Benchmarking Low-Frequency Variant Calling With Long-Read Data on Mitochondrial DNA
Background: Sequencing quality has improved over the last decade for long-reads, allowing for more accurate detection of somatic low-frequency variants. In this study, we used mixtures of mitochondrial samples with different haplogroups (i.e., a specific set of mitochondrial variants) to investigate...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.887644/full |
| _version_ | 1811233400006115328 |
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| author | Theresa Lüth Susen Schaake Anne Grünewald Anne Grünewald Patrick May Joanne Trinh Hansi Weissensteiner |
| author_facet | Theresa Lüth Susen Schaake Anne Grünewald Anne Grünewald Patrick May Joanne Trinh Hansi Weissensteiner |
| author_sort | Theresa Lüth |
| collection | DOAJ |
| description | Background: Sequencing quality has improved over the last decade for long-reads, allowing for more accurate detection of somatic low-frequency variants. In this study, we used mixtures of mitochondrial samples with different haplogroups (i.e., a specific set of mitochondrial variants) to investigate the applicability of nanopore sequencing for low-frequency single nucleotide variant detection.Methods: We investigated the impact of base-calling, alignment/mapping, quality control steps, and variant calling by comparing the results to a previously derived short-read gold standard generated on the Illumina NextSeq. For nanopore sequencing, six mixtures of four different haplotypes were prepared, allowing us to reliably check for expected variants at the predefined 5%, 2%, and 1% mixture levels. We used two different versions of Guppy for base-calling, two aligners (i.e., Minimap2 and Ngmlr), and three variant callers (i.e., Mutserve2, Freebayes, and Nanopanel2) to compare low-frequency variants. We used F1 score measurements to assess the performance of variant calling.Results: We observed a mean read length of 11 kb and a mean overall read quality of 15. Ngmlr showed not only higher F1 scores but also higher allele frequencies (AF) of false-positive calls across the mixtures (mean F1 score = 0.83; false-positive allele frequencies < 0.17) compared to Minimap2 (mean F1 score = 0.82; false-positive AF < 0.06). Mutserve2 had the highest F1 scores (5% level: F1 score >0.99, 2% level: F1 score >0.54, and 1% level: F1 score >0.70) across all callers and mixture levels.Conclusion: We here present the benchmarking for low-frequency variant calling with nanopore sequencing by identifying current limitations. |
| first_indexed | 2024-04-12T11:19:49Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-12T11:19:49Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-1c58141749544f659ace6d26082153ab2022-12-22T03:35:24ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-05-011310.3389/fgene.2022.887644887644Benchmarking Low-Frequency Variant Calling With Long-Read Data on Mitochondrial DNATheresa Lüth0Susen Schaake1Anne Grünewald2Anne Grünewald3Patrick May4Joanne Trinh5Hansi Weissensteiner6Institute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, GermanyInstitute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, GermanyInstitute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, GermanyLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, LuxembourgLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, LuxembourgInstitute of Neurogenetics, University of Lübeck and University Hospital Schleswig-Holstein, Lübeck, GermanyInstitute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, AustriaBackground: Sequencing quality has improved over the last decade for long-reads, allowing for more accurate detection of somatic low-frequency variants. In this study, we used mixtures of mitochondrial samples with different haplogroups (i.e., a specific set of mitochondrial variants) to investigate the applicability of nanopore sequencing for low-frequency single nucleotide variant detection.Methods: We investigated the impact of base-calling, alignment/mapping, quality control steps, and variant calling by comparing the results to a previously derived short-read gold standard generated on the Illumina NextSeq. For nanopore sequencing, six mixtures of four different haplotypes were prepared, allowing us to reliably check for expected variants at the predefined 5%, 2%, and 1% mixture levels. We used two different versions of Guppy for base-calling, two aligners (i.e., Minimap2 and Ngmlr), and three variant callers (i.e., Mutserve2, Freebayes, and Nanopanel2) to compare low-frequency variants. We used F1 score measurements to assess the performance of variant calling.Results: We observed a mean read length of 11 kb and a mean overall read quality of 15. Ngmlr showed not only higher F1 scores but also higher allele frequencies (AF) of false-positive calls across the mixtures (mean F1 score = 0.83; false-positive allele frequencies < 0.17) compared to Minimap2 (mean F1 score = 0.82; false-positive AF < 0.06). Mutserve2 had the highest F1 scores (5% level: F1 score >0.99, 2% level: F1 score >0.54, and 1% level: F1 score >0.70) across all callers and mixture levels.Conclusion: We here present the benchmarking for low-frequency variant calling with nanopore sequencing by identifying current limitations.https://www.frontiersin.org/articles/10.3389/fgene.2022.887644/fullnanopore sequencinglong-readmtDNAheteroplasmybenchmarkingmixtures |
| spellingShingle | Theresa Lüth Susen Schaake Anne Grünewald Anne Grünewald Patrick May Joanne Trinh Hansi Weissensteiner Benchmarking Low-Frequency Variant Calling With Long-Read Data on Mitochondrial DNA Frontiers in Genetics nanopore sequencing long-read mtDNA heteroplasmy benchmarking mixtures |
| title | Benchmarking Low-Frequency Variant Calling With Long-Read Data on Mitochondrial DNA |
| title_full | Benchmarking Low-Frequency Variant Calling With Long-Read Data on Mitochondrial DNA |
| title_fullStr | Benchmarking Low-Frequency Variant Calling With Long-Read Data on Mitochondrial DNA |
| title_full_unstemmed | Benchmarking Low-Frequency Variant Calling With Long-Read Data on Mitochondrial DNA |
| title_short | Benchmarking Low-Frequency Variant Calling With Long-Read Data on Mitochondrial DNA |
| title_sort | benchmarking low frequency variant calling with long read data on mitochondrial dna |
| topic | nanopore sequencing long-read mtDNA heteroplasmy benchmarking mixtures |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.887644/full |
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