Fast and accurate correction of optical mapping data via spaced seeds

Show full item record



Salmela , L , Mukherjee , K , Puglisi , S J , Muggli , M D & Boucher , C 2020 , ' Fast and accurate correction of optical mapping data via spaced seeds ' , Bioinformatics , vol. 36 , no. 3 , pp. 682-689 .

Title: Fast and accurate correction of optical mapping data via spaced seeds
Author: Salmela, Leena; Mukherjee, Kingshuk; Puglisi, Simon J.; Muggli, Martin D.; Boucher, Christina
Contributor organization: Department of Computer Science
Helsinki Institute for Information Technology
Algorithmic Bioinformatics
Date: 2020-02-01
Language: eng
Number of pages: 8
Belongs to series: Bioinformatics
ISSN: 1367-4803
Abstract: Motivation: Optical mapping data is used in many core genomics applications, including structural variation detection, scaffolding assembled contigs and mis-assembly detection. However, the pervasiveness of spurious and deleted cut sites in the raw data, which are called Rmaps, make assembly and alignment of them challenging. Although there exists another method to error correct Rmap data, named cOMet, it is unable to scale to even moderately large sized genomes. The challenge faced in error correction is in determining pairs of Rmaps that originate from the same region of the same genome. Results: We create an efficient method for determining pairs of Rmaps that contain significant overlaps between them. Our method relies on the novel and nontrivial adaption and application of spaced seeds in the context of optical mapping, which allows for spurious and deleted cut sites to be accounted for. We apply our method to detecting and correcting these errors. The resulting error correction method, referred to as Elmeri, improves upon the results of state-of-the-art correction methods but in a fraction of the time. More specifically, cOMet required 9.9 CPU days to error correct Rmap data generated from the human genome, whereas Elmeri required less than 15 CPU hours and improved the quality of the Rmaps by more than four times compared to cOMet.
Subject: GENOME
1182 Biochemistry, cell and molecular biology
113 Computer and information sciences
111 Mathematics
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion

Files in this item

Total number of downloads: Loading...

Files Size Format View
btz663.pdf 651.0Kb PDF View/Open

This item appears in the following Collection(s)

Show full item record