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Integrated analysis of genetic data with R

Overview of attention for article published in Human Genomics, January 2006
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Title
Integrated analysis of genetic data with R
Published in
Human Genomics, January 2006
DOI 10.1186/1479-7364-2-4-258
Pubmed ID
Authors

Jing Hua Zhao, Qihua Tan

Abstract

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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Colombia 1 1%
China 1 1%
Italy 1 1%
Unknown 64 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 28%
Student > Ph. D. Student 14 20%
Student > Master 11 16%
Other 3 4%
Student > Doctoral Student 3 4%
Other 14 20%
Unknown 5 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 48%
Medicine and Dentistry 11 16%
Biochemistry, Genetics and Molecular Biology 8 12%
Computer Science 4 6%
Environmental Science 1 1%
Other 5 7%
Unknown 7 10%