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CaArray_EXP-598: TCGA (LUSC): Analysis of DNA Methylation for LUSC using Illumina Infinium HumanMethylation450 platform (jhu-usc)

ABSTRACT: TCGA Analysis of DNA Methylation for LUSC using Illumina Infinium HumanMethylation450 platform

ORGANISM(S): Homo sapiens

PROVIDER: GSE68825 | GEO | 2015/05/14

SECONDARY ACCESSION(S): PRJNA283876

REPOSITORIES: GEO

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caArray_EXP-598: TCGA (LUSC): Analysis of DNA Methylation for LUSC using Illumina Infinium HumanMethylation450 platform (jhu-usc)

Project description:TCGA Analysis of DNA Methylation for LUSC using Illumina Infinium HumanMethylation450 platform EXP-598 Assay Type: Methylation Provider: Illumina Array Designs: jhu-usc.edu_TCGA_HumanMethylation450 Organism: Homo sapiens (ncbitax) Tissue Sites: Lung Material Types: Control Analyte, Solid normal_tissue, organism_part, Primary solid_tumor Disease States: Lung Squamous Cell Carcinoma, NOT SPECIFIED

2015-05-14 | E-GEOD-68825 | biostudies-arrayexpress

caArray_EXP-620: TCGA (Coad): Analysis of DNA Methylation for COAD using Illumina Infinium HumanMethylation450 platform (Jhu-usc)

Project description:TCGA Analysis of DNA Methylation for COAD using Illumina Infinium HumanMethylation450 platform

2015-05-14 | GSE68838 | GEO

caArray_EXP-620: TCGA (Coad): Analysis of DNA Methylation for COAD using Illumina Infinium HumanMethylation450 platform (Jhu-usc)

Project description:TCGA Analysis of DNA Methylation for COAD using Illumina Infinium HumanMethylation450 platform EXP-620 Assay Type: Methylation Provider: Illumina Array Designs: jhu-usc.edu_TCGA_HumanMethylation450 Organism: Homo sapiens (ncbitax) Tissue Sites: Colon Material Types: Control Analyte, Solid normal_tissue, organism_part, Primary solid_tumor

2015-05-14 | E-GEOD-68838 | biostudies-arrayexpress

caArray_EXP-550: TCGA (READ): Analysis of DNA Methylation for rectal adenocarcinoma (READ) Using Illumina Infinium Human DNA Methylation 27 platform (HumanMethylation27)(jhu-usc)

Project description:TCGA Analysis of DNA Methylation for rectal adenocarcinoma (READ) Using Illumina Infinium Human DNA Methylation 27 platform

2015-05-12 | GSE68751 | GEO

caArray_EXP-550: TCGA (READ): Analysis of DNA Methylation for rectal adenocarcinoma (READ) Using Illumina Infinium Human DNA Methylation 27 platform (HumanMethylation27)(jhu-usc)

Project description:TCGA Analysis of DNA Methylation for rectal adenocarcinoma (READ) Using Illumina Infinium Human DNA Methylation 27 platform EXP-550 Assay Type: Methylation Provider: Illumina Array Designs: jhu-usc.edu_OV.HumanMethylation27.v2 Organism: home sapiens (ncbitax) Tissue Sites: rectal Material Types: Primary solid_tumor, Control Cell Line, organism_part, Solid normal_tissue Disease States: Rectal Adenocarcinoma, NOT SPECIFIED, [Not Available], Rectal Mucinous Adenocarcinoma

2015-05-12 | E-GEOD-68751 | biostudies-arrayexpress

SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips.

Project description:DNA methylation is the most widely studied epigenetic mark and is known to be essential to normal development and frequently disrupted in disease. The Illumina HumanMethylation450 BeadChip assays the methylation status of CpGs at 485,577 sites across the genome. Here we present Subset-quantile Within Array Normalization (SWAN), a new method that substantially improves the results from this platform by reducing technical variation within and between arrays. SWAN is available in the minfi Bioconductor package.

| S-EPMC3446316 | biostudies-literature

A framework for analyzing DNA methylation data from Illumina Infinium HumanMethylation450 BeadChip.

