Minimum error correction-based haplotype assembly: Considerations for long read data.

Details

Serval ID
serval:BIB_38E50ECCDCEA
Type
Article: article from journal or magazin.
Collection
Publications
Title
Minimum error correction-based haplotype assembly: Considerations for long read data.
Journal
PloS one
Author(s)
Majidian S., Kahaei M.H., de Ridder D.
ISSN
1932-6203 (Electronic)
ISSN-L
1932-6203
Publication state
Published
Issued date
2020
Peer-reviewed
Oui
Volume
15
Number
6
Pages
e0234470
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
The single nucleotide polymorphism (SNP) is the most widely studied type of genetic variation. A haplotype is defined as the sequence of alleles at SNP sites on each haploid chromosome. Haplotype information is essential in unravelling the genome-phenotype association. Haplotype assembly is a well-known approach for reconstructing haplotypes, exploiting reads generated by DNA sequencing devices. The Minimum Error Correction (MEC) metric is often used for reconstruction of haplotypes from reads. However, problems with the MEC metric have been reported. Here, we investigate the MEC approach to demonstrate that it may result in incorrectly reconstructed haplotypes for devices that produce error-prone long reads. Specifically, we evaluate this approach for devices developed by Illumina, Pacific BioSciences and Oxford Nanopore Technologies. We show that imprecise haplotypes may be reconstructed with a lower MEC than that of the exact haplotype. The performance of MEC is explored for different coverage levels and error rates of data. Our simulation results reveal that in order to avoid incorrect MEC-based haplotypes, a coverage of 25 is needed for reads generated by Pacific BioSciences RS systems.
Keywords
Data Analysis, Electronic Data Processing/methods, Genome, Human, Haplotypes/genetics, Humans, Polymorphism, Single Nucleotide/genetics, Scientific Experimental Error, Sequence Analysis, DNA/instrumentation, Sequence Analysis, DNA/methods
Pubmed
Web of science
Open Access
Yes
Create date
16/06/2021 13:26
Last modification date
19/10/2023 9:47
Usage data