935k dna methylation array infinium methylation epic beadchip kit  (INFINIUM Inc)

Journal: NAR Genomics and Bioinformatics

Article Title: Navigating Illumina DNA methylation data: biology versus technical artefacts

doi: 10.1093/nargab/lqae181

Figure Lengend Snippet: Workflow DNA methylation analysis pipeline – normalization and quality assessment. Samples are normalized using the Illumina-like process with the minfi package in R. Afterwards, beta values are calculated. The quality of each sample is assessed by the newly implemented DB-Score, BIN-Score and the three measures based on deviations from consistently high or low CM-Scores. Loci with a detection P- value > 0.01 were filtered out and samples with a loci call rate (LCR) < 98% are excluded.

Article Snippet: We want to highlight that the QC-Scores are specifically designed for use with the current DNA methylation BeadChip arrays from Illumina (450k and EPIC).

Techniques: DNA Methylation Assay

Journal: NAR Genomics and Bioinformatics

Article Title: Navigating Illumina DNA methylation data: biology versus technical artefacts

doi: 10.1093/nargab/lqae181

Figure Lengend Snippet: Application of the DNA methylation analysis pipeline. We applied our DNA methylation pipeline on four distinct cohorts, one cryo-preserved-based, one FFPE-based, on 5-azacytidine-treated samples and a large cohort of predominately cancer cell lines ( n = 1080), specifically highlighting the utility of the DB-Score and BIN-Score. ( A ) Correlation of DB-Score and BIN-Score from cryo-preserved samples of the ICGC MMML-Seq cohort (including 450k and EPIC array data). As the ICGC MMML-Seq cohort comprises 450k and EPIC array data, two normalization samples are displayed. Good quality: DB-Score < 1 and BIN-Score < 0.25; questionable quality: DB-Score > 1 or BIN-Score > 0.25; technical failure: DB-Score > 1 and BIN-Score > 0.25. ( B ) Comparison of 450k array and WGBS data from samples with a good DB- and BIN-Score. Pearson correlation was applied. See samples S7-S10 in panel (A). ( C ) Left panel (case S11: histogram and CNV-plot): Example with a questionable quality due to a good DB-Score but bad BIN-Score likely because of a large number of small duplications. Sample S11 in panel (A). Right panel (case 12: density plot and CNV-plot): Example of a sample with a questionable quality due to a bad DB-Score but good BIN-Score. Correlation with WGBS data demonstrated a robust concordance with array data demonstrated by Pearson correlation, suggesting an authentic biological effect. See sample S12 in panel (A). ( D ) Correlation of DB-Score and BIN-Score from FFPE tissues (EPIC array data). ( E ) Correlation of DB-Score and BIN-Score from 5-azacytidine (AZA)-treated samples. Cells from two cell lines (A549, KMST-6-TNF) were treated with AZA (duplicates). ( F ) Density plots of the AZA-treated samples and corresponding controls. ( G ) Correlation of DB-Score and BIN-Score from predominately cancer cell lines ( n = 1 080, GSE68379). ( H ) CNV-Plots of two distinct cell lines, one with a high BIN-Score (upper plot, BIN-Score: 0.265) and a cell line showing extensive genomic aberrations (lower plot).

Article Snippet: We want to highlight that the QC-Scores are specifically designed for use with the current DNA methylation BeadChip arrays from Illumina (450k and EPIC).

Techniques: DNA Methylation Assay, Comparison

Journal: Brain Pathology

Article Title: Exploiting nanopore sequencing for characterization and grading of IDH ‐mutant gliomas

doi: 10.1111/bpa.13203

Figure Lengend Snippet: A total of 19 clinical samples used for nCNV‐seq. (A) Classification of samples from patients with the IDH ‐mutant gliomas based on WHO Classification 2021. (B) Summary of demographic and molecular features of the 19 IDH ‐mutant gliomas. Each row represents a single case. IDH1 ‐R132H was tested by immunostaining and/or WGS. p TERT was tested by WGS. ATRX, alpha‐thalassemia/mental retardation syndrome X‐linked; CDKN2A/B, cyclin‐dependent kinase inhibitor 2A/B; EPIC array, Infinium MethylationEPIC BeadChip DNA methylation arrays; FISH, fluorescence in situ hybridization; IDH, isocitrate dehydrogenase; NGS, next‐generation sequencing; WHO CNS5, 2021 WHO Classification of Tumors of the Central Nervous System, Fifth Edition.

Article Snippet: Therefore, a variety of copy‐number variation (CNV) detection techniques have been tested clinically and compared to FISH, including comparative genomic hybridization [ ], single‐nucleotide polymorphism array [ ], Infinium MethylationEPIC BeadChip DNA methylation arrays (EPIC array; Illumina) [ ], and whole‐genome sequencing (WGS), the most efficient platform in CNV detection [ ].

Techniques: Mutagenesis, Immunostaining, DNA Methylation Assay, Fluorescence, In Situ Hybridization, Next-Generation Sequencing