Segway 2.0: Gaussian mixture models and minibatch training
نویسندگان
چکیده
Summary Segway performs semi-automated genome annotation, discovering joint patterns across multiple genomic signal datasets. We discuss a major new version of Segway and highlight its ability to model data with substantially greater accuracy. Major enhancements in Segway 2.0 include the ability to model data with a mixture of Gaussians, enabling capture of arbitrarily complex signal distributions, and minibatch training, leading to better learned parameters. Availability and implementation Segway and its source code are freely available for download at http://segway.hoffmanlab.org. We have made available scripts (https://doi.org/10.5281/zenodo.802939) and datasets (https://doi.org/10.5281/zenodo.802906) for this paper's analysis. Contact [email protected]. Supplementary information Supplementary data are available at Bioinformatics online.
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عنوان ژورنال:
دوره 34 شماره
صفحات -
تاریخ انتشار 2018