MeDEStrand: an improved method to infer genome-wide absolute methylation levels from DNA enrichment data

被引:0
|
作者
Jingting Xu
Shimeng Liu
Ping Yin
Serdar Bulun
Yang Dai
机构
[1] University of Illinois at Chicago,Department of Bioengineering
[2] Feinberg School of Medicine,Division of Reproductive Science in Medicine, Department of Obstetrics and Gynecology
[3] Northwestern University,undefined
来源
BMC Bioinformatics | / 19卷
关键词
DNA methylation; MeDIP-seq; RRBS; CpG bias; Sigmoid function;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [1] MeDEStrand: an improved method to infer genome-wide absolute methylation levels from DNA enrichment data
    Xu, Jingting
    Liu, Shimeng
    Yin, Ping
    Bulun, Serdar
    Dai, Yang
    BMC BIOINFORMATICS, 2018, 19
  • [2] Gene set enrichment analysis for genome-wide DNA methylation data
    Jovana Maksimovic
    Alicia Oshlack
    Belinda Phipson
    Genome Biology, 22
  • [3] Gene set enrichment analysis for genome-wide DNA methylation data
    Maksimovic, Jovana
    Oshlack, Alicia
    Phipson, Belinda
    GENOME BIOLOGY, 2021, 22 (01)
  • [4] Profiling genome-wide DNA methylation
    Yong, Wai-Shin
    Hsu, Fei-Man
    Chen, Pao-Yang
    EPIGENETICS & CHROMATIN, 2016, 9
  • [5] Profiling genome-wide DNA methylation
    Wai-Shin Yong
    Fei-Man Hsu
    Pao-Yang Chen
    Epigenetics & Chromatin, 9
  • [6] A streamlined method for analysing genome-wide DNA methylation patterns from low amounts of FFPE DNA
    Ludgate, Jackie L.
    Wright, James
    Stockwell, Peter A.
    Morison, Ian M.
    Eccles, Michael R.
    Chatterjee, Aniruddha
    BMC MEDICAL GENOMICS, 2017, 10
  • [7] A streamlined method for analysing genome-wide DNA methylation patterns from low amounts of FFPE DNA
    Jackie L. Ludgate
    James Wright
    Peter A. Stockwell
    Ian M. Morison
    Michael R. Eccles
    Aniruddha Chatterjee
    BMC Medical Genomics, 10
  • [8] Phenotype prediction based on genome-wide DNA methylation data
    Wilhelm, Thomas
    BMC BIOINFORMATICS, 2014, 15
  • [9] Phenotype prediction based on genome-wide DNA methylation data
    Thomas Wilhelm
    BMC Bioinformatics, 15
  • [10] On the potential of models for location and scale for genome-wide DNA methylation data
    Simone Wahl
    Nora Fenske
    Sonja Zeilinger
    Karsten Suhre
    Christian Gieger
    Melanie Waldenberger
    Harald Grallert
    Matthias Schmid
    BMC Bioinformatics, 15