In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 16, No. 11 ( 2020-11-23), p. e1008397-
Abstract:
Genetic diseases are driven by aberrations of the human genome. Identification of such aberrations including structural variations (SVs) is key to our understanding. Conventional short-reads whole genome sequencing (cWGS) can identify SVs to base-pair resolution, but utilizes only short-range information and suffers from high false discovery rate (FDR). Linked-reads sequencing (10XWGS) utilizes long-range information by linkage of short-reads originating from the same large DNA molecule. This can mitigate alignment-based artefacts especially in repetitive regions and should enable better prediction of SVs. However, an unbiased evaluation of this technology is not available. In this study, we performed a comprehensive analysis of different types and sizes of SVs predicted by both the technologies and validated with an independent PCR based approach. The SVs commonly identified by both the technologies were highly specific, while validation rate dropped for uncommon events. A particularly high FDR was observed for SVs only found by 10XWGS. To improve FDR and sensitivity, statistical models for both the technologies were trained. Using our approach, we characterized SVs from the MCF7 cell line and a primary breast cancer tumor with high precision. This approach improves SV prediction and can therefore help in understanding the underlying genetics in various diseases.
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1008397
DOI:
10.1371/journal.pcbi.1008397.g001
DOI:
10.1371/journal.pcbi.1008397.g002
DOI:
10.1371/journal.pcbi.1008397.g003
DOI:
10.1371/journal.pcbi.1008397.g004
DOI:
10.1371/journal.pcbi.1008397.s001
DOI:
10.1371/journal.pcbi.1008397.s002
DOI:
10.1371/journal.pcbi.1008397.s003
DOI:
10.1371/journal.pcbi.1008397.s004
DOI:
10.1371/journal.pcbi.1008397.s005
DOI:
10.1371/journal.pcbi.1008397.s006
DOI:
10.1371/journal.pcbi.1008397.s007
DOI:
10.1371/journal.pcbi.1008397.s008
DOI:
10.1371/journal.pcbi.1008397.s009
DOI:
10.1371/journal.pcbi.1008397.s010
DOI:
10.1371/journal.pcbi.1008397.s011
DOI:
10.1371/journal.pcbi.1008397.s012
DOI:
10.1371/journal.pcbi.1008397.s013
DOI:
10.1371/journal.pcbi.1008397.s014
DOI:
10.1371/journal.pcbi.1008397.s015
DOI:
10.1371/journal.pcbi.1008397.s016
DOI:
10.1371/journal.pcbi.1008397.s017
DOI:
10.1371/journal.pcbi.1008397.s018
DOI:
10.1371/journal.pcbi.1008397.s019
DOI:
10.1371/journal.pcbi.1008397.s020
DOI:
10.1371/journal.pcbi.1008397.s021
DOI:
10.1371/journal.pcbi.1008397.s022
DOI:
10.1371/journal.pcbi.1008397.s023
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2020
detail.hit.zdb_id:
2193340-6
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