Detecting Genetic Disposition of Ethnicity to Autoimmune Diseases via Clustering

Senturk D., ORMAN G. K.

2021 IEEE International Conference on Big Data, Big Data 2021, Virtual, Online, Amerika Birleşik Devletleri, 15 - 18 Aralık 2021, ss.4761-4769 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/bigdata52589.2021.9671698
  • Basıldığı Şehir: Virtual, Online
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.4761-4769
  • Anahtar Kelimeler: cluster analysis, clustering algorithms, autoimmune diseases, HLA genes, population genetics, MAJOR HISTOCOMPATIBILITY COMPLEX, HLA CLASS-I, CROHNS-DISEASE, SUSCEPTIBILITY, MHC, LINKAGE, REGION, EPIDEMIOLOGY, ASSOCIATION, PREVALENCE
  • Galatasaray Üniversitesi Adresli: Evet

Özet

© 2021 IEEE.Most autoimmune diseases are generally influenced by HLA genes, which play a role in their onset and progression. In most cases, they are not counted as a diagnostic criterion for autoimmune diseases, but they act as a predisposing agent for the onset of the disease. The goal of this research is to look at the link between disease, genetics, and ethnicity. By clustering the HLA genes predisposing to selected autoimmune diseases using different clustering algorithms, we isolated the clusters that contained the samples having predisposing genes. After carrying out a homogeneity analysis, we arrived at the results concerning the ethnicity of the samples predisposed to the corresponding diseases. A well-known validation metric, the silhouette coefficient, is used to assess the methods. The accuracy of the findings is determined by comparing final clusters of HLA genes and the literature on the epidemiology of selected autoimmune diseases. The results demonstrate that clustering assists to find predisposing genes in distinct groups.