Identifying the Risky SNP of Osteoporosis with ID3-PEP Decision Tree Algorithm

Jincai Yang,Xiaohua Hu,Xingpeng Jiang,Qingyang Huang,Xianjun Shen,Huichao Gu

doi:10.1155/2017/9194801

Abstract

In the past 20 years, much progress has been made on the genetic analysis of osteoporosis. A number of genes and SNPs associated with osteoporosis have been found through GWAS method. In this paper, we intend to identify the suspected risky SNPs of osteoporosis with computational methods based on the known osteoporosis GWAS-associated SNPs. The process includes two steps. Firstly, we decided whether the genes associated with the suspected risky SNPs are associated with osteoporosis by using random walk algorithm on the PPI network of osteoporosis GWAS-associated genes and the genes associated with the suspected risky SNPs. In order to solve the overfitting problem in ID3 decision tree algorithm, we then classified the SNPs with positive results based on their features of position and function through a simplified classification decision tree which was constructed by ID3 decision tree algorithm with PEP (Pessimistic-Error Pruning). We verified the accuracy of the identification framework with the data set of GWAS-associated SNPs, and the result shows that this method is feasible. It provides a more convenient way to identify the suspected risky SNPs associated with osteoporosis.

Highlights

Osteoporosis is a type of systemic skeletal disease that is characterized by reduced bone mass and microarchitecture deterioration of bone tissues, thereby leading to the loss of strength and increased risk of fractures [1]
We identified the suspected risky SNPs associated with osteoporosis by algorithm based on the analysis of osteoporosis genome-wide association study (GWAS)-associated SNPs with the method mentioned above [9]
We constructed a Protein-Protein Interaction (PPI) network based on the Protein-Protein Interaction analysis of the osteoporosis GWAS-associated genes and the genes associated with suspected risky SNPs and identify whether the genes associated with the suspected risky SNPs are associated with osteoporosis through random walk algorithm based on Markov chain

Summary

Introduction

Osteoporosis is a type of systemic skeletal disease that is characterized by reduced bone mass and microarchitecture deterioration of bone tissues, thereby leading to the loss of strength and increased risk of fractures [1]. It is one of the agerelated diseases with arteriosclerosis, hypertension, diabetes, and cancer. With the completion of the International HapMap Project and 1000 Genomes Project, about ten millions SNPs of human were annotated, among which more than 3 million are common SNPs. Genetic analysis has reached the stage of genome-wide association study (GWAS). The GWAS is applied to the study of 40 kinds of diseases that are related to more than 500 thousands SNPs [2]

Methods

Results

Conclusion