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Sana ME, Iascone M, Marchetti D, et al. GAMES identifies and annotates mutations in next-generation sequencing projects. Bioinformatics. 2010;27(1):9-13doi: 10.1093/bioinformatics/btq603.
Sana, M. E., Iascone, M., Marchetti, D., Palatini, J., Galasso, M., & Volinia, S. (2011). GAMES identifies and annotates mutations in next-generation sequencing projects. Bioinformatics (Oxford, England), 27(1), 9-13. https://doi.org/10.1093/bioinformatics/btq603
Sana, Maria Elena, et al. "GAMES identifies and annotates mutations in next-generation sequencing projects." Bioinformatics (Oxford, England) vol. 27,1 (2011): 9-13. doi: https://doi.org/10.1093/bioinformatics/btq603
Sana ME, Iascone M, Marchetti D, Palatini J, Galasso M, Volinia S. GAMES identifies and annotates mutations in next-generation sequencing projects. Bioinformatics. 2011 Jan 01;27(1):9-13. doi: 10.1093/bioinformatics/btq603. Epub 2010 Oct 22. PMID: 20971986.
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Bioinformatics. 2011 Jan 01;27(1):9-13. doi: 10.1093/bioinformatics/btq603. Epub 2010 Oct 22.

GAMES identifies and annotates mutations in next-generation sequencing projects.

Bioinformatics (Oxford, England)

Maria Elena Sana, Maria Iascone, Daniela Marchetti, Jeff Palatini, Marco Galasso, Stefano Volinia

Affiliations

  1. DAMA, Data Mining for Analysis of DNA, Department of Morphology and Embryology and TecnoPolo for Life Sciences, University of Ferrara, Ferrara, Italy.

PMID: 20971986 DOI: 10.1093/bioinformatics/btq603

Abstract

MOTIVATION: Next-generation sequencing (NGS) methods have the potential for changing the landscape of biomedical science, but at the same time pose several problems in analysis and interpretation. Currently, there are many commercial and public software packages that analyze NGS data. However, the limitations of these applications include output which is insufficiently annotated and of difficult functional comprehension to end users.

RESULTS: We developed GAMES (Genomic Analysis of Mutations Extracted by Sequencing), a pipeline aiming to serve as an efficient middleman between data deluge and investigators. GAMES attains multiple levels of filtering and annotation, such as aligning the reads to a reference genome, performing quality control and mutational analysis, integrating results with genome annotations and sorting each mismatch/deletion according to a range of parameters. Variations are matched to known polymorphisms. The prediction of functional mutations is achieved by using different approaches. Overall GAMES enables an effective complexity reduction in large-scale DNA-sequencing projects.

AVAILABILITY: GAMES is available free of charge to academic users and may be obtained from http://aqua.unife.it/GAMES.

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