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Integrated analysis of genetic data with R

Genetic data are now widely available. There is, however, an apparent lack of concerted effort to produce software systems for statistical analysis of genetic data compared with other fields of statistics. It is often a tremendous task for end-users to tailor them for particular data, especially whe...

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Detalles Bibliográficos
Autores principales: Zhao, Jing Hua, Tan, Qihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3525150/
https://www.ncbi.nlm.nih.gov/pubmed/16460651
http://dx.doi.org/10.1186/1479-7364-2-4-258
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author Zhao, Jing Hua
Tan, Qihua
author_facet Zhao, Jing Hua
Tan, Qihua
author_sort Zhao, Jing Hua
collection PubMed
description Genetic data are now widely available. There is, however, an apparent lack of concerted effort to produce software systems for statistical analysis of genetic data compared with other fields of statistics. It is often a tremendous task for end-users to tailor them for particular data, especially when genetic data are analysed in conjunction with a large number of covariates. Here, R http://www.r-project.org, a free, flexible and platform-independent environment for statistical modelling and graphics is explored as an integrated system for genetic data analysis. An overview of some packages currently available for analysis of genetic data is given. This is followed by examples of package development and practical applications. With clear advantages in data management, graphics, statistical analysis, programming, internet capability and use of available codes, it is a feasible, although challenging, task to develop it into an integrated platform for genetic analysis; this will require the joint efforts of many researchers.
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spelling pubmed-35251502012-12-19 Integrated analysis of genetic data with R Zhao, Jing Hua Tan, Qihua Hum Genomics Software Review Genetic data are now widely available. There is, however, an apparent lack of concerted effort to produce software systems for statistical analysis of genetic data compared with other fields of statistics. It is often a tremendous task for end-users to tailor them for particular data, especially when genetic data are analysed in conjunction with a large number of covariates. Here, R http://www.r-project.org, a free, flexible and platform-independent environment for statistical modelling and graphics is explored as an integrated system for genetic data analysis. An overview of some packages currently available for analysis of genetic data is given. This is followed by examples of package development and practical applications. With clear advantages in data management, graphics, statistical analysis, programming, internet capability and use of available codes, it is a feasible, although challenging, task to develop it into an integrated platform for genetic analysis; this will require the joint efforts of many researchers. BioMed Central 2006-01-01 /pmc/articles/PMC3525150/ /pubmed/16460651 http://dx.doi.org/10.1186/1479-7364-2-4-258 Text en Copyright ©2006 Henry Stewart Publications
spellingShingle Software Review
Zhao, Jing Hua
Tan, Qihua
Integrated analysis of genetic data with R
title Integrated analysis of genetic data with R
title_full Integrated analysis of genetic data with R
title_fullStr Integrated analysis of genetic data with R
title_full_unstemmed Integrated analysis of genetic data with R
title_short Integrated analysis of genetic data with R
title_sort integrated analysis of genetic data with r
topic Software Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3525150/
https://www.ncbi.nlm.nih.gov/pubmed/16460651
http://dx.doi.org/10.1186/1479-7364-2-4-258
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