Literature DB >> 19542153

Copy number variation has little impact on bead-array-based measures of DNA methylation.

E Andrés Houseman1, Brock C Christensen, Margaret R Karagas, Margaret R Wrensch, Heather H Nelson, Joseph L Wiemels, Shichun Zheng, John K Wiencke, Karl T Kelsey, Carmen J Marsit.   

Abstract

MOTIVATION: Integration of various genome-scale measures of molecular alterations is of great interest to researchers aiming to better define disease processes or identify novel targets with clinical utility. Particularly important in cancer are measures of gene copy number DNA methylation. However, copy number variation may bias the measurement of DNA methylation. To investigate possible bias, we analyzed integrated data obtained from 19 head and neck squamous cell carcinoma (HNSCC) tumors and 23 mesothelioma tumors.
RESULTS: Statistical analysis of observational data produced results consistent with those anticipated from theoretical mathematical properties. Average beta value reported by Illumina GoldenGate (a bead-array platform) was significantly smaller than a similar measure constructed from the ratio of average dye intensities. Among CpGs that had only small variations in measured methylation across tumors (filtering out clearly biological methylation signatures), there were no systematic copy number effects on methylation for three and more than four copies; however, one copy led to small systematic negative effects, and no copies led to substantial significant negative effects.
CONCLUSIONS: Since mathematical considerations suggest little bias in methylation assayed using bead-arrays, the consistency of observational data with anticipated properties suggests little bias. However, further analysis of systematic copy number effects across CpGs suggest that though there may be little bias when there are copy number gains, small biases may result when one allele is lost, and substantial biases when both alleles are lost. These results suggest that further integration of these measures can be useful for characterizing the biological relationships between these somatic events.

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Year:  2009        PMID: 19542153      PMCID: PMC2723008          DOI: 10.1093/bioinformatics/btp364

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


  24 in total

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Journal:  Bioinformatics       Date:  2003-12-12       Impact factor: 6.937

2.  High-resolution analysis of DNA copy number using oligonucleotide microarrays.

Authors:  Graham R Bignell; Jing Huang; Joel Greshock; Stephen Watt; Adam Butler; Sofie West; Mira Grigorova; Keith W Jones; Wen Wei; Michael R Stratton; P Andrew Futreal; Barbara Weber; Michael H Shapero; Richard Wooster
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Review 4.  Applications of next-generation sequencing technologies in functional genomics.

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Review 5.  The fundamental role of epigenetic events in cancer.

Authors:  Peter A Jones; Stephen B Baylin
Journal:  Nat Rev Genet       Date:  2002-06       Impact factor: 53.242

6.  Integrated analysis of homozygous deletions, focal amplifications, and sequence alterations in breast and colorectal cancers.

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7.  The Cancer Biomedical Informatics Grid (caBIG): pioneering an expansive network of information and tools for collaborative cancer research.

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8.  Whole genome DNA copy number changes identified by high density oligonucleotide arrays.

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Journal:  Hum Genomics       Date:  2004-05       Impact factor: 4.639

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Journal:  Environ Health Perspect       Date:  2008-06       Impact factor: 9.031

10.  Model-based clustering of DNA methylation array data: a recursive-partitioning algorithm for high-dimensional data arising as a mixture of beta distributions.

Authors:  E Andres Houseman; Brock C Christensen; Ru-Fang Yeh; Carmen J Marsit; Margaret R Karagas; Margaret Wrensch; Heather H Nelson; Joseph Wiemels; Shichun Zheng; John K Wiencke; Karl T Kelsey
Journal:  BMC Bioinformatics       Date:  2008-09-09       Impact factor: 3.169

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  23 in total

Review 1.  Principles and challenges of genomewide DNA methylation analysis.

Authors:  Peter W Laird
Journal:  Nat Rev Genet       Date:  2010-03       Impact factor: 53.242

2.  Genomic perturbations reveal distinct regulatory networks in intrahepatic cholangiocarcinoma.

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3.  Reducing the risk of false discovery enabling identification of biologically significant genome-wide methylation status using the HumanMethylation450 array.

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4.  Integrated profiling reveals a global correlation between epigenetic and genetic alterations in mesothelioma.

Authors:  Brock C Christensen; E Andres Houseman; Graham M Poage; John J Godleski; Raphael Bueno; David J Sugarbaker; John K Wiencke; Heather H Nelson; Carmen J Marsit; Karl T Kelsey
Journal:  Cancer Res       Date:  2010-06-29       Impact factor: 12.701

5.  Genetic and epigenetic somatic alterations in head and neck squamous cell carcinomas are globally coordinated but not locally targeted.

Authors:  Graham M Poage; Brock C Christensen; E Andres Houseman; Michael D McClean; John K Wiencke; Marshall R Posner; John R Clark; Heather H Nelson; Carmen J Marsit; Karl T Kelsey
Journal:  PLoS One       Date:  2010-03-11       Impact factor: 3.240

6.  SeSAMe: reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions.

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7.  Recursively partitioned mixture model clustering of DNA methylation data using biologically informed correlation structures.

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9.  DNA methylation analyses of urothelial carcinoma reveal distinct epigenetic subtypes and an association between gene copy number and methylation status.

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Journal:  Epigenetics       Date:  2012-06-18       Impact factor: 4.528

10.  The epigenetic landscape of oral squamous cell carcinoma.

Authors:  P V Jithesh; J M Risk; A G Schache; J Dhanda; B Lane; T Liloglou; R J Shaw
Journal:  Br J Cancer       Date:  2013-01-03       Impact factor: 7.640

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