Open AccessSimilarity study of single nucleotide polymorphism (SNPs) data
Author(s) -
Wenjun Yu,
Bin Hu,
Yu Huang
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/768/5/052135
Subject(s) - single nucleotide polymorphism , cluster analysis , genetic data , consistency (knowledge bases) , computational biology , similarity (geometry) , biology , snp , data mining , genetics , bioinformatics , computer science , genotype , artificial intelligence , medicine , gene , population , image (mathematics) , environmental health
Based on the classification of patients, the analysis of genetic data has important complementary significance for predicting the progress of patients’ diseases and subsequent treatment. Massive sequencing data provides the basis for genetic analysis. We used GAMETES to simulate single-nucleotide polymorphisms (SNPS) data, and proposed correlation clustering analysis algorithms to provide a scientific basis for understanding the consistency of clinical data and genetic data.