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BESST - Efficient scaffolding of large fragmented assemblies
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. KTH, Centres, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0001-7378-2320
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
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2014 (English)In: BMC Bioinformatics, ISSN 1471-2105, Vol. 15, no 1, 281- p.Article in journal (Refereed) Published
Abstract [en]

Background: The use of short reads from High Throughput Sequencing (HTS) techniques is now commonplace in de novo assembly. Yet, obtaining contiguous assemblies from short reads is challenging, thus making scaffolding an important step in the assembly pipeline. Different algorithms have been proposed but many of them use the number of read pairs supporting a linking of two contigs as an indicator of reliability. This reasoning is intuitive, but fails to account for variation in link count due to contig features. We have also noted that published scaffolders are only evaluated on small datasets using output from only one assembler. Two issues arise from this. Firstly, some of the available tools are not well suited for complex genomes. Secondly, these evaluations provide little support for inferring a software's general performance. Results: We propose a new algorithm, implemented in a tool called BESST, which can scaffold genomes of all sizes and complexities and was used to scaffold the genome of P. abies (20 Gbp). We performed a comprehensive comparison of BESST against the most popular stand-alone scaffolders on a large variety of datasets. Our results confirm that some of the popular scaffolders are not practical to run on complex datasets. Furthermore, no single stand-alone scaffolder outperforms the others on all datasets. However, BESST fares favorably to the other tested scaffolders on GAGE datasets and, moreover, outperforms the other methods when library insert size distribution is wide. Conclusion: We conclude from our results that information sources other than the quantity of links, as is commonly used, can provide useful information about genome structure when scaffolding.

Place, publisher, year, edition, pages
2014. Vol. 15, no 1, 281- p.
Keyword [en]
Genome analysis, Genome assembly, Mate pair next-generation sequencing, Scaffolding
National Category
Biochemistry and Molecular Biology
URN: urn:nbn:se:kth:diva-152583DOI: 10.1186/1471-2105-15-281ISI: 000341198900001ScopusID: 2-s2.0-84906826446OAI: diva2:750546
Swedish Research Council, 2010-4634Knut and Alice Wallenberg FoundationScience for Life Laboratory - a national resource center for high-throughput molecular bioscience

QC 20140929

Available from: 2014-09-29 Created: 2014-09-29 Last updated: 2015-09-15Bibliographically approved
In thesis
1. Algorithms and statistical models for scaffolding contig assemblies and detecting structural variants using read pair data
Open this publication in new window or tab >>Algorithms and statistical models for scaffolding contig assemblies and detecting structural variants using read pair data
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Advances in throughput from Next Generation Sequencing (NGS) methods has provided new ways to study molecular biology. The increased amount of data enables genome wide scale studies of structural variation, transcription, translation and genome composition. Not only is the scale of each experiment large; lowered cost and faster turn-around has also increased the frequency with which new experiments are conducted. With the data growth comes an increase in demand for efficient and robust algorithms — this is a great computational challenge. The design of computationally efficient algorithms are crucial to cope with the amount of data and it is relatively easy to verify an efficient algorithm by runtime and memory consumption. However, as NGS data comes with several artifacts together with the size the difficulty lies in verifying that the algorithm gives accurate results and are robust to different data sets.

This thesis focuses on modeling assumptions of mate-pair and paired-end reads when scaffolding contig assemblies or detecting variants. Both genome assembly and structural variation are difficult problems, partly because of a computationally complex nature of the problems, but also due to various noise and artifacts in input data. Constructing methods that addresses all artifacts and parameters in data is difficult, if not impossible, and end-to-end pipelines often come with several simplifications. Instead of tackling these difficult problems all at once, a large part of this thesis concentrates on smaller problems around scaffolding and structural variation detection. By identifying and modeling parts of the problem where simplifications has been made in other algorithms, we obtain an improved solution to the corresponding full problem.

The first paper shows an improved model to estimate gap sizes, hence contig placement, in the scaffolding problem. The second paper introduces a new scaffolder to scaffold large complex genomes and the third paper extends the scaffolding method to account for paired-end-contamination in mate-pair libraries. The fourth paper investigates detection of structural variants using fragment length information and corrects a commonly assumed null-hypothesis distribution used to detect structural variants.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. x, 59 p.
TRITA-CSC-A, ISSN 1653-5723 ; 2015:14
National Category
Bioinformatics (Computational Biology)
urn:nbn:se:kth:diva-173580 (URN)978-91-7595-677-0 (ISBN)
Public defence
2015-10-01, Atrium, Nobels väg 12B, Stockholm, 10:00 (English)

QC 20150915

Available from: 2015-09-15 Created: 2015-09-14 Last updated: 2015-09-15Bibliographically approved

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