Swarnaseetha Adusumalli, Mohd Feroz Mohd Omar, Richie Soong, Touati Benoukraf

Swarnaseetha Adusumalli received her Master in Bioinformatics degree from the Nanyang Technological University, Singapore. She has a broad experience in the analysis of different high-throughput sequencing data sets. She was a bioinformatician at the Cancer Science Institute of Singapore, National University of Singapore, and recently joined the Genome Institute of Singapore, A*STAR.
Mohd Feroz Mohd Omar is a PhD student in Oncology at the National University of Singapore. He holds a Bachelor in Biotechnology degree from Flinders University, Australia. He is interested in elucidation of epigenetic cancer biomarkers using high-throughput sequencing and molecular biology.
Richie Soong is Senior Principal Investigator at the Cancer Science Institute of Singapore, Associate Professor at the National University of Singapore and the Chief of the Centre for Translational Research and Diagnostics, which combines the largest biosample repository in Singapore, a translational research laboratory and two clinical molecular diagnostics centers.
Touati Benoukraf holds a PhD in Computational Biology from the University of Aix-Marseille II, France. He is currently Research Assistant Professor at the Cancer Science Institute of Singapore, National University of Singapore. His interests include the study of epigenetic aberrations in cancers using high-throughput sequencing technologies.


The combination of DNA bisulfite treatment with high-throughput sequencing technologies has enabled investigation of genome-wide DNA methylation beyond CpG sites and CpG islands. These technologies have opened new avenues to understand the interplay between epigenetic events, chromatin plasticity and gene regulation. However, the processing, managing and mining of this huge volume of data require specialized computational tools and statistical methods that are yet to be standardized. Here, we describe a complete bisulfite sequencing analysis workflow, including recently developed programs, highlighting each of the crucial analysis steps required, i.e. sequencing quality control, reads alignment, methylation scoring, methylation heterogeneity assessment, genomic features annotation, data visualization and determination of differentially methylated cytosines. Moreover, we discuss the limitations of these technologies and considerations to perform suitable analyses.

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