eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Leibniz International Proceedings in Informatics
1868-8969
2020-08-25
11:1
11:17
10.4230/LIPIcs.WABI.2020.11
article
A Graph-Theoretic Barcode Ordering Model for Linked-Reads
Dufresne, Yoann
1
https://orcid.org/0000-0002-0930-8920
Sun, Chen
2
Marijon, Pierre
3
https://orcid.org/0000-0002-6694-6873
Lavenier, Dominique
4
https://orcid.org/0000-0003-2557-680X
Chauve, Cedric
5
6
https://orcid.org/0000-0001-9837-1878
Chikhi, Rayan
1
https://orcid.org/0000-0003-1099-8735
Department of Computational Biology, C3BI USR 3756 CNRS, Institut Pasteur, Paris, France
Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, USA
Center for Bioinformatics, Saarland University, Saarland Informatics Campus, Saarbrücken, Germany
IRISA, Inria, Université de Rennes, France
Department of Mathematics, Simon Fraser University, Burnaby, Canada
LaBRI, Université de Bordeaux, France
Considering a set of intervals on the real line, an interval graph records these intervals as nodes and their intersections as edges. Identifying (i.e. merging) pairs of nodes in an interval graph results in a multiple-interval graph. Given only the nodes and the edges of the multiple-interval graph without knowing the underlying intervals, we are interested in the following questions. Can one determine how many intervals correspond to each node? Can one compute a walk over the multiple-interval graph nodes that reflects the ordering of the original intervals? These questions are closely related to linked-read DNA sequencing, where barcodes are assigned to long molecules whose intersection graph forms an interval graph. Each barcode may correspond to multiple molecules, which complicates downstream analysis, and corresponds to the identification of nodes of the corresponding interval graph. Resolving the above graph-theoretic problems would facilitate analyses of linked-reads sequencing data, through enabling the conceptual separation of barcodes into molecules and providing, through the molecules order, a skeleton for accurately assembling the genome. Here, we propose a framework that takes as input an arbitrary intersection graph (such as an overlap graph of barcodes) and constructs a heuristic approximation of the ordering of the original intervals.
https://drops.dagstuhl.de/storage/00lipics/lipics-vol172-wabi2020/LIPIcs.WABI.2020.11/LIPIcs.WABI.2020.11.pdf
DNA sequencing
graph algorithms
linked-reads
interval graphs
cliques