TALC: Transcript-level Aware Long-read Correction | Zendy

Lucile Broseus | Zendy; Aubin Thomas | Zendy; Andrew J. Oldfield | Zendy; Dany Séverac | Zendy; Emeric Dubois | Zendy; William Ritchie | Zendy

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TALC: Transcript-level Aware Long-read Correction

Author(s) -

Lucile Broseus,

Aubin Thomas,

Andrew J. Oldfield,

Dany Séverac,

Emeric Dubois,

William Ritchie

Publication year - 2020

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa634

Subject(s) - computer science , talc , transcriptome , de bruijn graph , de bruijn sequence , rna seq , sequence assembly , computational biology , graph , data mining , gene , biology , theoretical computer science , genetics , gene expression , mathematics , paleontology , discrete mathematics

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.

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