Published April 25, 2021 | Version 2
Dataset Open

Training material for the SIGU course "Data analysis and interpretation for clinical genomics" (part 1/4)

  • 1. Istituto Giannina Gaslini, IRCCS, Genoa, Italy
  • 2. Istituto Superiore di Sanità, Rome, Italy
  • 3. Ospedale Pediatrico Bambino Gesù, IRCCS, Rome, Italy
  • 4. Albert Ludwigs University, Freiburg, Germany
  • 5. Institute of Genomic Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore, Rome, Italy
  • 6. Sant'Orsola-Malpighi University Hospital, Bologna, Italy

Description

In years 2018-2019, we organized on behalf of the Italian Society of Human Genetics (SIGU) an itinerant Galaxy-based “hands-on-computer” training activity entitled “Data analysis and interpretation for clinical genomics”. This one-day course was offered to participants including clinical doctors, biologists, laboratory technicians and bioinformaticians. Topics covered by the course were NGS data quality check, detection of variants, copy number alterations and runs of homozygosity, annotation and filtering and clinical interpretation of sequencing results.

To meet the constant need for training on basic NGS analysis and interpretation of sequencing data in the clinical setting, we designed an on-line Galaxy-based training resource dedicated to this topic, articulated in presentations and practical assignments by which students will learn how to approach NGS data processing at the level of FASTQ, BAM and VCF files and clinically-oriented examination of variants emerging from sequencing experiments such as whole exomes.

This repository contains datasets required for the online training "Data analysis and interpretation for clinical genomics" available at https://sigu-training.github.io/clinical_genomics/.

Tools used in the training are available at the European Galaxy instance running at https://usegalaxy.eu, which also includes a copy of this repository in the Shared Data Libraries. Files named Fam_*.bam are based on hg38 reference genome; all the other files refer to hg19.

This is part of a 4 dataset submission.

Files

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Additional details

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