Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease

Huang, Yi-Fei, Siepel, Adam (June 2019) Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease. Genome Research, 29 (8). pp. 1310-1321. ISSN 10889051 (ISSN)

[img] PDF
2019.Huang.LASSIE.pdf - Published Version
Restricted to Registered users only until 28 December 2019.

Download (5Mb)
URL: https://www.ncbi.nlm.nih.gov/pubmed/31249063
DOI: 10.1101/441337

Abstract

A central challenge in human genomics is to understand the cellular, evolutionary, and clinical significance of genetic variants. Here we introduce a unified population-genetic and machine-learning model, called Linear Allele-Specific Selection InferencE (LASSIE), for estimating the fitness effects of all potential single-nucleotide variants, based on polymorphism data and predictive genomic features. We applied LASSIE to 51 high-coverage genome sequences annotated with 33 genomic features, and constructed a map of allele-specific selection coefficients across all protein-coding sequences in the human genome. We show that this map is informative about both human evolution and disease.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > genomics and proteomics > computers > computer software
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > single nucleotide polymorphism
CSHL Authors:
Communities: CSHL labs > Siepel lab
Depositing User: Matthew Dunn
Date: 27 June 2019
Date Deposited: 27 Nov 2018 16:56
Last Modified: 03 Sep 2019 20:06
Related URLs:
URI: http://repository.cshl.edu/id/eprint/37482

Actions (login required)

Administrator's edit/view item Administrator's edit/view item
CSHL HomeAbout CSHLResearchEducationNews & FeaturesCampus & Public EventsCareersGiving