AluScanCNV2: An R package for copy number variation calling and cancer risk prediction with next-generation sequencing data

The usage of next-generation sequencing (NGS) to detect copy number variation (CNV) is widely accepted in cancer research. Based on an AluScanCNV software developed by us previously, an AluScanCNV2 software has been developed in the present study as an R package that performs CNV detection from NGS...

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Detalles Bibliográficos
Autores principales: Hu, Taobo, Chen, Si, Ullah, Ata, Xue, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Chongqing Medical University 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6411622/
https://www.ncbi.nlm.nih.gov/pubmed/30906832
http://dx.doi.org/10.1016/j.gendis.2018.09.001
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author Hu, Taobo
Chen, Si
Ullah, Ata
Xue, Hong
author_facet Hu, Taobo
Chen, Si
Ullah, Ata
Xue, Hong
author_sort Hu, Taobo
collection PubMed
description The usage of next-generation sequencing (NGS) to detect copy number variation (CNV) is widely accepted in cancer research. Based on an AluScanCNV software developed by us previously, an AluScanCNV2 software has been developed in the present study as an R package that performs CNV detection from NGS data obtained through AluScan, whole-genome sequencing or other targeted NGS platforms. Its applications would include the expedited usage of somatic CNVs for cancer subtyping, and usage of recurrent germline CNVs to perform machine learning-assisted prediction of a test subject's susceptibility to cancer.
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spelling pubmed-64116222019-03-22 AluScanCNV2: An R package for copy number variation calling and cancer risk prediction with next-generation sequencing data Hu, Taobo Chen, Si Ullah, Ata Xue, Hong Genes Dis Article The usage of next-generation sequencing (NGS) to detect copy number variation (CNV) is widely accepted in cancer research. Based on an AluScanCNV software developed by us previously, an AluScanCNV2 software has been developed in the present study as an R package that performs CNV detection from NGS data obtained through AluScan, whole-genome sequencing or other targeted NGS platforms. Its applications would include the expedited usage of somatic CNVs for cancer subtyping, and usage of recurrent germline CNVs to perform machine learning-assisted prediction of a test subject's susceptibility to cancer. Chongqing Medical University 2018-09-08 /pmc/articles/PMC6411622/ /pubmed/30906832 http://dx.doi.org/10.1016/j.gendis.2018.09.001 Text en © 2018 Chongqing Medical University. Production and hosting by Elsevier B.V. http://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 Article
Hu, Taobo
Chen, Si
Ullah, Ata
Xue, Hong
AluScanCNV2: An R package for copy number variation calling and cancer risk prediction with next-generation sequencing data
title AluScanCNV2: An R package for copy number variation calling and cancer risk prediction with next-generation sequencing data
title_full AluScanCNV2: An R package for copy number variation calling and cancer risk prediction with next-generation sequencing data
title_fullStr AluScanCNV2: An R package for copy number variation calling and cancer risk prediction with next-generation sequencing data
title_full_unstemmed AluScanCNV2: An R package for copy number variation calling and cancer risk prediction with next-generation sequencing data
title_short AluScanCNV2: An R package for copy number variation calling and cancer risk prediction with next-generation sequencing data
title_sort aluscancnv2: an r package for copy number variation calling and cancer risk prediction with next-generation sequencing data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6411622/
https://www.ncbi.nlm.nih.gov/pubmed/30906832
http://dx.doi.org/10.1016/j.gendis.2018.09.001
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