Machine learning based disease prediction from genotype data-Reference-Cited by-同舟云学术

Machine learning based disease prediction from genotype data

Published:2021-07-01 Issue:8 Volume:402 Page:871-885
ISSN:1437-4315
Container-title:Biological Chemistry
language:en
Short-container-title:

Author:

Katsaouni Nikoletta¹^ORCID,Tashkandi Araek²,Wiese Lena³,Schulz Marcel H.¹⁴⁵

Affiliation:

1. Institute for Cardiovascular Regeneration , Goethe University , 60590 Frankfurt am Main , Germany

2. Institute of Computer Sciences and Engineering , University of Jeddah , 21959 Jeddah , Saudi Arabia

3. Institute of Computer Science , Goethe University , 60629 Frankfurt am Main , Germany

4. German Center for Cardiovascular Research (DZHK) , Partner Site RheinMain , 60590 Frankfurt am Main , Germany

5. Cardio-Pulmonary Institute , Goethe University Hospital , Frankfurt am Main , Germany

Abstract

Abstract Using results from genome-wide association studies for understanding complex traits is a current challenge. Here we review how genotype data can be used with different machine learning (ML) methods to predict phenotype occurrence and severity from genotype data. We discuss common feature encoding schemes and how studies handle the often small number of samples compared to the huge number of variants. We compare which ML methods are being applied, including recent results using deep neural networks. Further, we review the application of methods for feature explanation and interpretation.

Publisher

Walter de Gruyter GmbH

Subject

Clinical Biochemistry,Molecular Biology,Biochemistry

Link

https://www.degruyter.com/document/doi/10.1515/hsz-2021-0109/pdf

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