Literature DB >> 21228048

CNAmet: an R package for integrating copy number, methylation and expression data.

Riku Louhimo1, Sampsa Hautaniemi.   

Abstract

SUMMARY: Gene copy number and DNA methylation alterations are key regulators of gene expression in cancer. Accordingly, genes that show simultaneous methylation, copy number and expression alterations are likely to have a key role in tumor progression. We have implemented a novel software package (CNAmet) for integrative analysis of high-throughput copy number, DNA methylation and gene expression data. To demonstrate the utility of CNAmet, we use copy number, DNA methylation and gene expression data from 50 glioblastoma multiforme and 188 ovarian cancer primary tumor samples. Our results reveal a synergistic effect of DNA methylation and copy number alterations on gene expression for several known oncogenes as well as novel candidate oncogenes. AVAILABILITY: CNAmet R-package and user guide are freely available under GNU General Public License at http://csbi.ltdk.helsinki.fi/CNAmet.

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Year:  2011        PMID: 21228048     DOI: 10.1093/bioinformatics/btr019

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  42 in total

1.  Lessons from a decade of integrating cancer copy number alterations with gene expression profiles.

Authors:  Norman Huang; Parantu K Shah; Cheng Li
Journal:  Brief Bioinform       Date:  2011-09-23       Impact factor: 11.622

Review 2.  Principles and methods of integrative genomic analyses in cancer.

Authors:  Vessela N Kristensen; Ole Christian Lingjærde; Hege G Russnes; Hans Kristian M Vollan; Arnoldo Frigessi; Anne-Lise Børresen-Dale
Journal:  Nat Rev Cancer       Date:  2014-05       Impact factor: 60.716

3.  Incorporating inter-relationships between different levels of genomic data into cancer clinical outcome prediction.

Authors:  Dokyoon Kim; Hyunjung Shin; Kyung-Ah Sohn; Anurag Verma; Marylyn D Ritchie; Ju Han Kim
Journal:  Methods       Date:  2014-02-18       Impact factor: 3.608

4.  A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping.

Authors:  Anita Sathyanarayanan; Rohit Gupta; Erik W Thompson; Dale R Nyholt; Denis C Bauer; Shivashankar H Nagaraj
Journal:  Brief Bioinform       Date:  2020-12-01       Impact factor: 11.622

5.  Software for the Integration of Multiomics Experiments in Bioconductor.

Authors:  Marcel Ramos; Lucas Schiffer; Angela Re; Rimsha Azhar; Azfar Basunia; Carmen Rodriguez; Tiffany Chan; Phil Chapman; Sean R Davis; David Gomez-Cabrero; Aedin C Culhane; Benjamin Haibe-Kains; Kasper D Hansen; Hanish Kodali; Marie S Louis; Arvind S Mer; Markus Riester; Martin Morgan; Vince Carey; Levi Waldron
Journal:  Cancer Res       Date:  2017-11-01       Impact factor: 12.701

6.  integIRTy: a method to identify genes altered in cancer by accounting for multiple mechanisms of regulation using item response theory.

Authors:  Pan Tong; Kevin R Coombes
Journal:  Bioinformatics       Date:  2012-09-26       Impact factor: 6.937

7.  Genome-wide copy number variation pattern analysis and a classification signature for non-small cell lung cancer.

Authors:  Zhe-Wei Qiu; Jia-Hao Bi; Adi F Gazdar; Kai Song
Journal:  Genes Chromosomes Cancer       Date:  2017-05-04       Impact factor: 5.006

8.  Graph- and rule-based learning algorithms: a comprehensive review of their applications for cancer type classification and prognosis using genomic data.

Authors:  Saurav Mallik; Zhongming Zhao
Journal:  Brief Bioinform       Date:  2020-03-23       Impact factor: 11.622

9.  Extracting coordinated patterns of DNA methylation and gene expression in ovarian cancer.

Authors:  Je-Gun Joung; Dokyoon Kim; Kyung Hwa Kim; Ju Han Kim
Journal:  J Am Med Inform Assoc       Date:  2013-04-18       Impact factor: 4.497

10.  Estimation of a non-parametric variable importance measure of a continuous exposure.

Authors:  Antoine Chambaz; Pierre Neuvial; Mark J van der Laan
Journal:  Electron J Stat       Date:  2012       Impact factor: 1.125

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