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.
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.
Authors: Alex H Ramos; Lee Lichtenstein; Manaswi Gupta; Michael S Lawrence; Trevor J Pugh; Gordon Saksena; Matthew Meyerson; Gad Getz Journal: Hum Mutat Date: 2015-03-16 Impact factor: 4.878
Authors: Maria Fischer; Rene Snajder; Stephan Pabinger; Andreas Dander; Anna Schossig; Johannes Zschocke; Zlatko Trajanoski; Gernot Stocker Journal: PLoS One Date: 2012-08-01 Impact factor: 3.240
Authors: Yan W Asmann; Sumit Middha; Asif Hossain; Saurabh Baheti; Ying Li; High-Seng Chai; Zhifu Sun; Patrick H Duffy; Ahmed A Hadad; Asha Nair; Xiaoyu Liu; Yuji Zhang; Eric W Klee; Krishna R Kalari; Jean-Pierre A Kocher Journal: Bioinformatics Date: 2011-11-15 Impact factor: 6.937