System and method of analyzing association change pattern from multi-omics data

A technology of omics data and patterns, applied in the analysis of 2D or 3D molecular structure, informatics, bioinformatics, etc. The effect of applicability and strong compatibility

Inactive Publication Date: 2019-02-01
SHANTOU UNIV MEDICAL COLLEGE
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] However, the above-mentioned omics data analysis methods and systems are only for simple query and visualization of various omics data, and lack of methods to effectively integrate multi-level and different omics data, especially for analyzing correlation change patterns from multi-omics data method and system

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  • System and method of analyzing association change pattern from multi-omics data

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Embodiment 1

[0027] see figure 1 Shown, a system for analyzing patterns of association change from multi-omics data comprising:

[0028] Omics dataset 1 containing various omics data;

[0029] Binarization algorithm unit 2 for preprocessing omics datasets;

[0030] Association rule Apriori algorithm unit 3 for mining out the interrelated patterns of molecular changes.

[0031] In this embodiment, the omics data set includes genome exon sequencing data, genome copy number change data, genome methylation data, gene chip expression profile data, gene sequencing data, non-coding RNA expression data, and protein profile data . It should be noted that the omics data set of the present invention is not limited to include the above-mentioned types of data, and can be increased according to actual needs.

[0032] A method for analyzing patterns of association change from multi-omics data, comprising the steps of:

[0033] Step 1. Collecting and arranging various omics data to form an omics dat...

Embodiment 2

[0043] Utilizing the RNA-seq omics data of patients with esophageal cancer, a total of 14,179 interrelated rules between genes are excavated by the present invention. For example, one of the rules is {CDK1}==>{CCNB2}, the support is 0.435, the confidence is 0.808, and the lift is 1.416. It shows that CDK1 (cyclin dependent kinase 1, cyclin dependent kinase 1) and CCNB2 (cyclin B2, cyclin B2) have a high correlation. In the RNA-seq gene detection data of 43.5% of esophageal cancer patients, it was found that the two were differentially expressed at the same time; when CDK1 was differentially expressed, the probability of CCNB2 was also found to be differentially expressed as high as 80.8%; the probability of both differentially expressed at the same time was CDK1 was 1.416 times more likely to be differentially expressed independently of CCNB2.

Embodiment 3

[0045] In order to study the similarity of DNA methylation mechanism between esophageal cancer and breast cancer, we used the present invention to analyze the DNA methylomics data of esophageal cancer patients and breast cancer patients respectively, and then compared the results of the two. When the support degree is 0.4 and the confidence degree is 0.8, a total of 239 common association rules are found. We found that many of these rule-forming genes are cadherins, which play a role in cell adhesion. This result shows that the methylation of cell adhesion-related genes is a common carcinogenic mechanism of esophageal cancer and breast cancer.

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Abstract

The invention discloses a system and a method of analyzing an association change pattern from multi-omics data. The system comprises an omics data set containing multiple omics data, a binary algorithm unit for preprocessing the omics data set and an association rule Apriori algorithm unit for mining the mutual association pattern of each molecule change. Different omics data can be effectively integrated, and the analysis association change pattern in the multi-omics data can be well mined.

Description

technical field [0001] The present invention relates to the field of bioinformatics and computational data analysis, in particular to a system and method for analyzing association change patterns from multi-omics data. Background technique [0002] In recent years, with the rapid development of high-throughput sequencing technology, various omics data can be generated by sequencing the same sample. The multi-omics data here includes but is not limited to the following data: genomic exome sequencing data, genome copy number Change data, genome methylation data, gene chip expression profile data, gene sequencing data, non-coding RNA expression data, and protein mass spectrometry data, etc. In this way, when sequencing tools are applied to scientific research, researchers can study systematic changes in samples under experimental conditions from multiple perspectives such as DNA, RNA, and methylation; when sequencing tools are applied to clinical disease samples, doctors can O...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B15/00G16B50/00
Inventor 徐建震杨德印范健张凡陈丹泽
Owner SHANTOU UNIV MEDICAL COLLEGE
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