ICO Amplicon NGS Data Analysis: A Web Tool for Variant Detection in Common High-Risk Hereditary Cancer Genes Analyzed by Amplicon GS Junior Next-Generation Sequencing

• Published in: Human mutation Vol. 35; no. 3; pp. 271 - 277
• Main Authors: Lopez-Doriga, Adriana, Feliubadaló, Lídia, Menéndez, Mireia, Lopez-Doriga, Sergio, Morón-Duran, Francisco D., del Valle, Jesús, Tornero, Eva, Montes, Eva, Cuesta, Raquel, Campos, Olga, Gómez, Carolina, Pineda, Marta, González, Sara, Moreno, Victor, Capellá, Gabriel, Lázaro, Conxi
• Format: Journal Article Publication
• Language: English
• Published: United States Blackwell Publishing Ltd 01.03.2014; Hindawi Limited
• Subjects: Aplicacions de la informàtica; Aspectes genètics; bioinformatic analysis; Bioinformatics; Bioinformàtica; Cancer; Ciències de la salut; Computational Biology - methods; Càncer; Data analysis; DIAGNOSIS; Genes; Genes, Neoplasm; Genetic aspects; Genetic Testing - methods; Genome, Human; Genomics - methods; hereditary cancer; High-Throughput Nucleotide Sequencing - methods; Humans; Informàtica; Internet; Medicina; Mutació (Biologia); Mutation (Biology); mutation analysis; next generation sequencing; User-Computer Interface; variant identification; Àrees temàtiques de la UPC
• ISSN: 1059-7794; 1098-1004
• DOI: 10.1002/humu.22484

ABSTRACT Next‐generation sequencing (NGS) has revolutionized genomic research and is set to have a major impact on genetic diagnostics thanks to the advent of benchtop sequencers and flexible kits for targeted libraries. Among the main hurdles in NGS are the difficulty of performing bioinformatic analysis of the huge volume of data generated and the high number of false positive calls that could be obtained, depending on the NGS technology and the analysis pipeline. Here, we present the development of a free and user‐friendly Web data analysis tool that detects and filters sequence variants, provides coverage information, and allows the user to customize some basic parameters. The tool has been developed to provide accurate genetic analysis of targeted sequencing of common high‐risk hereditary cancer genes using amplicon libraries run in a GS Junior System. The Web resource is linked to our own mutation database, to assist in the clinical classification of identified variants. We believe that this tool will greatly facilitate the use of the NGS approach in routine laboratories. We present a free, accurate and user‐friendly web‐based tool to perform the bioinformatic analysis of data obtained using the GS Junior sequencer for mutational analysis of high‐risk cancer susceptibility genes. Our algorithm detects and filters sequence variants, providing coverage information and allowing the user to customize some of the basic parameters. The identified variants are classified according to our ICO Mutation Database. The software described in the manuscript is available at http://bioinfo.iconcologia.net/aplicNGS.