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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...

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Detalles Bibliográficos
Autores principales: Maeser, Nicole, Khan, Aziz, Sun, Ruping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
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)
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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
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