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Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline
A common technique for uncovering intra-tumor genomic heterogeneity (ITH) is variant detection. However, it can be challenging to reliably characterize ITH given uneven sample quality (e.g., depth of coverage, tumor purity, and subclonality). We describe a protocol for calling point mutations and co...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816983/ https://www.ncbi.nlm.nih.gov/pubmed/36586123 http://dx.doi.org/10.1016/j.xpro.2022.101927 |
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author | Maeser, Nicole Khan, Aziz Sun, Ruping |
author_facet | Maeser, Nicole Khan, Aziz Sun, Ruping |
author_sort | Maeser, Nicole |
collection | PubMed |
description | A common technique for uncovering intra-tumor genomic heterogeneity (ITH) is variant detection. However, it can be challenging to reliably characterize ITH given uneven sample quality (e.g., depth of coverage, tumor purity, and subclonality). We describe a protocol for calling point mutations and copy number alterations using sequencing of multiple related clinical patient samples across diverse tissue, optimizing for sensitivity with specificity. The ith.Variant pipeline can be run on single- or multi-region whole-genome and whole-exome sequencing. For complete details on the use and execution of this protocol, please refer to Sun et al. (2017).(1) |
format | Online Article Text |
id | pubmed-9816983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-98169832023-01-07 Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline Maeser, Nicole Khan, Aziz Sun, Ruping STAR Protoc Protocol A common technique for uncovering intra-tumor genomic heterogeneity (ITH) is variant detection. However, it can be challenging to reliably characterize ITH given uneven sample quality (e.g., depth of coverage, tumor purity, and subclonality). We describe a protocol for calling point mutations and copy number alterations using sequencing of multiple related clinical patient samples across diverse tissue, optimizing for sensitivity with specificity. The ith.Variant pipeline can be run on single- or multi-region whole-genome and whole-exome sequencing. For complete details on the use and execution of this protocol, please refer to Sun et al. (2017).(1) Elsevier 2022-12-29 /pmc/articles/PMC9816983/ /pubmed/36586123 http://dx.doi.org/10.1016/j.xpro.2022.101927 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Protocol Maeser, Nicole Khan, Aziz Sun, Ruping Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline |
title | Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline |
title_full | Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline |
title_fullStr | Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline |
title_full_unstemmed | Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline |
title_short | Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline |
title_sort | somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.variant pipeline |
topic | Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816983/ https://www.ncbi.nlm.nih.gov/pubmed/36586123 http://dx.doi.org/10.1016/j.xpro.2022.101927 |
work_keys_str_mv | AT maesernicole somaticvariantdetectionfrommultisampledgenomicsequencingdataoftumorspecimensusingtheithvariantpipeline AT khanaziz somaticvariantdetectionfrommultisampledgenomicsequencingdataoftumorspecimensusingtheithvariantpipeline AT sunruping somaticvariantdetectionfrommultisampledgenomicsequencingdataoftumorspecimensusingtheithvariantpipeline |