TALC: Transcription Aware Long Read Correction

TALC: Transcription Aware Long Read Correction  

TALC:转录组 意识 长读校正

Lucile Broseus, Aubin Thomas, Andrew J. Oldfield, Dany Severac, Emeric Dubois, William Ritchie

doi: https://doi.org/10.1101/2020.01.10.901728

Now published in Bioinformatics doi: 10.1093/bioinformatics/btaa634

 

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ABSTRACT

Motivation Long-read sequencing technologies are invaluable for determining complex RNA transcript architectures but are error-prone. Numerous “hybrid correction” algorithms have been developed for genomic data that correct long reads by exploiting the accuracy and depth of short reads sequenced from the same sample. These algorithms are not suited for correcting more complex transcriptome sequencing data.

Results We have created a novel algorithm called TALC (Transcription Aware Long Read Correction) which models changes in RNA expression and isoform representation in a weighted De-Bruijn graph to correct long reads from transcriptome studies. We show that transcription aware correction by TALC improves the accuracy of the whole spectrum of downstream RNA-seq applications and is thus necessary for transcriptome analyses that use long read technology.

Availability and Implementation TALC is implemented in C++ and available at https://gitlab.igh.cnrs.fr/lbroseus/TALC.

Contact william.ritchie{at}igh.cnrs.fr