Kmerator Suite: design of specific k -mer signatures and automatic metadata discovery in large RNA-seq datasets - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue NAR Genomics and Bioinformatics Année : 2021

Kmerator Suite: design of specific k -mer signatures and automatic metadata discovery in large RNA-seq datasets

Résumé

The huge body of publicly available RNA-sequencing (RNA-seq) libraries is a treasure of functional information allowing to quantify the expression of known or novel transcripts in tissues. However, transcript quantification commonly relies on alignment methods requiring a lot of computational resources and processing time, which does not scale easily to large datasets. K-mer decomposition constitutes a new way to process RNA-seq data for the identification of transcriptional signatures, as k-mers can be used to quantify accurately gene expression in a less resource-consuming way. We present the Kmerator Suite, a set of three tools designed to extract specific k-mer signatures, quantify these k-mers into RNA-seq datasets and quickly visualize large dataset characteristics. The core tool, Kmerator, produces specific k-mers for 97% of human genes, enabling the measure of gene expression with high accuracy in simulated datasets. KmerExploR, a direct application of Kmerator, uses a set of predictor gene-specific k-mers to infer metadata including library protocol, sample features or contaminations from RNA-seq datasets. KmerExploR results are visualized through a user-friendly interface. Moreover, we demonstrate that the Kmerator Suite can be used for advanced queries targeting known or new biomarkers such as mutations, gene fusions or long non-coding RNAs for human health applications.
Fichier principal
Vignette du fichier
kmerator_suite_NAR_pdf_editor.pdf (3.89 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte
Licence

Dates et versions

hal-04147535 , version 1 (30-06-2023)

Licence

Identifiants

Citer

Sébastien Riquier, Chloé Bessiere, Benoit Guibert, Anne-Laure Bouge, Anthony Boureux, et al.. Kmerator Suite: design of specific k -mer signatures and automatic metadata discovery in large RNA-seq datasets. NAR Genomics and Bioinformatics, 2021, 3 (3), pp.lqab058. ⟨10.1093/nargab/lqab058⟩. ⟨hal-04147535⟩
17 Consultations
9 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More