Literature DB >> 30139641

Complex-Trait Prediction in the Era of Big Data.

Gustavo de Los Campos1, Ana Ines Vazquez2, Stephen Hsu3, Louis Lello4.   

Abstract

Accurate prediction of complex traits requires using a large number of DNA variants. Advances in statistical and machine learning methodology enable the identification of complex patterns in high-dimensional settings. However, training these highly parameterized methods requires very large data sets. Until recently, such data sets were not available. But the situation is changing rapidly as very large biomedical data sets comprising individual genotype-phenotype data for hundreds of thousands of individuals become available in public and private domains. We argue that the convergence of advances in methodology and the advent of Big Genomic Data will enable unprecedented improvements in complex-trait prediction; we review theory and evidence supporting our claim and discuss challenges and opportunities that Big Data will bring to complex-trait prediction. Published by Elsevier Ltd.

Entities:  

Keywords:  Big Data; GWAS; SNP; complex traits; disease risk; prediction

Mesh:

Year:  2018        PMID: 30139641      PMCID: PMC6150788          DOI: 10.1016/j.tig.2018.07.004

Source DB:  PubMed          Journal:  Trends Genet        ISSN: 0168-9525            Impact factor:   11.639


  31 in total

1.  Accurate prediction of genetic values for complex traits by whole-genome resequencing.

Authors:  Theo Meuwissen; Mike Goddard
Journal:  Genetics       Date:  2010-03-22       Impact factor: 4.562

2.  Semi-parametric genomic-enabled prediction of genetic values using reproducing kernel Hilbert spaces methods.

Authors:  Gustavo De los Campos; Daniel Gianola; Guilherme J M Rosa; Kent A Weigel; José Crossa
Journal:  Genet Res (Camb)       Date:  2010-08       Impact factor: 1.588

3.  Personal genomes: The case of the missing heritability.

Authors:  Brendan Maher
Journal:  Nature       Date:  2008-11-06       Impact factor: 49.962

4.  Common SNPs explain a large proportion of the heritability for human height.

Authors:  Jian Yang; Beben Benyamin; Brian P McEvoy; Scott Gordon; Anjali K Henders; Dale R Nyholt; Pamela A Madden; Andrew C Heath; Nicholas G Martin; Grant W Montgomery; Michael E Goddard; Peter M Visscher
Journal:  Nat Genet       Date:  2010-06-20       Impact factor: 38.330

Review 5.  Epistasis--the essential role of gene interactions in the structure and evolution of genetic systems.

Authors:  Patrick C Phillips
Journal:  Nat Rev Genet       Date:  2008-11       Impact factor: 53.242

6.  UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age.

Authors:  Cathie Sudlow; John Gallacher; Naomi Allen; Valerie Beral; Paul Burton; John Danesh; Paul Downey; Paul Elliott; Jane Green; Martin Landray; Bette Liu; Paul Matthews; Giok Ong; Jill Pell; Alan Silman; Alan Young; Tim Sprosen; Tim Peakman; Rory Collins
Journal:  PLoS Med       Date:  2015-03-31       Impact factor: 11.069

7.  Improved Genetic Profiling of Anthropometric Traits Using a Big Data Approach.

Authors:  Oriol Canela-Xandri; Konrad Rawlik; John A Woolliams; Albert Tenesa
Journal:  PLoS One       Date:  2016-12-15       Impact factor: 3.240

8.  Prediction of years of life after diagnosis of breast cancer using omics and omic-by-treatment interactions.

Authors:  Agustín González-Reymúndez; Gustavo de Los Campos; Lucía Gutiérrez; Sophia Y Lunt; Ana I Vazquez
Journal:  Eur J Hum Genet       Date:  2017-03-08       Impact factor: 4.246

9.  Incorporating Genetic Heterogeneity in Whole-Genome Regressions Using Interactions.

Authors:  Gustavo de Los Campos; Yogasudha Veturi; Ana I Vazquez; Christina Lehermeier; Paulino Pérez-Rodríguez
Journal:  J Agric Biol Environ Stat       Date:  2015-11-09       Impact factor: 1.524

10.  Increased Proportion of Variance Explained and Prediction Accuracy of Survival of Breast Cancer Patients with Use of Whole-Genome Multiomic Profiles.

