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A multi-objective optimisation approach to the design of experiment in de novo assembly projects
KTH, School of Computer Science and Communication (CSC). KTH, Centres, Science for Life Laboratory, SciLifeLab.
2012 (English)In: Database and Expert Systems Applications (DEXA), 2012 23rd International Workshop on, IEEE , 2012, 213-217 p.Conference paper (Refereed)
Abstract [en]

Genomics projects are characterised by difficult biological pipelines and high sequencing costs. In particular, de novo assembly projects must go through data production, assembly, and results validation. Early mistakes in the first (and most expensive) step can therefore be detected only at a very late stage and have serious consequences. Our goal is to design a pipeline able to provide the users with the optimal input for the sequencing experiments within a de novo assembly project. We present a new approach, based on multi-objective optimisation, aiming at transforming the design of genomics experiments from a set of "best practices" to an algorithmically controlled procedure. We implemented our model with mode FRONTIER and we show how our method can be used to infer the final quality of a whole genome assembly project from the results obtained on a small but representative sample.

Place, publisher, year, edition, pages
IEEE , 2012. 213-217 p.
, Proceedings - International Workshop on Database and Expert Systems Applications, DEXA, ISSN 1529-4188
Keyword [en]
de novo assembly, multi-objective optimisation, Pareto optima, sequencing technologies
National Category
Bioinformatics (Computational Biology)
URN: urn:nbn:se:kth:diva-108030DOI: 10.1109/DEXA.2012.42ISI: 000312658400034ScopusID: 2-s2.0-84869435177ISBN: 978-076954801-2OAI: diva2:580172
23rd International Workshop on Database and Expert Systems Applications, DEXA 2012, 3 September 2012 through 6 September 2012, Vienna
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceSwedish e‐Science Research Center

QC 20121221

Available from: 2012-12-21 Created: 2012-12-19 Last updated: 2013-04-08Bibliographically approved

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Vezzi, Francesco
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School of Computer Science and Communication (CSC)Science for Life Laboratory, SciLifeLab
Bioinformatics (Computational Biology)

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