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Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders
BACKGROUND: Due to its reduced cost and incomparable advantages, WGS is likely to lead to changes in clinical diagnosis of rare and undiagnosed diseases. However, the sensitivity and breadth of coverage of clinical WGS as a diagnostic test for genetic disorders has not been fully evaluated. METHODS:...
Autores principales: | , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045368/ https://www.ncbi.nlm.nih.gov/pubmed/33849535 http://dx.doi.org/10.1186/s12920-021-00948-5 |
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author | Sun, Yan Liu, Fengxia Fan, Chunna Wang, Yaoshen Song, Lijie Fang, Zhonghai Han, Rui Wang, Zhonghua Wang, Xiaodan Yang, Ziying Xu, Zhenpeng Peng, Jiguang Shi, Chaonan Zhang, Hongyun Dong, Wei Huang, Hui Li, Yun Le, Yanqun Sun, Jun Peng, Zhiyu |
author_facet | Sun, Yan Liu, Fengxia Fan, Chunna Wang, Yaoshen Song, Lijie Fang, Zhonghai Han, Rui Wang, Zhonghua Wang, Xiaodan Yang, Ziying Xu, Zhenpeng Peng, Jiguang Shi, Chaonan Zhang, Hongyun Dong, Wei Huang, Hui Li, Yun Le, Yanqun Sun, Jun Peng, Zhiyu |
author_sort | Sun, Yan |
collection | PubMed |
description | BACKGROUND: Due to its reduced cost and incomparable advantages, WGS is likely to lead to changes in clinical diagnosis of rare and undiagnosed diseases. However, the sensitivity and breadth of coverage of clinical WGS as a diagnostic test for genetic disorders has not been fully evaluated. METHODS: Here, the performance of WGS in NA12878, the YH cell line, and the Chinese trios were measured by assessing their sensitivity, PPV, depth and breadth of coverage using MGISEQ-2000. We also compared the performance of WES and WGS using NA12878. The sensitivity and PPV were tested using the family-based trio design for the Chinese trios. We further developed a systematic WGS pipeline for the analysis of 8 clinical cases. RESULTS: In general, the sensitivity and PPV for SNV/indel detection increased with mean depth and reached a plateau at an ~ 40X mean depth using down-sampling samples of NA12878. With a mean depth of 40X, the sensitivity of homozygous and heterozygous SNPs of NA12878 was > 99.25% and > 99.50%, respectively, and the PPV was 99.97% and 98.96%. Homozygous and heterozygous indels showed lower sensitivity and PPV. The sensitivity and PPV were still not 100% even with a mean depth of ~ 150X. We also observed a substantial variation in the sensitivity of CNV detection across different tools, especially in CNVs with a size less than 1 kb. In general, the breadth of coverage for disease-associated genes and CNVs increased with mean depth. The sensitivity and coverage of WGS (~ 40X) was better than WES (~ 120X). Among the Chinese trios with an ~ 40X mean depth, the sensitivity among offspring was > 99.48% and > 96.36% for SNP and indel detection, and the PPVs were 99.86% and 97.93%. All 12 previously validated variants in the 8 clinical cases were successfully detected using our WGS pipeline. CONCLUSIONS: The current standard of a mean depth of 40X may be sufficient for SNV/indel detection and identification of most CNVs. It would be advisable for clinical scientists to determine the range of sensitivity and PPV for different classes of variants for a particular WGS pipeline, which would be useful when interpreting and delivering clinical reports. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-021-00948-5. |
format | Online Article Text |
id | pubmed-8045368 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80453682021-04-14 Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders Sun, Yan Liu, Fengxia Fan, Chunna Wang, Yaoshen Song, Lijie Fang, Zhonghai Han, Rui Wang, Zhonghua Wang, Xiaodan Yang, Ziying Xu, Zhenpeng Peng, Jiguang Shi, Chaonan Zhang, Hongyun Dong, Wei Huang, Hui Li, Yun Le, Yanqun Sun, Jun Peng, Zhiyu BMC Med Genomics Research Article BACKGROUND: Due to its reduced cost and incomparable advantages, WGS is likely to lead to changes in clinical diagnosis of rare and undiagnosed diseases. However, the sensitivity and breadth of coverage of clinical WGS as a diagnostic test for genetic disorders has not been fully evaluated. METHODS: Here, the performance of WGS in NA12878, the YH cell line, and the Chinese trios were measured by assessing their sensitivity, PPV, depth and breadth of coverage using MGISEQ-2000. We also compared the performance of WES and WGS using NA12878. The sensitivity and PPV were tested using the family-based trio design for the Chinese trios. We further developed a systematic WGS pipeline for the analysis of 8 clinical cases. RESULTS: In general, the sensitivity and PPV for SNV/indel detection increased with mean depth and reached a plateau at an ~ 40X mean depth using down-sampling samples of NA12878. With a mean depth of 40X, the sensitivity of homozygous and heterozygous SNPs of NA12878 was > 99.25% and > 99.50%, respectively, and the PPV was 99.97% and 98.96%. Homozygous and heterozygous indels showed lower sensitivity and PPV. The sensitivity and PPV were still not 100% even with a mean depth of ~ 150X. We also observed a substantial variation in the sensitivity of CNV detection across different tools, especially in CNVs with a size less than 1 kb. In general, the breadth of coverage for disease-associated genes and CNVs increased with mean depth. The sensitivity and coverage of WGS (~ 40X) was better than WES (~ 120X). Among the Chinese trios with an ~ 40X mean depth, the sensitivity among offspring was > 99.48% and > 96.36% for SNP and indel detection, and the PPVs were 99.86% and 97.93%. All 12 previously validated variants in the 8 clinical cases were successfully detected using our WGS pipeline. CONCLUSIONS: The current standard of a mean depth of 40X may be sufficient for SNV/indel detection and identification of most CNVs. It would be advisable for clinical scientists to determine the range of sensitivity and PPV for different classes of variants for a particular WGS pipeline, which would be useful when interpreting and delivering clinical reports. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-021-00948-5. BioMed Central 2021-04-13 /pmc/articles/PMC8045368/ /pubmed/33849535 http://dx.doi.org/10.1186/s12920-021-00948-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Sun, Yan Liu, Fengxia Fan, Chunna Wang, Yaoshen Song, Lijie Fang, Zhonghai Han, Rui Wang, Zhonghua Wang, Xiaodan Yang, Ziying Xu, Zhenpeng Peng, Jiguang Shi, Chaonan Zhang, Hongyun Dong, Wei Huang, Hui Li, Yun Le, Yanqun Sun, Jun Peng, Zhiyu Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders |
title | Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders |
title_full | Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders |
title_fullStr | Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders |
title_full_unstemmed | Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders |
title_short | Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders |
title_sort | characterizing sensitivity and coverage of clinical wgs as a diagnostic test for genetic disorders |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8045368/ https://www.ncbi.nlm.nih.gov/pubmed/33849535 http://dx.doi.org/10.1186/s12920-021-00948-5 |
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