Comparison of different cell type correction methods for genome-scale epigenetics studies
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Summary
Results from real data and simulations indicated that SVA is recommended when the focus is on the identification of informative CpGs, and when appropriate reference data are available, the method implemented in the minfi package is recommended.
- Type
- article
- Published
- 2017-04-14
- Cited by
- 69
- References
- 50
- OpenAlex
- https://openalex.org/W28410574
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:722888
Keywords
Local Multipoint Distribution Service, Computer science, Attenuation, Channel (broadcasting), Telecommunications
References
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- Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays
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- Epigenome-wide association studies without the need for cell-type composition
- Arsenic induces DNA damage via reactive oxygen species in human cells
- Gender specific differences in levels of DNA methylation at selected loci from human total blood: a tendency toward higher methylation levels in males
- Differential DNA Methylation in Purified Human Blood Cells: Implications for Cell Lineage and Studies on Disease Susceptibility
- Effect of Arsenic on Regulatory T Cells
- Colorectal cancer DNA methylation marker panel validated with high performance in Non-Hodgkin lymphoma
- Chronic Arsenic Exposure and Cardiac Repolarization Abnormalities with QT Interval Prolongation in a Population-based Study
- Associations between maternal phthalate exposure and cord sex hormones in human infants.
- Drinking-Water Arsenic Exposure Modulates Gene Expression in Human Lymphocytes from a U.S. Population
- Monomethylarsonous Acid Inhibited Endogenous Cholesterol Biosynthesis in Human Skin Fibroblasts
- Epigenetic changes associated with inflammation in breast cancer patients treated with chemotherapy
- The Relationship of DNA Methylation with Age, Gender and Genotype in Twins and Healthy Controls
- FaST linear mixed models for genome-wide association studies
- Heterogeneity in White Blood Cells Has Potential to Confound DNA Methylation Measurements
Cited by
- Cell-type deconvolution from DNA methylation: a review of recent applications
- Epigenetic research in multiple sclerosis: progress, challenges, and opportunities.
- Consistency and Variability of DNA Methylation in Women During Puberty, Young Adulthood, and Pregnancy
- CRP polymorphisms and DNA methylation of the AIM2 gene influence associations between trauma exposure, PTSD, and C-reactive protein
- Statistical and integrative system-level analysis of DNA methylation data
- Analysis of DNA modifications in aging research
- LFMM 2.0: Latent factor models for confounder adjustment in genome and epigenome-wide association studies
- Age prediction of children and adolescents aged 6-17 years: an epigenome-wide analysis of DNA methylation
- Population DNA methylation studies in the Developmental Origins of Health and Disease (DOHaD) framework
- A comparative analysis of cell-type adjustment methods for epigenome-wide association studies based on simulated and real data sets
- A Possible Mechanism For Leptin’s Role In Lung Function Independent Of Body Mass Index: Investigating Leptin’s Genotype, DNA, Methylation, And Serum Protein Levels
- Assessment of dried blood spots for DNA methylation profiling
- Longitudinal investigation of DNA methylation changes preceding adolescent psychotic experiences
- Epigenetic Marks of Prenatal Air Pollution Exposure Found in Multiple Tissues Relevant for Child Health
- Association of Arsenic Exposure with Whole Blood DNA Methylation: An Epigenome-Wide Study of Bangladeshi Adults
- Prenatal Particulate Air Pollution and DNA Methylation in Newborns: An Epigenome-Wide Meta-Analysis
- Best practices in DNA methylation: lessons from inflammatory bowel disease, psoriasis and ankylosing spondylitis
- Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease
- Rheumatoid arthritis-relevant DNA methylation changes identified in ACPA-positive asymptomatic individuals using methylome capture sequencing
- TOAST: improving reference-free cell composition estimation by cross-cell type differential analysis
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