Small sample-based genotype and phenotype association analysis method in multi-omics data

Abstract

The invention discloses a small sample-based genotype and phenotype correlation analysis method in multi-omics data. The method specifically comprises the following steps: generating a weighted undirected gene association graph by using a protein network and a gene expression value, and clustering the undirected graph by using an SPICi clustering method to generate a gene cluster; screening the gene clusters by using a group Lasso method; obtaining an SNP cluster corresponding to the screened gene cluster through the eQTL data; constructing each SNP cluster, the corresponding gene cluster and the phenotype into a three-layer network class block, performing regression operation on the association relationship between the SNP and the gene in each class block by adopting a sparse partial least square method, and performing operation on the association relationship between the gene and the phenotype by adopting logistic regression; and averaging the obtained prediction results of the blocks to obtain a final prediction result. The method can solve the problem that effective regression cannot be realized due to huge characteristic values under the condition of small samples in a three-layer network; wherein the prediction accuracy is improved, the biological significance is clearer and tissue specificity is considered.

Description

technical field [0001] The invention relates to the field of bioinformatics, in particular to a small sample-based method for researching the association between genotype and phenotype in multi-omics data. Background technique [0002] An important goal of current genetics is to establish a complete functional link between genotype and phenotype, the so-called genotype-phenotype map. Studying the relationship between genotype and phenotype can make the process of genetic variation more clear. Genome-wide association studies (GWAS) between common genotypes and phenotypes are an effective way to reveal the link between an individual's genetic background and a specific disease or trait. Its principle is to find out the difference sites on all genomes, and analyze the correlation between the difference sites and the phenotype. Over the past decade or so, numerous genome-wide association studies have identified many genetic variants associated with complex diseases or other tra...

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Problems solved by technology

[0006] Furthermore, the use of multi-omics methods to explore the relationship between genotype and phenotype requires that each omics data be the same sample set. Due to the huge amount of SNP features, the two types of multi-omics analysis methods require a large sample size when building models. , and due to the protection of patients' personal privacy and the requirements of each institution for data, it is difficult to obtain clinical data

Therefore, the public clinical data cannot meet the data requirements of the multi-omics data fusion method in terms of sample size or the number of omics.

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