Authors:  Ana I Vazquez; Yogasudha Veturi; Michael Behring; Sadeep Shrestha; Matias Kirst; Marcio F R Resende; Gustavo de Los Campos
Journal:  Genetics       Date:  2016-04-29       Impact factor: 4.562

View more
  15 in total

Review 1.  Mouse Systems Genetics as a Prelude to Precision Medicine.

Authors:  Hao Li; Johan Auwerx
Journal:  Trends Genet       Date:  2020-02-06       Impact factor: 11.639

2.  Boosting GWAS using biological networks: A study on susceptibility to familial breast cancer.

Authors:  Héctor Climente-González; Christine Lonjou; Fabienne Lesueur; Dominique Stoppa-Lyonnet; Nadine Andrieu; Chloé-Agathe Azencott
Journal:  PLoS Comput Biol       Date:  2021-03-18       Impact factor: 4.475

Review 3.  Hunting for genes that shape human faces: Initial successes and challenges for the future.

Authors:  Seth M Weinberg; Jasmien Roosenboom; John R Shaffer; Mark D Shriver; Joanna Wysocka; Peter Claes
Journal:  Orthod Craniofac Res       Date:  2019-05       Impact factor: 1.826

Review 4.  What Can We Learn About Drug Safety and Other Effects in the Era of Electronic Health Records and Big Data That We Would Not Be Able to Learn From Classic Epidemiology?

Authors:  Ali Zarrinpar; Ting-Yuan David Cheng; Zhiguang Huo
Journal:  J Surg Res       Date:  2019-10-22       Impact factor: 2.192

5.  Accurate and Scalable Construction of Polygenic Scores in Large Biobank Data Sets.

Authors:  Sheng Yang; Xiang Zhou
Journal:  Am J Hum Genet       Date:  2020-04-23       Impact factor: 11.025

6.  Genetic correlations between traits associated with hyperuricemia, gout, and comorbidities.

Authors:  Richard J Reynolds; M Ryan Irvin; S Louis Bridges; Hwasoon Kim; Tony R Merriman; Donna K Arnett; Jasvinder A Singh; Nicholas A Sumpter; Alexa S Lupi; Ana I Vazquez
Journal:  Eur J Hum Genet       Date:  2021-02-26       Impact factor: 5.351

7.  Robust modeling of additive and nonadditive variation with intuitive inclusion of expert knowledge.

Authors:  Ingeborg Gullikstad Hem; Maria Lie Selle; Gregor Gorjanc; Geir-Arne Fuglstad; Andrea Riebler
Journal:  Genetics       Date:  2021-03-31       Impact factor: 4.562

Review 8.  The Genetics of Neuropathic Pain from Model Organisms to Clinical Application.

Authors:  Margarita Calvo; Alexander J Davies; Harry L Hébert; Greg A Weir; Elissa J Chesler; Nanna B Finnerup; Roy C Levitt; Blair H Smith; G Gregory Neely; Michael Costigan; David L Bennett
Journal:  Neuron       Date:  2019-11-20       Impact factor: 17.173

9.  Genomic Prediction of 16 Complex Disease Risks Including Heart Attack, Diabetes, Breast and Prostate Cancer.

Authors:  Louis Lello; Timothy G Raben; Soke Yuen Yong; Laurent C A M Tellier; Stephen D H Hsu
Journal:  Sci Rep       Date:  2019-10-25       Impact factor: 4.379

10.  Exploring the possibility of predicting human head hair greying from DNA using whole-exome and targeted NGS data.

Authors:  Ewelina Pośpiech; Magdalena Kukla-Bartoszek; Joanna Karłowska-Pik; Piotr Zieliński; Anna Woźniak; Michał Boroń; Michał Dąbrowski; Magdalena Zubańska; Agata Jarosz; Tomasz Grzybowski; Rafał Płoski; Magdalena Spólnicka; Wojciech Branicki
Journal:  BMC Genomics       Date:  2020-08-05       Impact factor: 3.969

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.