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Improved Statistical Analysis for Array CGH-Based DNA Copy Number Aberrations

Array-based comparative genomic hybridization (aCGH) allows measuring DNA copy number at the whole genome scale. In cancer studies, one may be interested in identifying DNA copy number aberrations (CNAs) associated with certain clinicopathological characteristics such as cancer metastasis. We propos...

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Detalles Bibliográficos
Autores principales: Jiang, Hongmei, Zhu, Zhong-Zheng, Yu, Yue, Lin, Simon, Hou, Lifang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Libertas Academica 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3212864/
https://www.ncbi.nlm.nih.gov/pubmed/22084565
http://dx.doi.org/10.4137/CIN.S8019
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author Jiang, Hongmei
Zhu, Zhong-Zheng
Yu, Yue
Lin, Simon
Hou, Lifang
author_facet Jiang, Hongmei
Zhu, Zhong-Zheng
Yu, Yue
Lin, Simon
Hou, Lifang
author_sort Jiang, Hongmei
collection PubMed
description Array-based comparative genomic hybridization (aCGH) allows measuring DNA copy number at the whole genome scale. In cancer studies, one may be interested in identifying DNA copy number aberrations (CNAs) associated with certain clinicopathological characteristics such as cancer metastasis. We proposed to define test regions based on copy number pattern profiles across multiple samples, using either smoothed log(2)-ratio or discrete data of copy number gain/loss calls. Association test performed on the refined test regions instead of the probes has improved power due to reduced number of tests. We also compared three types of measurement of copy number levels, normalized log(2)-ratio, smoothed log(2)-ratio, and copy number gain or loss calls in statistical hypothesis testing. The relative strengths and weaknesses of the proposed method were demonstrated using both simulation studies and real data analysis of a liver cancer study.
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spelling pubmed-32128642011-11-14 Improved Statistical Analysis for Array CGH-Based DNA Copy Number Aberrations Jiang, Hongmei Zhu, Zhong-Zheng Yu, Yue Lin, Simon Hou, Lifang Cancer Inform Methodology Array-based comparative genomic hybridization (aCGH) allows measuring DNA copy number at the whole genome scale. In cancer studies, one may be interested in identifying DNA copy number aberrations (CNAs) associated with certain clinicopathological characteristics such as cancer metastasis. We proposed to define test regions based on copy number pattern profiles across multiple samples, using either smoothed log(2)-ratio or discrete data of copy number gain/loss calls. Association test performed on the refined test regions instead of the probes has improved power due to reduced number of tests. We also compared three types of measurement of copy number levels, normalized log(2)-ratio, smoothed log(2)-ratio, and copy number gain or loss calls in statistical hypothesis testing. The relative strengths and weaknesses of the proposed method were demonstrated using both simulation studies and real data analysis of a liver cancer study. Libertas Academica 2011-10-19 /pmc/articles/PMC3212864/ /pubmed/22084565 http://dx.doi.org/10.4137/CIN.S8019 Text en © the author(s), publisher and licensee Libertas Academica Ltd. This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited.
spellingShingle Methodology
Jiang, Hongmei
Zhu, Zhong-Zheng
Yu, Yue
Lin, Simon
Hou, Lifang
Improved Statistical Analysis for Array CGH-Based DNA Copy Number Aberrations
title Improved Statistical Analysis for Array CGH-Based DNA Copy Number Aberrations
title_full Improved Statistical Analysis for Array CGH-Based DNA Copy Number Aberrations
title_fullStr Improved Statistical Analysis for Array CGH-Based DNA Copy Number Aberrations
title_full_unstemmed Improved Statistical Analysis for Array CGH-Based DNA Copy Number Aberrations
title_short Improved Statistical Analysis for Array CGH-Based DNA Copy Number Aberrations
title_sort improved statistical analysis for array cgh-based dna copy number aberrations
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3212864/
https://www.ncbi.nlm.nih.gov/pubmed/22084565
http://dx.doi.org/10.4137/CIN.S8019
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