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Start of funding 01.07.2017
Detection of rare splicing events in RNA-seq data
Prof. Dr. Julien Gagneur
Technische Universität München
Department of Informatics (I12)
Prof. Dr. Lars Steinmetz
Stanford University
Stanford Genome Technology Center - Dept. of Biochemistry
Aberrant splicing has long been recognized as a major cause of Mendelian disorders.
Combined with the rapid advances in sequencing technologies and the immense growth of
available RNA-seq samples (eg. GTEx project) a need is present for a new methodology to
model the data. Through the collaboration of two complementary labs – the Gagneur lab
(Computational biology, TUM) and the Steinmetz lab (Genome Technology Center, Stanford)
– we aim to improve the diagnostics in rare Mendelian disorders by developing an enhanced
detection algorithm of disease causing aberrant splicing events. One part of the project is to
share the algorithm with the whole rare disease community as an R/Bioconductor package to
improve the diagnostics of rare disease patients.
Final report:
The aim of this visit was to develop a new tool to detect aberrant splicing events within RNA-seq data. Through close collaborations with the Steinmetz lab in Stanford, CA, we developed a software (an R package) called FraseR (Find Rare Aberrant Splicing Events in RNA-seq). Initial benchmarks of FraseR on sequencing data from rare disease cohorts as well as RNA-seq data from the GTEx consortium (https://gtexportal.org) show the benefit of an enhanced and optimized algorithm for outlier detection in comparison to state-of-the-art methods. Algorithmic results and candidate pathogenic splicing events detected with FraseR were presented during a talk by Christian Mertes at the annual meeting of the American Society of Human Genetics in October 2018. Further testing and optimization of the algorithm is on-going before publications. Altogether, the collaboration between the Gagneur lab and the Steinmetz lab was successful and we plan to continue working together. We recently obtained funding for a common project (BMBF funded project “mitoNET 3”).
Presentation:
Mertes C., F. Brechtmann, J Gagneur et al.; OUTRIDER and FraseR: Statistical methods to detect aberrant events in RNA sequencing data; (Talk #258). Presented at the 68th Annual Meeting of The American Society of Human Genetics, October 20, 2018, San Diego, California.