Detection of Differentially Methylated Regions Using Bayes Factor for Ordinal Group Responses.

Dunbar Dunbar,George George,Ghosh Ghosh,Shi Shi,Ryu Ryu,Xu Xu

doi:10.3390/genes10090721

Dunbar Dunbar, George George + Show 4 more

Open Access

https://doi.org/10.3390/genes10090721

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Abstract

Researchers in genomics are increasingly interested in epigenetic factors such as DNA methylation, because they play an important role in regulating gene expression without changes in the DNA sequence. There have been significant advances in developing statistical methods to detect differentially methylated regions (DMRs) associated with binary disease status. Most of these methods are being developed for detecting differential methylation rates between cases and controls. We consider multiple severity levels of disease, and develop a Bayesian statistical method to detect the region with increasing (or decreasing) methylation rates as the disease severity increases. Patients are classified into more than two groups, based on the disease severity (e.g., stages of cancer), and DMRs are detected by using moving windows along the genome. Within each window, the Bayes factor is calculated to test the hypothesis of monotonic increase in methylation rates corresponding to severity of the disease versus no difference. A mixed-effect model is used to incorporate the correlation of methylation rates of nearby CpG sites in the region. Results from extensive simulation indicate that our proposed method is statistically valid and reasonably powerful. We demonstrate our approach on a bisulfite sequencing dataset from a chronic lymphocytic leukemia (CLL) study.

Highlights

It is widely accepted that cancer develops through a series of stages [1]
We propose a Bayesian approach and use the Bayes factor to test the association between methylation rates and disease severity
The Bayes factor was calculated for each moving window with window size of 6

Summary

Introduction

It is widely accepted that cancer develops through a series of stages [1]. It starts from a very limited area, not invasive and metastatic at the early stage, spreads to distant sites in the body, and becomes highly invasive and metastatic at the late stage. Patient survival times are significantly reduced at the late stages. The 5-year relative survival rate for lung cancer is. 54% at a localized stage, and is reduced to 4% at the distant stage [2]. More than half of lung cancers are diagnosed at a distant stage, which indicates that early diagnosis of cancer is the main factor to enhance patient survival. Identifying high-risk cancer patients at an early stage, would allow them to receive standard chemotherapy in advance

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