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

Authors :
Chloé Bessière
Haoliang Xue
Benoit Guibert
Anthony Boureux
Florence Rufflé
Julien Viot
Rayan Chikhi
Mikaël Salson
Camille Marchet
Thérèse Commes
Daniel Gautheret
Source :
Genome Biology, Vol 25, Iss 1, Pp 1-16 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

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.

Details

Language :
English
ISSN :
1474760X
Volume :
25
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Genome Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.609a092c730485c832b8c973417638f
Document Type :
article
Full Text :
https://doi.org/10.1186/s13059-024-03413-5