TEA: the epigenome platform for Arabidopsis methylome study.
Bisulfite sequencing (BS-seq) has become a standard technology to profile genome-wide DNA methylation at single-base resolution. It allows researchers to conduct genome-wise cytosine methylation analyses on issues about genomic imprinting, transcriptional regulation, cellular development and differentiation. One single data from a BS-Seq experiment is resolved into many features according to the sequence contexts, making methylome data analysis and data visualization a complex task.



We developed a streamlined platform, TEA, for analyzing and visualizing data from whole-genome BS-Seq (WGBS) experiments conducted in the model plant Arabidopsis thaliana. To capture the essence of the genome methylation level and to meet the efficiency for running online, we introduce a straightforward method for measuring genome methylation in each sequence context by gene. The method is scripted in Java to process BS-Seq mapping results. Through a simple data uploading process, the TEA server deploys a web-based platform for deep analysis by linking data to an updated Arabidopsis annotation database and toolkits.



TEA is an intuitive and efficient online platform for analyzing the Arabidopsis genomic DNA methylation landscape. It provides several ways to help users exploit WGBS data. TEA is freely accessible for academic users at: http://tea.iis.sinica.edu.tw .
Bioinformatics Program, Taiwan International Graduate Program, Institute of Information Science, Academia Sinica, Taipei, Taiwan.|Institute of Information Science, Academia Sinica, Taipei, Taiwan.|Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan.
Sheng-Yao
SY
Su
Institute of Information Science, Academia Sinica, Taipei, Taiwan.
Shu-Hwa
SH
Chen
Institute of Information Science, Academia Sinica, Taipei, Taiwan.
I-Hsuan
IH
Lu
Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan.
Yih-Shien
YS
Chiang
Institute of Information Science, Academia Sinica, Taipei, Taiwan.
Yu-Bin
YB
Wang
Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan. paoyang@gate.sinica.edu.tw.
Pao-Yang
PY
Chen
Institute of Information Science, Academia Sinica, Taipei, Taiwan. cylin@iis.sinica.edu.tw.|Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan. cylin@iis.sinica.edu.tw.|Institute of Fisheries Science, College of Life Science, National Taiwan University, Taipei, Taiwan. cylin@iis.sinica.edu.tw.
Chung-Yen
CY
Lin
D017360:Arabidopsis / Q000235:genetics* / Q000378:metabolism; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D019175:DNA Methylation; D044127:Epigenesis, Genetic; D057890:Epigenomics / Q000379:methods*; D063990:Gene Ontology; D057188:Workflow