Git Product home page Git Product logo

gdct's Introduction

Genetic Dissection of Complex Traits

Statistical packages

Zhao JH, Ma J, Huang XN, Gong XF (1994). Practical Guides to Statistical Packages (in Chinese).

SAS, Stata and S-PLUS/R

Zhao JH, Tan Q (2006). Genetic dissection of complex traits in Silico: approaches, problems and solution. Current Bioinformatics 1 (2), 359-369.

Papers

Zhao JH, Tan Q (2006). Integrated analysis of genetic data with R. Human Genomics 2(4), 258-265.

Zhao JH (2007). gap: Genetic Analysis Package. Journal of Statistical Software 23(8), 1-18.

Zhao JH, Luan JA, Tan Q, Loos R, Wareham NJ (2007). Analysis of large genomic data in silico: the EPIC-Norfolk study of obesity. In DS Huang, L Heutte, and M Loog (Eds). Advanced Intelligent Computing Theories and Applications with Aspects of Contemporary Intelligent Computing Techniques, Third International Conference on Intelligent Computing (ICIC), CCIS 2, pp. 781–790, Springer-Verlag Berlin Heidelberg.

Zhao JH, Luan JA, Loos RJF, Wareham N (2011). On genotype-phenotyp association using SAS. Proceedings of the IASTED International Conference July 11 - 13, 2011 Cambridge, United Kingdom, Computational Bioscience (CompBio 2011)

Zhao JH, Luan JA (2012). Mixed modeling with whole genome data. Journal of Probability and Statistics, Volume 2012, 1-16.

Zhao JH, Luan JA, Congdon P (2018). Bayesian linear mixed models with polygenic effects. Journal of Statistical Software 85(6), 1-27.

References

Ahmadi N, Bartholomé J (2022). Genomic Prediction of Complex Traits-Methods and Protocols, Springer, https://link.springer.com/book/10.1007/978-1-0716-2205-6.

Gondro C, van der Werf J, Hayes B (2013). Genome-Wide Association Studies and Genomic Prediction, Springer, https://link.springer.com/book/10.1007/978-1-62703-447-0.

López DAM, López AM, Crossa J (2022). Multivariate Statistical Machine Learning Methods for Genomic Prediction, Springer, https://link.springer.com/content/pdf/10.1007/978-3-030-89010-0.pdf.

Sorensen D, Gianola D (2002). Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics, Springer, https://link.springer.com/book/10.1007/b98952.

Repositories

Zhao JH (2017). vdi.md and SOFTWARE.md. GWAS-2017 (see https://www.physalia-courses.org/courses-workshops/course15/ and GWAS-course for the workshop information), Berlin, https://github.com/jinghuazhao?tab=repositories.

Zhao JH (2019). GitHub repositories: Computational-Statistics, DSA, Mixed-Models, Numerical-Analysis, Omics-analysis, https://github.com/jinghuazhao?tab=repositories.

gdct's People

Contributors

jinghuazhao avatar

Stargazers

 avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.