Project description:BACKGROUND:DNA methylation has been identified to be widely associated to complex diseases. Among biological platforms to profile DNA methylation in human, the Illumina Infinium HumanMethylation450 BeadChip (450K) has been accepted as one of the most efficient technologies. However, challenges exist in analysis of DNA methylation data generated by this technology due to widespread biases. RESULTS:Here we proposed a generalized framework for evaluating data analysis methods for Illumina 450K array. This framework considers the following steps towards a successful analysis: importing data, quality control, within-array normalization, correcting type bias, detecting differentially methylated probes or regions and biological interpretation. CONCLUSIONS:We evaluated five methods using three real datasets, and proposed outperform methods for the Illumina 450K array data analysis. Minfi and methylumi are optimal choice when analyzing small dataset. BMIQ and RCP are proper to correcting type bias and the normalized result of them can be used to discover DMPs. R package missMethyl is suitable for GO term enrichment analysis and biological interpretation.

| S-EPMC5907140 | biostudies-literature

caArray_laird-00224: TCGA Ovarian: Analysis of DNA Methylation for Ovarian Using Illumina Infinium Human DNA Methylation 27 platform (HumanMethylation27) (USC)

Project description:TCGA Analysis of DNA Methylation Using Illumina Infinium Human DNA Methylation 27 platform

2015-11-21 | GSE75268 | GEO

Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray.

Project description:DNA methylation, an important type of epigenetic modification in humans, participates in crucial cellular processes, such as embryonic development, X-inactivation, genomic imprinting and chromosome stability. Several platforms have been developed to study genome-wide DNA methylation. Many investigators in the field have chosen the Illumina Infinium HumanMethylation microarray for its ability to reliably assess DNA methylation following sodium bisulfite conversion. Here, we analyzed methylation profiles of 489 adult males and 357 adult females generated by the Infinium HumanMethylation450 microarray. Among the autosomal CpG sites that displayed significant methylation differences between the two sexes, we observed a significant enrichment of cross-reactive probes co-hybridizing to the sex chromosomes with more than 94% sequence identity. This could lead investigators to mistakenly infer the existence of significant autosomal sex-associated methylation. Using sequence identity cutoffs derived from the sex methylation analysis, we concluded that 6% of the array probes can potentially generate spurious signals because of co-hybridization to alternate genomic sequences highly homologous to the intended targets. Additionally, we discovered probes targeting polymorphic CpGs that overlapped SNPs. The methylation levels detected by these probes are simply the reflection of underlying genetic polymorphisms but could be misinterpreted as true signals. The existence of probes that are cross-reactive or of target polymorphic CpGs in the Illumina HumanMethylation microarrays can confound data obtained from such microarrays. Therefore, investigators should exercise caution when significant biological associations are found using these array platforms. A list of all cross-reactive probes and polymorphic CpGs identified by us are annotated in this paper.

| S-EPMC3592906 | biostudies-literature

MGMIN: A Normalization Method for Correcting Probe Design Bias in Illumina Infinium HumanMethylation450 BeadChips.

Project description:The Illumina Infinium HumanMethylation450 Beadchips have been widely utilized in epigenome-wide association studies (EWAS). However, the existing two types of probes (type I and type II), with the distribution of measurements of probes and dynamic range different, may bias downstream analyses. Here, we propose a method, MGMIN (M-values Gaussian-MIxture Normalization), to correct the probe designs based on M-values of DNA methylation. Our strategy includes fitting Gaussian mixture distributions to type I and type II probes separately, a transformation of M-values into quantiles and finally a dilation transformation based on M-values of DNA methylation to maintain the continuity of the data. Our method is validated on several public datasets on reducing probe design bias, reducing the technical variation and improving the ability to find biologically differential methylation signals. The results show that MGMIN achieves competitive performances compared to BMIQ which is a well-known normalization method on β-values of DNA methylation.

| S-EPMC7652792 | biostudies-literature

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