Accurate prediction method for pathogenic genetic variation

Abstract

The invention discloses an accurate prediction method for pathogenic genetic variation. Known pathogenic variations are classified into two types: database variation and training set positive variation; partial evidences in an ACMG guide are obtained through the database variation; training set positive genetic variation data and corresponding phenotypic data of a patient are simulated through a random extraction method; guide related features are calculated; phenotype related features are calculated by utilizing an ERIC-based calculation method; and in combination with existing pathogenicityjudgment related features, and by utilizing a machine learning algorithm, variation pathogenicity prediction performed by comprehensively considering genotype data and phenotype data is realized. Themethod solves the problem that accurate prediction of variation pathogenicity cannot be performed due to incomplete clinical phenotype data, noises and inaccurate description in an actual scene.

Description

technical field [0001] The invention relates to a prediction method, in particular to an accurate prediction method of pathogenic genetic variation. Background technique [0002] Rare disease genetic prediction refers to the process of finding causative genetic variants from a patient's genome that can explain the patient's clinical phenotype. Accurate and rapid genetic prediction is related to the later treatment, care and even life of patients. However, it is very difficult to accurately predict the pathogenic genetic variation. In actual scenarios, a series of problems such as incomplete clinical phenotype data, noise and inaccurate description make it impossible to accurately predict the pathogenicity of the variation. Contents of the invention [0003] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides an accurate prediction method of pathogenic genetic variation, which solves the problem of incomplete clinical phenotype data,...

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Problems solved by technology

[0003] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides an accurate prediction method of pathogenic genetic variation, which solves the problem of incomplete clinical phenotype data, noise and inaccurate description in actual scenarios, which lead to the inability to carry out mutation-causing disease. The problem of accurate prediction of sex

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