Small-scale SNP detection experiments generate massive amounts of data, much of which can potentially be captured and analyzed in an automated fashion. However, no current software tool exists to comprehensively capture and m
anage SNP discovery data. Instead, most data management is done by a combination of spreadsheets, systematic file naming conventions, and the laboratory notebook. Manual record keeping involves a large investment of researchers' time and effort, and represents the single biggest potential source of experimental error.
We have created a software tool that encapsulates the laboratory workflow and data
management requirements for a small-scale SNP detection project. The software consists of a GUI; a w
orkflow automation manager; extensible interfaces to external SNP detection and display programs; and a SNP informatics management system. Object oriented design allows modular implementation of all major SNP detection protocols. Additionally, DNA sample
source tracking and analysis modules such as statistical and clustering algorithms allow the user to easily identify sample groups which contain the same variant for epidemiological studies.
The proposed software closely replicates the steps invo
lved in a SNP detection experiment. The initial design of the system is based upon a workflow used in SNP detection experiments using gene resequencing protocols. Data required for record-keeping and analyses is tracked using graphical user interfaces tha
t duplicate as closely as possible the experimental devices familiar to the researcher where appropriate and automated collection directly from the experimental detection devices where possible. The goal is to create a system which is as unobtrusive and s
imple to use as possible.
The SNP LIMS software is distributed as open source software, free of charge to academics and non-profit researchers.
Direct comments and questions to mbarenbo.gmu.edu
Last updated