 Hello, my name is Conchilathro, I am the director of the molecular diagnosis unit of the dietary cancer program. We work at the Catalan Institute of Oncology, ECO, a public comprehensive cancer center leading in cancer care in Catalonia, Spain. Today we are here to present you our paper entitled ECO-amplicon NGS data analysis, a web tool for variant detection in common high risk and dietary cancer gene, analysed by Amplicon GS Junior Next Generation Sequencing. The past two years have seen an enormous shift in the field of genetic testing, due mainly to the implementation of next generation sequencing and GS, methodologies in medium-scale or bench-stop sequencers. One of the critical steps when using these instruments is the interpretation of the enormous quantity of data, which underlines the need of bioinformatic tools for better interpret results and to facilitate the implementation of NGS in routine laboratories. Since the acquisition of GS Junior Sequencer in our unit, we developed an NGS workflow for the molecular diagnosis of dietary cancer syndroms. We have refined the analysis pipeline and now we present a free web tool that allows for others users to run the bioinformatic analysis of their own data. Our algorithm detects and filters sequence variants, providing coverage information and allowing the user to customize all some of the basic parameters. The identified variants are classified according to our e-commutation database, providing a putative pathogenicity classification of all variants identified in our call of patients. We hope that our tool will provide invaluable support to use it of this platform for dietary cancer syndroms. In this video, we show all the steps of our pipeline with a special emphasis in the bioinformatic analysis. I hope you will enjoy it. The web tool has been designed to analyze data obtained from multiplicom libraries run in NGS Junior. These are commercial multiplex-amplicom libraries that target the high-gross genes for the most common dietary cancer syndroms. In order to run the bioinformatic data analysis, we should connect to the web application address. Once it's open, select the gene analysis required and upload parameters and data. First, fill in the run name, then upload the midge as a text file. Indicate the commercial key views and choose the thresholds for coverage and variant filtering. Finally, upload read data in FASTA and quality file. Enter the email address to receive the results notification and press the run button and wait for the email. The bioinformatics pipeline includes different steps as represented in this figure. Reads uploaded by the web tool are preprocessed, the multiplexed and trimmed. Then, reads are aligned by BWA-MEM algorithm. From the alignment file, bar scan is used for variant calling and by our commands, variant and coverage reports are generated and reaped to download by users. The user receives a zip file with the alignments and the report files. We'll now show the main ones. The variant report is a comma separated file listing the variants that remain after filtering. Its variant is described by its position, base change and several parameters, including, if already in our eco database its putative pathogenicity. The Amplicon Meet Coverage file lists the main coverage for each Amplicon and Meet, which are also represented after normalization to indicate putative large rearrangements. Variants can be assessed by looking at the alignments on any free visualizer like IGV. Here we show a single nucleotide substitution and here a four base pair delition. Thank you for your attention. For any question you can contact us by the web tool desk.