Title
Recommended Citation
August 1, 2013.
Abstract
In a time of increasingly efficient technology and data production, scientists are producing data faster than it can be analyzed. Therefore, user accessibility to data analysis is becoming more and more critical. In general, researchers have a set of raw data and want an efficient means to their final analysis. A package serves as that means by creating a set of functions and making them accessible to the user. Often, a user has a small piece of code to run (a single R script, for example), and that script requires the use of certain functions, which are contained in a package. So a user can run an analysis, receive a set of reports, and never actually touch the package or its functions. The objective of my project is to create one such user-friendly package in R specific to the field of population genetics. The typical user will have a set of DNA data for a population of individuals from a given species. In installing this package, called eiaGenetics, a user can run analyses specific to their research in population genetics. All they have to do is input their raw data, have the package installed, and run the analysis. As an extension to my project, I wrote the code for one such analysis, which used functions implicit in the eiaGenetics package.
Disciplines
Computational Biology | Computational Engineering | Genetics
Mentor
Eric Archer
Lab site
National Oceanic and Atmospheric Administration Southwest Fisheries Science Center (NOAA SWFSC)
Funding Acknowledgement
This material is based upon work supported by the S.D. Bechtel, Jr. Foundation and by the National Science Foundation under Grant No. 0952013. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the S.D. Bechtel, Jr. Foundation or the National Science Foundation. This project has also been made possible with support of the National Marine Sanctuary Foundation. The STAR program is administered by the Cal Poly Center for Excellence in Science and Mathematics Education (CESaME) on behalf of the California State University (CSU).
URL: https://digitalcommons.calpoly.edu/star/166