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
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% |