ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues.

Détails

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Etat: Public
Version: Final published version
ID Serval
serval:BIB_66C286C8031F
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues.
Périodique
Genome Biology
Auteur⸱e⸱s
Mangul S., Yang H.T., Strauli N., Gruhl F., Porath H.T., Hsieh K., Chen L., Daley T., Christenson S., Wesolowska-Andersen A., Spreafico R., Rios C., Eng C., Smith A.D., Hernandez R.D., Ophoff R.A., Santana J.R., Levanon E.Y., Woodruff P.G., Burchard E., Seibold M.A., Shifman S., Eskin E., Zaitlen N.
ISSN
1474-760X (Electronic)
ISSN-L
1474-7596
Statut éditorial
Publié
Date de publication
2018
Peer-reviewed
Oui
Volume
19
Numéro
1
Pages
36
Langue
anglais
Résumé
High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki .

Pubmed
Web of science
Open Access
Oui
Création de la notice
22/03/2018 20:17
Dernière modification de la notice
20/08/2019 15:22
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