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Journal article
Analysis of Subtelomeric REXTAL Assemblies Using QUAST
IEEE/ACM transactions on computational biology and bioinformatics, v 18(1), pp 365-372
Jan 2021
PMID: 31056507
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Genomic regions of high segmental duplication content and/or structural variation have led to gaps and misassemblies in the human reference sequence, and are refractory to assembly from whole-genome short-read datasets. Human subtelomere regions are highly enriched in both segmental duplication content and structural variations, and as a consequence are both impossible to assemble accurately and highly variable from individual to individual. Recently, we developed a pipeline for improved region-specific assembly called Regional Extension of Assemblies Using Linked-Reads (REXTAL). In this study, we evaluate REXTAL and genome-wide assembly (Supernova) approaches on 10X Genomics linked-reads data sets partitioned and barcoded using the Gel Bead in Emulsion (GEM) microfluidic method. Our results describe the accuracy and relative performance of these two approaches using the reference-based assessment module of QUAST. We show that REXTAL dramatically outperforms the Supernova whole genome assembler in subtelomeric segmental duplication regions, and results in highly accurate assemblies. Nearly all of the REXTAL "misassemblies" identified using default QUAST parameters simply pinpoint locations of tandem repeat arrays in the reference sequence where the repeat array length differs from that in the cognate REXTAL assembly by <inline-formula><tex-math notation="LaTeX">></tex-math> <mml:math><mml:mo>></mml:mo></mml:math><inline-graphic xlink:href="islam-ieq1-2913845.gif"/> </inline-formula> 1000 bp.
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Details
- Title
- Analysis of Subtelomeric REXTAL Assemblies Using QUAST
- Creators
- Tunazzina Islam - Old Dominion UniversityDesh Ranjan - Old Dominion UniversityMohammad Zubair - Old Dominion UniversityEleanor Young - Drexel UniversityMing Xiao - Drexel UniversityHarold Riethman - Old Dominion University
- Publication Details
- IEEE/ACM transactions on computational biology and bioinformatics, v 18(1), pp 365-372
- Publisher
- IEEE
- Grant note
- R21CA177395 / National Institutes of Health (10.13039/100000002) Old Dominion University (10.13039/100009980)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000615042600035
- Scopus ID
- 2-s2.0-85100522165
- Other Identifier
- 991019167818304721
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InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Biochemical Research Methods
- Computer Science, Interdisciplinary Applications
- Mathematics, Interdisciplinary Applications
- Statistics & Probability