Detection and accurate false discovery rate control of differentially methylated regions from whole genome bisulfite sequencing

Differential methylation analysis for BS-seq data under general experimental design

(2016) Yongseok Park et al.   BIOINFORMATICS

DNMT3A Loss Drives Enhancer Hypomethylation in FLT3-ITD-Associated Leukemias

(2016) Liubin Yang et al.   CANCER CELL

Genetics: profiling DNA methylation and beyond

(2016) Vivien Marx   NATURE METHODS

HMM-DM: identifying differentially methylated regions using a hidden Markov model

(2016) Xiaoqing Yu et al.   Statistical Applications in Genetics and Molecular Biology

HMM-DM: identifying differentially methylated regions using a hidden Markov model

(2016) Xiaoqing Yu et al.   Statistical Applications in Genetics and Molecular Biology

Identification of differentially methylated loci using wavelet-based functional mixed models

(2015) Wonyul Lee et al.   BIOINFORMATICS

metilene: fast and sensitive calling of differentially methylated regions from bisulfite sequencing data

(2015) Frank Jühling et al.   GENOME RESEARCH

Bacterial infection remodels the DNA methylation landscape of human dendritic cells

(2015) Alain Pacis et al.   GENOME RESEARCH

Human body epigenome maps reveal noncanonical DNA methylation variation

(2015) Matthew D. Schultz et al.   NATURE

M3D: a kernel-based test for spatially correlated changes in methylation profiles

(2014) Tom R. Mayo et al.   BIOINFORMATICS

MethylSig: a whole genome DNA methylation analysis pipeline

(2014) Yongseok Park et al.   BIOINFORMATICS

Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays

(2014) Martin J. Aryee et al.   BIOINFORMATICS

Using beta-binomial regression for high-precision differential methylation analysis in multifactor whole-genome bisulfite sequencing experiments

(2014) Egor Dolzhenko et al.   BMC BIOINFORMATICS

Coverage recommendations for methylation analysis by whole-genome bisulfite sequencing

(2014) Michael J Ziller et al.   NATURE METHODS

De novo detection of differentially bound regions for ChIP-seq data using peaks and windows: controlling error rates correctly

(2014) Aaron T.L. Lun et al.   NUCLEIC ACIDS RESEARCH

Bisulfighter: accurate detection of methylated cytosines and differentially methylated regions

(2014) Yutaka Saito et al.   NUCLEIC ACIDS RESEARCH

MOABS: model based analysis of bisulfite sequencing data

(2014) Deqiang Sun et al.   GENOME BIOLOGY

Statistical methods for detecting differentially methylated loci and regions

(2014) Mark D. Robinson et al.   Frontiers in Genetics

Detection of significantly differentially methylated regions in targeted bisulfite sequencing data

(2013) Katja Hebestreit et al.   BIOINFORMATICS

DNA methylation: roles in mammalian development

(2013) Zachary D. Smith et al.   NATURE REVIEWS GENETICS

Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies

(2012) Andrew E Jaffe et al.   INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

A solution to separation for clustered binary data

(2012) José Cortiñas Abrahantes et al.   STATISTICAL MODELLING

BSmooth: from whole genome bisulfite sequencing reads to differentially methylated regions

(2012) Kasper D Hansen et al.   GENOME BIOLOGY

methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles

(2012) Altuna Akalin et al.   GENOME BIOLOGY

Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications

(2011) Felix Krueger et al.   BIOINFORMATICS

False discovery rate for scanning statistics

(2011) D. O. Siegmund et al.   BIOMETRIKA

Tackling the widespread and critical impact of batch effects in high-throughput data

(2010) Jeffrey T. Leek et al.   NATURE REVIEWS GENETICS

A weakly informative default prior distribution for logistic and other regression models

(2009) Andrew Gelman et al.   Annals of Applied Statistics

The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores

(2009) Rafael A Irizarry et al.   NATURE GENETICS