Methods for high-throughput MethylCap-Seq data analysis

被引:0
|
作者
Benjamin AT Rodriguez
David Frankhouser
Mark Murphy
Michael Trimarchi
Hok-Hei Tam
John Curfman
Rita Huang
Michael WY Chan
Hung-Cheng Lai
Deval Parikh
Bryan Ball
Sebastian Schwind
William Blum
Guido Marcucci
Pearlly Yan
Ralf Bundschuh
机构
[1] The Ohio State University Comprehensive Cancer Center,Graduate Institute of Medical Sciences, Department of Obstetrics and Gynecology
[2] Tri-Service General Hospital,Department of Life Science
[3] National Defense Medical Center,Departments of Physics and Biochemistry
[4] National Chung Cheng University,undefined
[5] Center for RNA Biology,undefined
[6] The Ohio State University,undefined
来源
BMC Genomics | / 13卷
关键词
Acute Myeloid Leukemia Patient; Genomic Feature; Data Visualization; Ovarian Cancer Sample; Short Read Aligner;
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] Methods for high-throughput MethylCap-Seq data analysis
    Rodriguez, Benjamin A. T.
    Frankhouser, David
    Murphy, Mark
    Trimarchi, Michael
    Tam, Hok-Hei
    Curfman, John
    Huang, Rita
    Chan, Michael W. Y.
    Lai, Hung-Cheng
    Parikh, Deval
    Ball, Bryan
    Schwind, Sebastian
    Blum, William
    Marcucci, Guido
    Yan, Pearlly
    Bundschuh, Ralf
    BMC GENOMICS, 2012, 13
  • [2] Statistical methods for detecting differentially methylated regions based on MethylCap-seq data
    Ayyala, Deepak N.
    Frankhouser, David E.
    Ganbat, Javkhlan-Ochir
    Marcucci, Guido
    Bundschuh, Ralf
    Yan, Pearlly
    Lin, Shili
    BRIEFINGS IN BIOINFORMATICS, 2016, 17 (06) : 926 - 937
  • [3] PrEMeR-CG: inferring nucleotide level DNA methylation values from MethylCap-seq data
    Frankhouser, David E.
    Murphy, Mark
    Blachly, James S.
    Park, Jincheol
    Zoller, Mike W.
    Ganbat, Javkhlan-Ochir
    Curfman, John
    Byrd, John C.
    Lin, Shili
    Marcucci, Guido
    Yan, Pearlly
    Bundschuh, Ralf
    BIOINFORMATICS, 2014, 30 (24) : 3567 - 3574
  • [4] The developmental epigenomics toolbox: ChIP-seq and MethylCap-seq profiling of early zebrafish embryos
    Bogdanovic, Ozren
    Fernandez-Minan, Ana
    Tena, Juan J.
    de la Calle-Mustienes, Elisa
    Luis Gomez-Skarmeta, Jose
    METHODS, 2013, 62 (03) : 207 - 215
  • [5] Comparing the normalization methods for the differential analysis of Illumina high-throughput RNA-Seq data
    Peipei Li
    Yongjun Piao
    Ho Sun Shon
    Keun Ho Ryu
    BMC Bioinformatics, 16
  • [6] Comparing the normalization methods for the differential analysis of Illumina high-throughput RNA-Seq data
    Li, Peipei
    Piao, Yongjun
    Shon, Ho Sun
    Ryu, Keun Ho
    BMC BIOINFORMATICS, 2015, 16
  • [7] Whole-genome DNA methylation profiling using MethylCap-seq
    Brinkman, Arie B.
    Simmer, Femke
    Ma, Kelong
    Kaan, Anita
    Zhu, Jingde
    Stunnenberg, Hendrik G.
    METHODS, 2010, 52 (03) : 232 - 236
  • [8] High-frequency aberrantly methylated targets in pancreatic adenocarcinoma identified via global DNA methylation analysis using methylCap-seq
    Yangxing Zhao
    Jinfeng Sun
    Hongyu Zhang
    Shicheng Guo
    Jun Gu
    Wei Wang
    Ning Tang
    Xiaoyu Zhou
    Jian Yu
    Clinical Epigenetics, 2014, 6
  • [9] Computational Methods for Analysis of High-Throughput Screening Data
    Balakin, Konstantin V.
    Savchuk, Nikolay P.
    CURRENT COMPUTER-AIDED DRUG DESIGN, 2006, 2 (01) : 1 - 19
  • [10] Statistical methods for the analysis of high-throughput metabolomics data
    Bartel, Joerg
    Krumsiek, Jan
    Theis, Fabian J.
    COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 2013, 4 (05):