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A Composite Framework for the Statistical Analysis of Epidemiological DNA Methylation Data with the Infinium Human Methylation 450K BeadChip

ABSTRACT: High-throughput DNA methylation profiling exploits microarray technologies thus providing a wealth of data, which however solicits rigorous, generic and analytical pipelines for an efficient systems level analysis and interpretation. In the present study, we utilize the Illumina's Infinium Human Methylation 450K BeadChip platform in an epidemiological cohort, targeting to associate interesting methylation patterns with breast cancer predisposition. The computational framework proposed here extends the -established in transcriptomic microarrays- logarithmic ratio of the Methylated versus the Unmethylated signal intensities, quoted as M-value. Moreover, intensity-based correction of the M-signal distribution is introduced in order to correct for batch effects and probe-specific errors in intensity measurements. This is accomplished through the estimation of intensity-related error measures from quality control samples included in each chip. Moreover, robust statistical measures based on coefficient variation measurements of DNA methylation between control and case samples alleviate the impact of technical variation. The results presented here are juxtaposed to those derived by applying classical pre-processing and statistical selection methodologies. Overall, in comparison to traditional approaches, the introduced framework's superior performance in terms of technical bias correction, along with its generic character, support its suitability for various microarray technologies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE52635 | GEO | 2016/01/01

SECONDARY ACCESSION(S): PRJNA229508

REPOSITORIES: GEO

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Project description:To examine the effect of wtAPE1 and ubiquitin-APE1 fusion proteins on global gene expression. Total RNA from HEK293 derivatives that express vector alone (ctl), wt-APE1, or ubiquitin-APE1 fusion in the presence of doxycycline were analyzed. Three HEK293 derivatives expressing none (vector), wtAPE1, or Ub-APE1 fusion linked at APE1's 24th Lys were incubated with/without doxycycline (dox) 2 µg/ml for 16 hr. Each -/+ dox cultures were triplicated. Total RNA was extracted (Qiagen) and then analyzed by LSU's bioinformatics core. The quality and quantity of total RNA was assessed using an ND-1000 Spectrophometer (NanoDrop, Wilmington, DE), NanoChip assay and Bioanalyzer 2100 (Agilent). All samples were of high integrity with RIN # greater than 7 and A260/280 greater than 1.8. Procedures for cDNA synthesis, sense target labeling, and hybridization were carried out as described at http://media.affymetrix.com/support/technical/appnotes/wt_appnote.pdf (Affymetrix, Redwood City, CA). All experiments were performed using GeneChip Exon 1.0 ST Arrays and Whole Transcript Sense Target labeling Assay (version 4, Affymetrix). Overnight hybridization of fragmented single-stranded DNA was carried out in an Affymetrix GeneChip Hybridization Oven 640, then washed and stained with streptavidin-phycoerythrin using GeneChip 450 Microfluidics Station (Affymetrix). Chips were scanned with an Affymetrix High Resolution 3000 (G7) scanner. Signal and background intensities were quantitated by pixel intensity using Affymetrix GeneChip Operating Software (GCOS 1.4). Array quality control assessment was carried out using Robust Multi-chip Analysis (RMA) workflow for Core probesets in Expression Console (Affymetrix). Gene-level analysis for differential gene expression was analyzed in GeneSpring 7.3x (Agilent Technologies) using the sample CHP files. The RMA method was used for the background correction, normalization and average expression measures for the probesets. An expression filter (20th percentile cutoff) was applied to remove genes with low signal intensity values. For differential gene expression analysis, the Welch ANOVA test with asymptotic p-value computation was applied and transcripts with p-value (< 0.05) and fold change (2.0 fold) were selected.

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A Composite Framework for the Statistical Analysis of Epidemiological DNA Methylation Data with the Infinium Human Methylation 450K BeadChip

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