Galaxy Is a Suitable Bioinformatics Platform for the Molecular Diagnosis of Human Genetic Disorders Using High-Throughput Sequencing Data Analysis: Five Years of Experience in a Clinical Laboratory
Résumé
Abstract Background To date, the usage of Galaxy, an open-source bioinformatics platform, has been reported primarily in research. We report 5 years’ experience (2015 to 2020) with Galaxy in our hospital, as part of the “Assistance Publique–Hôpitaux de Paris” (AP-HP), to demonstrate its suitability for high-throughput sequencing (HTS) data analysis in a clinical laboratory setting. Methods Our Galaxy instance has been running since July 2015 and is used daily to study inherited diseases, cancer, and microbiology. For the molecular diagnosis of hereditary diseases, 6970 patients were analyzed with Galaxy (corresponding to a total of 7029 analyses). Results Using Galaxy, the time to process a batch of 23 samples—equivalent to a targeted DNA sequencing MiSeq run—from raw data to an annotated variant call file was generally less than 2 h for panels between 1 and 500 kb. Over 5 years, we only restarted the server twice for hardware maintenance and did not experience any significant troubles, demonstrating the robustness of our Galaxy installation in conjunction with HTCondor as a job scheduler and a PostgreSQL database. The quality of our targeted exome sequencing method was externally evaluated annually by the European Molecular Genetics Quality Network (EMQN). Sensitivity was mean (SD)% 99 (2)% for single nucleotide variants and 93 (9)% for small insertion-deletions. Conclusion Our experience with Galaxy demonstrates it to be a suitable platform for HTS data analysis with vast potential to benefit patient care in a clinical laboratory setting.