Modern probabilistic and statistical approaches to search for nucleotide sequence options associated with integrated diseases
- Authors: Rytova A.I.1,2, Khlebus E.Y.1,3, Shevtsov A.E.2, Kutsenko V.A.2, Shcherbakova N.V.1, Zharikova A.A.1, Ershova A.I.1, Kiseleva A.V.1, Boytsov S.A.1, Yarovaya E.B.1,2, Meshkov A.N.1,4
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Affiliations:
- National Research Center for Preventive Medicine of the Ministry of Healthcare of the Russian Federation
- Department of Probability Theory
- Moscow Institute of Physics and Technology (State University)
- Department of Molecular and Cell Genetics
- Issue: Vol 53, No 10 (2017)
- Pages: 1091-1104
- Section: Reviews and Theoretical Articles
- URL: https://journals.rcsi.science/1022-7954/article/view/188472
- DOI: https://doi.org/10.1134/S1022795417100088
- ID: 188472
Cite item
Abstract
Complex diseases are a major important problem for modern medicine. These diseases arise under the influence of specific environmental and clinical-demographic factors, so-called risk factors, in combination with factors of genetic heredity. The contribution of genetic factors to the development of complex diseases is on average about 50%. The cause of complex diseases can be a lot of variants of the nucleotide sequence. In addition to common variants of single nucleotide polymorphisms (SNPs), rare variants also play a role in the development of complex diseases. This review presents modern probabilistic and statistical approaches to the search for gene variants and their combinations associated with complex diseases with an emphasis on methods for finding rare and unique variants. A comparative analysis of these approaches is performed, and a number of problems requiring resolution are formulated.
About the authors
A. I. Rytova
National Research Center for Preventive Medicine of the Ministry of Healthcare of the Russian Federation; Department of Probability Theory
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 101990; Moscow, 119991
E. Yu. Khlebus
National Research Center for Preventive Medicine of the Ministry of Healthcare of the Russian Federation; Moscow Institute of Physics and Technology (State University)
Author for correspondence.
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 101990; Dolgoprudny, Moscow oblast, 141701
A. E. Shevtsov
Department of Probability Theory
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 119991
V. A. Kutsenko
Department of Probability Theory
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 119991
N. V. Shcherbakova
National Research Center for Preventive Medicine of the Ministry of Healthcare of the Russian Federation
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 101990
A. A. Zharikova
National Research Center for Preventive Medicine of the Ministry of Healthcare of the Russian Federation
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 101990
A. I. Ershova
National Research Center for Preventive Medicine of the Ministry of Healthcare of the Russian Federation
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 101990
A. V. Kiseleva
National Research Center for Preventive Medicine of the Ministry of Healthcare of the Russian Federation
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 101990
S. A. Boytsov
National Research Center for Preventive Medicine of the Ministry of Healthcare of the Russian Federation
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 101990
E. B. Yarovaya
National Research Center for Preventive Medicine of the Ministry of Healthcare of the Russian Federation; Department of Probability Theory
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 101990; Moscow, 119991
A. N. Meshkov
National Research Center for Preventive Medicine of the Ministry of Healthcare of the Russian Federation; Department of Molecular and Cell Genetics
Email: elkhlebus@gmail.com
Russian Federation, Moscow, 101990; Moscow, 117997