-supervised segmentation and genome annotation
Rachel C.W. Chan, Matthew McNeil, Eric G. Roberts, Mickaël Mendez, Maxwell W. Libbrecht, Michael M. Hoffman
bioRxiv 2020.01.30.926923; doi: https://doi.org/10.1101/2020.01.30.926923
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Semi-supervised segmentation and genome annotation
Rachel C.W. Chan, Matthew McNeil, Eric G. Roberts, Mickaël Mendez, Maxwell W. Libbrecht, Michael M. Hoffman
bioRxiv 2020.01.30.926923; doi: https://doi.org/10.1101/2020.01.30.926923

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