Prediction of DNA methylation for every CpG loci in chromosome 18 in embryonic stem cells using support vector machine

Embryonic stem cells (ESC) are pluripotent cells, had been obtained from an embryo in a few days old in which all 200+ kinds of tissue in the human body originate a fact which makes them potentially important in medicine. DNA methylation on the other hand plays an important role in gene modification leading to change in biological processes as pluripotent and differentiated cells or reasoned for many diseases. Cytosines in CpG dinucleotides can be methylated leading to concentrate to predict methylation in CpG loci inside DNA by helping of results coming from whole genome bisulfite sequencing (WGBS) experiment but very expensive and Illumina 450K array experiment that covers less than 2% of CpG locus. A machine learning model has been implemented using support vector machine classifier (SVM) that is trained on chromosome 18 of the human H1 ESC with both 450K array data and WGBS. The SVM gives an accuracy of 99% when testing on chromosome 18 of the human H9 ESC to predict methyl or un-methyl for each CpG loci in the chromosome separately.