专利检索 ap:("Illumina Software, Inc." OR "Illumina, Inc." OR "Illumina Australia Pty Ltd" OR "Illumina Netherlands BV" OR "Illumina France SARL" OR "Illumina Cambridge Limited") AND inv:"Francois Aguet" 第 1 页

1.

发明公开
MACHINE LEARNING PIPELINE FOR GENOME-WIDE ASSOCIATION STUDIES 审中-公开

公开(公告)号：US20240120024A1

公开(公告)日：2024-04-11

申请号：US18483313

申请日：2023-10-09

申请人： Illumina Software, Inc. , Illumina, Inc. , Illumina Australia Pty Ltd , Illumina Netherlands BV , Illumina France SARL , Illumina Cambridge Limited

发明人： Yair Field , Jacob Christopher Ulirsch , Cinzia Malangone , Miguel Madrid-Mencia , Geoffrey Nilsen , Pam Tang Cheng , Ileena Mitra , Petko Plamenov Fiziev , Sabrina Rashid , Anthonius Petrus Nicolaas de Boer , Pierrick Wainschtein , Vlad Mihai Sima , Francois Aguet , Kai-How Farh

IPC分类号： G16B20/00 , G16B40/20

CPC分类号： G16B20/00 , G16B40/20

摘要： Genome-wide association studies may allow for detection of variants that are statistically significantly associated with disease risk. However, inferring which are the genes underlying these variant associations may be difficult. The presently disclosed approaches utilize machine learning techniques to predict genes from genome-wide association study summary statistics that substantially improves causal gene identification in terms of both precision and recall compared to other techniques.