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


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.

SUBMITTER: Bessiere C 

PROVIDER: S-EPMC11468207 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature

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

Bessière Chloé C   Xue Haoliang H   Guibert Benoit B   Boureux Anthony A   Rufflé Florence F   Viot Julien J   Chikhi Rayan R   Salson Mikaël M   Marchet Camille C   Commes Thérèse T   Gautheret Daniel D  

Genome biology 20241010 1


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 of  ...[more]

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