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Authors: Anna Kuosmanen 1 ; Ahmed Sobih 1 ; Romeo Rizzi 2 ; Veli Mäkinen 1 and Alexandru I. Tomescu 1

Affiliations: 1 University of Helsinki, Finland ; 2 University of Verona, Italy

ISBN: 978-989-758-170-0

Keyword(s): RNA-seq, Long Reads, Transcript Prediction, Network Flow, Splicing Graph, Minimum Path Cover.

Related Ontology Subjects/Areas/Topics: Algorithms and Software Tools ; Bioinformatics ; Biomedical Engineering ; Transcriptomics

Abstract: Over the past decade, sequencing read length has increased from tens to hundreds and then to thousands of bases. Current cDNA synthesis methods prevent RNA-seq reads from being long enough to entirely capture all the RNA transcripts, but long reads can still provide connectivity information on chains of multiple exons that are included in transcripts. We demonstrate that exploiting full connectivity information leads to significantly higher prediction accuracy, as measured by the F-score. For this purpose we implemented the solution to the Minimum Path Cover with Subpath Constraints problem introduced in (Rizzi et al., 2014), which is an extension of the classical Minimum Path Cover problem and was shown solvable by min-cost flows. We show that, under hypothetical conditions of perfect sequencing, our approach is able to use long reads more effectively than two state-of-the-art tools, StringTie and FlipFlop. Even in this setting the problem is not trivial, and errors in the underlying flow graph introduced by sequencing and alignment errors complicate the problem further. As such our work also demonstrates the need for a development of a good spliced read aligner for long reads. Our proof-of-concept implementation is available at http://www.cs.helsinki.fi/en/gsa/traphlor. (More)

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Paper citation in several formats:
Kuosmanen, A.; Sobih, A.; Rizzi, R.; Mäkinen, V. and Tomescu, A. (2016). On using Longer RNA-seq Reads to Improve Transcript Prediction Accuracy.In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 272-277. DOI: 10.5220/0005819702720277

@conference{bioinformatics16,
author={Anna Kuosmanen. and Ahmed Sobih. and Romeo Rizzi. and Veli Mäkinen. and Alexandru I. Tomescu.},
title={On using Longer RNA-seq Reads to Improve Transcript Prediction Accuracy},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)},
year={2016},
pages={272-277},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005819702720277},
isbn={978-989-758-170-0},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)
TI - On using Longer RNA-seq Reads to Improve Transcript Prediction Accuracy
SN - 978-989-758-170-0
AU - Kuosmanen, A.
AU - Sobih, A.
AU - Rizzi, R.
AU - Mäkinen, V.
AU - Tomescu, A.
PY - 2016
SP - 272
EP - 277
DO - 10.5220/0005819702720277

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