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Comparison of the copy-neutral loss of heterozygosity identified from whole-exome sequencing data using three different tools
Loss of heterozygosity (LOH) is a genomic aberration. In some cases, LOH can be generated without changing the copy number, which is called copy-neutral LOH (CN-LOH). CN-LOH frequently occurs in various human diseases, including cancer. However, the biological and clinical implications of CN-LOH for...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Korea Genome Organization
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001996/ https://www.ncbi.nlm.nih.gov/pubmed/35399003 http://dx.doi.org/10.5808/gi.21066 |
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author | Lee, Gang-Taik Chung, Yeun-Jun |
author_facet | Lee, Gang-Taik Chung, Yeun-Jun |
author_sort | Lee, Gang-Taik |
collection | PubMed |
description | Loss of heterozygosity (LOH) is a genomic aberration. In some cases, LOH can be generated without changing the copy number, which is called copy-neutral LOH (CN-LOH). CN-LOH frequently occurs in various human diseases, including cancer. However, the biological and clinical implications of CN-LOH for human diseases have not been well studied. In this study, we compared the performance of CN-LOH determination using three commonly used tools. For an objective comparison, we analyzed CN-LOH profiles from single-nucleotide polymorphism array data from 10 colon adenocarcinoma patients, which were used as the reference for comparison with the CN-LOHs obtained through whole-exome sequencing (WES) data of the same patients using three different analysis tools (FACETS, Nexus, and Sequenza). The majority of the CN-LOHs identified from the WES data were consistent with the reference data. However, some of the CN-LOHs identified from the WES data were not consistent between the three tools, and the consistency with the reference CN-LOH profile was also different. The Jaccard index of the CN-LOHs using FACETS (0.84 ± 0.29; mean value, 0.73) was significantly higher than that of Nexus (0.55 ± 0.29; mean value, 0.50; p = 0.02) or Sequenza (0 ± 0.41; mean value, 0.34; p = 0.04). FACETS showed the highest area under the curve value. Taken together, of the three CN-LOH analysis tools, FACETS showed the best performance in identifying CN-LOHs from The Cancer Genome Atlas colon adenocarcinoma WES data. Our results will be helpful in exploring the biological or clinical implications of CN-LOH for human diseases. |
format | Online Article Text |
id | pubmed-9001996 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Korea Genome Organization |
record_format | MEDLINE/PubMed |
spelling | pubmed-90019962022-04-21 Comparison of the copy-neutral loss of heterozygosity identified from whole-exome sequencing data using three different tools Lee, Gang-Taik Chung, Yeun-Jun Genomics Inform Original Article Loss of heterozygosity (LOH) is a genomic aberration. In some cases, LOH can be generated without changing the copy number, which is called copy-neutral LOH (CN-LOH). CN-LOH frequently occurs in various human diseases, including cancer. However, the biological and clinical implications of CN-LOH for human diseases have not been well studied. In this study, we compared the performance of CN-LOH determination using three commonly used tools. For an objective comparison, we analyzed CN-LOH profiles from single-nucleotide polymorphism array data from 10 colon adenocarcinoma patients, which were used as the reference for comparison with the CN-LOHs obtained through whole-exome sequencing (WES) data of the same patients using three different analysis tools (FACETS, Nexus, and Sequenza). The majority of the CN-LOHs identified from the WES data were consistent with the reference data. However, some of the CN-LOHs identified from the WES data were not consistent between the three tools, and the consistency with the reference CN-LOH profile was also different. The Jaccard index of the CN-LOHs using FACETS (0.84 ± 0.29; mean value, 0.73) was significantly higher than that of Nexus (0.55 ± 0.29; mean value, 0.50; p = 0.02) or Sequenza (0 ± 0.41; mean value, 0.34; p = 0.04). FACETS showed the highest area under the curve value. Taken together, of the three CN-LOH analysis tools, FACETS showed the best performance in identifying CN-LOHs from The Cancer Genome Atlas colon adenocarcinoma WES data. Our results will be helpful in exploring the biological or clinical implications of CN-LOH for human diseases. Korea Genome Organization 2022-03-31 /pmc/articles/PMC9001996/ /pubmed/35399003 http://dx.doi.org/10.5808/gi.21066 Text en (c) 2022, Korea Genome Organization https://creativecommons.org/licenses/by/4.0/(CC) This is an open-access article distributed under the terms of the Creative Commons Attribution license(https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Lee, Gang-Taik Chung, Yeun-Jun Comparison of the copy-neutral loss of heterozygosity identified from whole-exome sequencing data using three different tools |
title | Comparison of the copy-neutral loss of heterozygosity identified from whole-exome sequencing data using three different tools |
title_full | Comparison of the copy-neutral loss of heterozygosity identified from whole-exome sequencing data using three different tools |
title_fullStr | Comparison of the copy-neutral loss of heterozygosity identified from whole-exome sequencing data using three different tools |
title_full_unstemmed | Comparison of the copy-neutral loss of heterozygosity identified from whole-exome sequencing data using three different tools |
title_short | Comparison of the copy-neutral loss of heterozygosity identified from whole-exome sequencing data using three different tools |
title_sort | comparison of the copy-neutral loss of heterozygosity identified from whole-exome sequencing data using three different tools |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001996/ https://www.ncbi.nlm.nih.gov/pubmed/35399003 http://dx.doi.org/10.5808/gi.21066 |
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