Transipedia.org: k-mer-based exploration of large RNA sequencing datasets and application to cancer data

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Abstract

Indexing techniques relying on k-mers have proven effective in searching for RNA sequences across thousands of RNA-seq libraries, but without enabling direct RNA quantification. We show here that arbitrary RNA sequences can be quantified in seconds through their decomposition into k-mers, with a precision akin to that of conventional RNA quantification methods. Using an index of the Cancer Cell Line Encyclopedia (CCLE) collection consisting of 1019 RNA-seq samples, we show that k-mer indexing offers a powerful means to reveal non-reference sequences, and variant RNAs induced by specific gene alterations, for instance in splicing factors.

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Bessière, C., Xue, H., Guibert, B., Boureux, A., Rufflé, F., Viot, J., … Gautheret, D. (2024). Transipedia.org: k-mer-based exploration of large RNA sequencing datasets and application to cancer data. Genome Biology, 25(1). https://doi.org/10.1186/s13059-024-03413-5

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