RT Journal Article
SR Electronic
T1 AERON: Transcript quantification and gene-fusion detection using long reads
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.01.27.921338
DO 10.1101/2020.01.27.921338
A1 Mikko Rautiainen
A1 Dilip A Durai
A1 Ying Chen
A1 Lixia Xin
A1 Hwee Meng Low
A1 Jonathan Göke
A1 Tobias Marschall
A1 Marcel H. Schulz
YR 2020
UL http://biorxiv.org/content/early/2020/01/27/2020.01.27.921338.abstract
AB Single-molecule sequencing technologies have the potential to improve measurement and analysis of long RNA molecules expressed in cells. However, analysis of error-prone long RNA reads is a current challenge. We present AERON for the estimation of transcript expression and prediction of gene-fusion events. AERON uses an efficient read-to-graph alignment algorithm to obtain accurate estimates for noisy reads. We demonstrate AERON to yield accurate expression estimates on simulated and real datasets. It is the first method to reliably call gene-fusion events from long RNA reads. Sequencing the K562 transcriptome, we used AERON and found known as well as novel gene-fusion events.