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bioRxiv · 10.1101/2025.03.10.642333

Detecting aberrant splicing events in short-read RNA-seq with SAMI, an UMI-aware Nextflow pipeline

Mareschal, S.·Wucher, V.·Huet, S.·Leonce, C.·Chabane, K.·Hayette, S.·Bringuier, P.-P.·Pinson, S.·Barritault, M.·Bardel, C.
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Abstract

SummaryDespite RNA-sequencing solutions have existed for 15 years, successfully replacing micro-arrays for gene expression profiling, their potential to analyse splicing is still to be achieved in clinical settings. Powerful tools were developed to quantify known iso-forms, to compare sample groups or to identify outliers in large datasets, but most fail to address the most common situation in routine diagnostics: identifying non-recurring events in low-dimension data. To fill this gap, we developed SAMI (Splicing Analysis with Molecular Indexes), an UMI-aware pipeline focusing on splicing events which differ from provided annotation. The ability of SAMI and concurrent software to detect intragenic splicing aberrations and gene fusions was assessed, both on real data from a commercial control sample and simulated data generated with ASimulatoR. Availability and ImplementationNextflow pipeline and Singularity container recipe freely available under GPL 3 licence at https://github.com/HCL-HUBL/SAMI Contactsylvain.mareschal@chu-lyon.fr

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Mareschal, S., Wucher, V., Huet, S., Leonce, C., Chabane, K., Hayette, S., Bringuier, P.-P., Pinson, S., Barritault, M., Bardel, C.. 2025-03-13. Detecting aberrant splicing events in short-read RNA-seq with SAMI, an UMI-aware Nextflow pipeline. https://doi.org/10.1101/2025.03.10.642333

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