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Evaluation of tools for long read RNA-seq splice-aware alignment
Author(s) -
Krešimir Križanović,
Amina Echchiki,
Julien Roux,
Mile Šikić
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx668
Subject(s) - minion , nanopore sequencing , computer science , rna seq , alignment free sequence analysis , error detection and correction , set (abstract data type) , computational biology , splice , data mining , contig , dna sequencing , sequence alignment , genome , algorithm , biology , gene , genetics , transcriptome , programming language , gene expression , peptide sequence
High-throughput sequencing has transformed the study of gene expression levels through RNA-seq, a technique that is now routinely used by various fields, such as genetic research or diagnostics. The advent of third generation sequencing technologies providing significantly longer reads opens up new possibilities. However, the high error rates common to these technologies set new bioinformatics challenges for the gapped alignment of reads to their genomic origin. In this study, we have explored how currently available RNA-seq splice-aware alignment tools cope with increased read lengths and error rates. All tested tools were initially developed for short NGS reads, but some have claimed support for long Pacific Biosciences (PacBio) or even Oxford Nanopore Technologies (ONT) MinION reads.

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