mariyagolchin / a-primer-on-deep-learning-in-genomics

A-Primer-on-Deep-Learning-in-Genomics

This tutorial is a supplement to the manuscript, A Primer on Deep Learning in Genomics (Nature Genetics, 2018) by James Zou, Mikael Huss, Abubakar Abid, Pejman Mohammadi, Ali Torkamani & Amalio Telentil. Read the accompanying paper here.
A Primer on Deep Learning in Genomics (Nature Genetics, 2018)
Published: 26 November 2018 A primer on deep learning in genomics James Zou, Mikael Huss, Abubakar Abid, Pejman Mohammadi, Ali Torkamani & Amalio Telenti Nature Genetics volume 51, pages12–18 (2019)Cite this article

Abstract

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.

Reff:

[abidlabs-Deep Learning Genomics Primer] (https://github.com/abidlabs/deep-learning-genomics-primer/tree/master0