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Journal of Proteomics & Bioinformatics

Journal of Proteomics & Bioinformatics
Open Access

ISSN: 0974-276X

+44 1223 790975

Abstract

GDF: Dealing with High-throughput Genotyping Multiplatform Data for Medical and Population Genetic Applications

Jorge Amigo, Antonio Salas, Javier Costas and Ángel Carracedo

Background: A number of different high throughput genotyping platforms have arisen recently. These platforms generate large amounts of genotyping data which is subsequently processed and stored in public and/or private databases. Both, the variety of platforms employed by the different laboratories and the large amount of data they generate, entail serious problems for data managing in most laboratories. Some public or private software packages available today solve some important needs, but they deal with the data from a point of view that the researcher may probably not share, and no supervision of the results (e.g. genotyping inconsistencies or summaries of the genotyping data) may be performed.

Results: The main goal of the Genotyping Data Filter (GDF) software is to allow the researcher to locally manage large numbers of genotypes generated by the most standard genotyping platforms, obtaining statistics and summaries of the genotyping experiments whilst maintaining their privacy. GDF also allows the user to supervise the data such that the researcher can easily evaluate important parameters, including the proportion of missing data in samples and single nucleotide polymorphisms (SNPs), Hardy-Weinberg equilibrium, etc. Additionally, GDF parses the raw data into different text formats needed as input files in popular software packages frequently used in medical and population genetic applications.

Conclusions: GDF is a Perl program that efficiently process data from various genotyping platforms, allowing researchers to easily inspect their own genotyping data and to parse it for a wide spectrum of well-known specialized analysis software. It has been prepared to be run through a user friendly web interface on the most common cases, but it can also be run as a local script on personal computers, or even supercomputers for very large-scale projects.

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