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Accepted (AM)Open Access (License Unspecified), Open
Conference proceeding
REXTAL: Regional Extension of Assemblies Using Linked-Reads
BIOINFORMATICS RESEARCH AND APPLICATIONS, ISBRA 2018, v 10847, pp 63-78
01 Jan 2018
PMID: 32016171
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
It is currently impossible to get complete de novo assembly of segmentally duplicated genome regions using genome-wide short-read datasets. Here, we devise a new computational method called Regional Extension of Assemblies Using Linked-Reads (REXTAL) for improved region-specific assembly of segmental duplication-containing DNA, leveraging genomic short-read datasets generated from large DNA molecules partitioned and barcoded using the Gel Bead in Emulsion (GEM) microfluidic method [1]. We show that using REXTAL, it is possible to extend assembly of single-copy diploid DNA into adjacent, otherwise inaccessible subtelomere segmental duplication regions and other subtelomeric gap regions. Moreover, REXTAL is computationally more efficient for the directed assembly of such regions from multiple genomes (e.g., for the comparison of structural variation) than genome-wide assembly approaches.
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Details
- Title
- REXTAL: Regional Extension of Assemblies Using Linked-Reads
- Creators
- Tunazzina Islam - Old Dominion UniversityDesh Ranjan - Old Dominion UniversityEleanor Young - Drexel UniversityMing Xiao - Drexel UniversityMohammad Zubair - Old Dominion UniversityHarold Riethman - Old Dominion University
- Contributors
- F Zhang (Editor)Z Cai (Editor)P Skums (Editor)S Zhang (Editor)
- Publication Details
- BIOINFORMATICS RESEARCH AND APPLICATIONS, ISBRA 2018, v 10847, pp 63-78
- Series
- Lecture Notes in Bioinformatics
- Publisher
- Springer Nature
- Number of pages
- 16
- Grant note
- R21CA177395 / NIH; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA R21CA177395 / NATIONAL CANCER INSTITUTE; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI) Old Dominion University
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000469799100006
- Scopus ID
- 2-s2.0-85050344868
- Other Identifier
- 991019167926904721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Mathematical & Computational Biology