Minimum error correction-based haplotype assembly : Considerations for long read data
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.
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dig-wur-nl-wurpubs-5663662024-12-04 Majidian, Sina Kahaei, Mohammad Hossein de Ridder, Dick Article/Letter to editor PLoS ONE 15 (2020) 6 ISSN: 1932-6203 Minimum error correction-based haplotype assembly : Considerations for long read data 2020 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. en application/pdf https://research.wur.nl/en/publications/minimum-error-correction-based-haplotype-assembly-considerations- 10.1371/journal.pone.0234470 https://edepot.wur.nl/525368 Life Science https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/ Wageningen University & Research |
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Life Science Life Science Majidian, Sina Kahaei, Mohammad Hossein de Ridder, Dick Minimum error correction-based haplotype assembly : Considerations for long read data |
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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. |
format |
Article/Letter to editor |
topic_facet |
Life Science |
author |
Majidian, Sina Kahaei, Mohammad Hossein de Ridder, Dick |
author_facet |
Majidian, Sina Kahaei, Mohammad Hossein de Ridder, Dick |
author_sort |
Majidian, Sina |
title |
Minimum error correction-based haplotype assembly : Considerations for long read data |
title_short |
Minimum error correction-based haplotype assembly : Considerations for long read data |
title_full |
Minimum error correction-based haplotype assembly : Considerations for long read data |
title_fullStr |
Minimum error correction-based haplotype assembly : Considerations for long read data |
title_full_unstemmed |
Minimum error correction-based haplotype assembly : Considerations for long read data |
title_sort |
minimum error correction-based haplotype assembly : considerations for long read data |
url |
https://research.wur.nl/en/publications/minimum-error-correction-based-haplotype-assembly-considerations- |
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AT majidiansina minimumerrorcorrectionbasedhaplotypeassemblyconsiderationsforlongreaddata AT kahaeimohammadhossein minimumerrorcorrectionbasedhaplotypeassemblyconsiderationsforlongreaddata AT deridderdick minimumerrorcorrectionbasedhaplotypeassemblyconsiderationsforlongreaddata |
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