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Statistical genetics and its application to neuroimmunology
Author(s) -
Ogawa Kotaro,
Okada Yukinori
Publication year - 2018
Publication title -
clinical and experimental neuroimmunology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.297
H-Index - 15
ISSN - 1759-1961
DOI - 10.1111/cen3.12445
Subject(s) - imputation (statistics) , statistical genetics , genetic association , genome wide association study , single nucleotide polymorphism , computational biology , biology , neuroimmunology , genetics , genetic data , dna microarray , multiple sclerosis , genome , human genome , medicine , genotype , gene , computer science , population , machine learning , missing data , immunology , gene expression , immune system , environmental health
Statistical genetics is a field involving the analysis of genetic data. With the development of next‐generation sequencing and single‐nucleotide polymorphism microarrays, the amount of genetic data is increasing rapidly. Genome‐wide association studies are one example of the successful application of an approach based on statistical genetics. To shed light on neuroinflammatory diseases, such as multiple sclerosis, >100 000 people have been enrolled in the genome‐wide association study meta‐analysis, and 200 loci associated with multiple sclerosis have been detected. To utilize these genetic data for clinical medicine, development of novel methods of statistical genetics is warranted. Human leukocyte antigen imputation and in silico drug repositioning are good examples of such approaches.