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

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.

Identification of novel SNPs in differentially expressed genes and its association with horn cancer of Bos indicus bullocks by next-generation sequencing

“…This approach will be effective in quickly assessing the spectrum of SNPs in important genes or genomic regions affecting HC. Similar observations were also reported in other studies related to SNP discoveries in variety of diseases (Cheng et al 2010 ; Elliott et al 2012 ; Junemann et al 2012 ; Lopez-Doriga et al 2014 ). Our approach not only identify SNPs in exons, but also SNPs located in introns and up- and downstream regions, which have been recognised more important as playing important roles in gene regulation and diseases (Jaillon et al 2008 ).…”

High-frequency, low-coverage “false positives” mutations may be true in GS Junior sequencing studies

“…The first study used some web tools, including BWA-MEM, Cutadapt, VarScan, and a series of functions and filters that they programmed. These authors suggested thresholds for optimal accuracy and recommended a 38-fold coverage range to detect heterozygous alleles with a minimum 25% allele frequency for a sensitivity of 99.9% 7 . The second study used Amplicon variant analyser software.…”