A primer on deep learning in genomics

https://doi.org/10.1038/s41588-018-0295-5

> Deep learning methods are a class of machine learning techniques capable of identifying highly complex patterns in large datasets. Here, we provide a perspective and primer on deep learning applications for genome analysis. We discuss successful applications in the fields of regulatory genomics, variant calling and pathogenicity scores. We include general guidance for how to effectively use deep learning methods as well as a practical guide to tools and resources. This primer is accompanied by an interactive online tutorial.

This primer isn't in a ten simple rules format, but there is some overlap we with the goals of this project. We should review it and potentially use it as a reference. For instance, Table 1 lists resources for #31.

Start with the linked primer and its Table 1, then compare the listed resources with issue #31 and the project's goals. Determine whether the primer should be adopted as a reference and document any concrete resource updates; the work is done when that review and decision are recorded.

Written by the indexing model from the issue text.