A Bayesian hierarchical model to detect differentially methylated loci from single nucleotide resolution sequencing data.
about
Shape analysis of high-throughput transcriptomics experiment dataEpigenomic landscapes of retinal rods and conesThe DNA methyltransferase DNMT3C protects male germ cells from transposon activityRemoving unwanted variation in a differential methylation analysis of Illumina HumanMethylation450 array data.A Flexible, Efficient Binomial Mixed Model for Identifying Differential DNA Methylation in Bisulfite Sequencing Data.Detection of differentially methylated regions from bisulfite-seq data by hidden Markov models incorporating genome-wide methylation level distributions.A full Bayesian partition model for identifying hypo- and hyper-methylated loci from single nucleotide resolution sequencing data.Differential methylation analysis for BS-seq data under general experimental design.Methods for identifying differentially methylated regions for sequence- and array-based data.Detection of differentially methylated regions in whole genome bisulfite sequencing data using local Getis-Ord statistics.Statistical challenges in analyzing methylation and long-range chromosomal interaction dataStatistical method evaluation for differentially methylated CpGs in base resolution next-generation DNA sequencing data.Genome-wide DNA methylation analysis of the porcine hypothalamus-pituitary-ovary axis.MethylSig: a whole genome DNA methylation analysis pipeline.Using beta-binomial regression for high-precision differential methylation analysis in multifactor whole-genome bisulfite sequencing experiments.DRIMSeq: a Dirichlet-multinomial framework for multivariate count outcomes in genomics.Base-resolution methylation patterns accurately predict transcription factor bindings in vivo.De novo identification of differentially methylated regions in the human genome.swDMR: A Sliding Window Approach to Identify Differentially Methylated Regions Based on Whole Genome Bisulfite Sequencing.Detection of differentially methylated regions from whole-genome bisulfite sequencing data without replicates.Statistical methods for detecting differentially methylated regions based on MethylCap-seq data.An evaluation of methods to test predefined genomic regions for differential methylation in bisulfite sequencing data.A novel statistical method for quantitative comparison of multiple ChIP-seq datasetsA Bayesian Approach for Analysis of Whole-Genome Bisulfite Sequencing Data Identifies Disease-Associated Changes in DNA MethylationA survey of the approaches for identifying differential methylation using bisulfite sequencing data.Profiling the genome-wide DNA methylation pattern of porcine ovaries using reduced representation bisulfite sequencingA probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways.Chronic exposure to water pollutant trichloroethylene increased epigenetic drift in CD4(+) T cells.DNA methylation profiles of diverse Brachypodium distachyon align with underlying genetic diversity.Plasma cell differentiation is coupled to division-dependent DNA hypomethylation and gene regulationCumulative Impact of Polychlorinated Biphenyl and Large Chromosomal Duplications on DNA Methylation, Chromatin, and Expression of Autism Candidate Genes.Vector Integration Sites Identification for Gene-Trap Screening in Mammalian Haploid Cells.Statistical methods for detecting differentially methylated loci and regionsRapid recovery gene downregulation during excess-light stress and recovery in Arabidopsis.Transgenerational transmission of asthma risk after exposure to environmental particles during pregnancy.Comparative DNA methylation analysis to decipher common and cell type-specific patterns among multiple cell types.Tumor purity and differential methylation in cancer epigenomics.Bayesian genome- and epigenome-wide association studies with gene level dependence.Dental Pulp Stem Cells Model Early Life and Imprinted DNA Methylation Patterns.Targeted bisulfite sequencing of the dynamic DNA methylome
P2860
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P2860
A Bayesian hierarchical model to detect differentially methylated loci from single nucleotide resolution sequencing data.
description
2014 nî lūn-bûn
@nan
2014 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
A Bayesian hierarchical model ...... de resolution sequencing data.
@ast
A Bayesian hierarchical model ...... de resolution sequencing data.
@en
type
label
A Bayesian hierarchical model ...... de resolution sequencing data.
@ast
A Bayesian hierarchical model ...... de resolution sequencing data.
@en
prefLabel
A Bayesian hierarchical model ...... de resolution sequencing data.
@ast
A Bayesian hierarchical model ...... de resolution sequencing data.
@en
P2860
P356
P1476
A Bayesian hierarchical model ...... de resolution sequencing data.
@en
P2093
Karen N Conneely
P2860
P356
10.1093/NAR/GKU154
P407
P50
P577
2014-02-22T00:00:00Z