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 largescale DNA-sequencing projects. © The Author 2010. Published by Oxford University Press. All rights reserved.

GAMES identifies and annotates mutations in next-generation sequencing projects

SANA, Maria Elena;PALATINI, Jeffrej;GALASSO, Marco;VOLINIA, Stefano
2011

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 largescale DNA-sequencing projects. © The Author 2010. Published by Oxford University Press. All rights reserved.
2011
Sana, Maria Elena; Iascone, M; Marchetti, D; Palatini, Jeffrej; Galasso, Marco; Volinia, Stefano
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1532101
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