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Published Online: 4 October 2018

A Two-Level Scheme for Quality Score Compression

Publication: Journal of Computational Biology
Volume 25, Issue Number 10


Previous studies on quality score compression can be classified into two main lines: lossy schemes and lossless schemes. Lossy schemes enable a better management of computational resources. Thus, in practice, and for preliminary analyses, bioinformaticians may prefer to work with a lossy quality score representation. However, the original quality scores might be required for a deeper analysis of the data. Hence, it might be necessary to keep them; in addition to lossy compression this requires lossless compression as well. We developed a space-efficient hierarchical representation of quality scores, QScomp, which allows the users to work with lossy quality scores in routine analysis, without sacrificing the capability of reaching the original quality scores when further investigations are required. Each quality score is represented by a tuple through a novel decomposition. The first and second dimensions of these tuples are separately compressed such that the first-level compression is a lossy scheme. The compressed information of the second dimension allows the users to extract the original quality scores. Experiments on real data reveal that the downstream analysis with the lossy part—spending only 0.49 bits per quality score on average—shows a competitive performance, and that the total space usage with the inclusion of the compressed second dimension is comparable to the performance of competing lossless schemes.

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Information & Authors


Published In

cover image Journal of Computational Biology
Journal of Computational Biology
Volume 25Issue Number 10October 2018
Pages: 1141 - 1151
PubMed: 30059248


Published online: 4 October 2018
Published in print: October 2018
Published ahead of print: 30 July 2018


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Institut für Informationsverarbeitung, Leibniz Universität Hannover, Hannover, Germany.
Ali Fotouhi
Electronics and Communication Engineering Department, Istanbul Technical University, Istanbul, Turkey.
Jörn Ostermann
Institut für Informationsverarbeitung, Leibniz Universität Hannover, Hannover, Germany.
Muhammed Oğuzhan Külekci [email protected]
Informatics Institute, Istanbul Technical University, Istanbul, Turkey.


Address correspondence to:Jan VogesLeibniz Universität HannoverInstitut für InformationsverarbeitungAppelstr. 9AHannover 30167Germany
[email protected]
Assoc. Prof. Muhammed Oğuzhan KülekciInformatics InstituteIstanbul Technical UniversityIstanbul 34469Turkey
[email protected]

Author Disclosure Statement

The authors declare that no competing financial interests exist.

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