z-logo
open-access-imgOpen Access
MethRaFo: MeDIP-seq methylation estimate using a Random Forest Regressor
Author(s) -
Jun Ding,
Ziv BarJoseph
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx449
Subject(s) - methylated dna immunoprecipitation , computer science , dna methylation , python (programming language) , cpg site , differentially methylated regions , profiling (computer programming) , computational biology , data mining , biology , genetics , gene expression , gene , operating system
Profiling of genome wide DNA methylation is now routinely performed when studying development, cancer and several other biological processes. Although Whole genome Bisulfite Sequencing provides high-quality methylation measurements at the resolution of nucleotides, it is relatively costly and so several studies have used alternative methods for such profiling. One of the most widely used low cost alternatives is MeDIP-Seq. However, MeDIP-Seq is biased for CpG enriched regions and thus its results need to be corrected in order to determine accurate methylation levels.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom