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aaronkw committed Nov 20, 2019
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Expand Up @@ -7,7 +7,9 @@ Introduction

DeepSEA is a deep learning-based algorithmic framework for predicting the chromatin effects of sequence alterations with single nucleotide sensitivity. DeepSEA can accurately predict the epigenetic state of a sequence, including transcription factors binding, DNase I sensitivities and histone marks in multiple cell types, and further utilize this capability to predict the chromatin effects of sequence variants and prioritize regulatory variants.

The current version of DeepSEA, nicknamed '**Beluga**', can predict **2002** chromatin features.
The current version of DeepSEA, nicknamed '**Beluga**', can predict **2002** chromatin features. Beluga is described in:

Jian Zhou, Chandra L. Theesfeld, Kevin Yao, Kathleen M. Chen, Aaron K. Wong, and Olga G. Troyanskaya, **Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk**. Nature Genetics (2018).

DeepSEA is described in the following manuscript:

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