Genomic chromosome locations of predicted DMR and overlap between germ cell and somatic cell predicted sites.

<p>(A) Germ cell DHVPP and somatic cell SG predicted number of (+3) sites in each chromosome. (B) Germ cell DHVPP and somatic cell SG predicted number of single sites in each chromosome. (C) Overlap between predicted DMR (sites) from the two different datasets. (D) Overlap between predicted DMR (sites) from the two different datasets.</p

CpG density plot showing number of predicted DMR sites correlated with CpG density.

<p>(A) CpG density from the potential predicted germ cell DMR sites (3,234) when DHVPP is used as the training set to predict genome-wide. (B) CpG density from the potential predicted somatic cell DMR sites (1,502) when SG is used as the training set to predict genome-wide. X-axis shows the number of CpG's per 100bases on average while Y-axis shows the number of sites.</p

Validation of the germ cell DMR data set.

<p>MXC-DDT used as positive testing set and Sox9SryTcf21 as non-DMR negative testing set. (A) Prediction of the training set DHVPP with the positive MXC-DDT and negative Sx9SryTcf21 validation data set. (B) Overlap of germ cell validation set MXC-DDT with predicted DHVPP single probe data set.</p

Chromosomal plot of somatic cell dataset SG shows the predicted 3+ sites and the clusters.

<p>Potential predicted DMR sites (1,503) when SG is used as the training set to predict on the rest of the genome. X-axis shows each of the 21 chromosomes while Y-axis shows the length of the chromosome with predicted potential DMR locations. Red lines in the bottom are shown as potential DMR sites and clusters (44) with blue boxes are shown on the top of each chromosomes.</p

Predictive power of repeat elements accuracy based on genomic location of 1k, 5k, 100k from the DMR.

<p>(A) Combined average when each group of repeat elements are used for prediction for DHVPP dataset. (B) Combined average when each group of repeat elements are used for prediction for SG dataset. Shows combined repeat elements in the 100k, 5k and 1k upstream and downstream regions.</p

Machine learning approach and training set description.

<p>(A) Two-step machine learning framework for DMR identification. (B) Description of datasets: germ cell DHVPP; somatic cell (SG); MXC-DDT; and non-DMR Sox9SryTcf21.</p

Predictive power of specific features.

<p>(A) Groups of features with their predictive power (percent accuracy) for the DHVPP dataset. (B) Groups of features with the predictive power (percent accuracy) for the SG dataset. The features include RE—Repeat Elements, TF- Transcription Factors, SM- Sequence Motifs, MM-Mammalian Motifs with their predictive power indicated.</p