Method for mining methylation pattern by whole genome data

A genome-wide, data mining technology, applied in the field of bioinformatics data processing, can solve the problems of different omics data dimensions, unclear methylation data distribution, high data distribution requirements, etc., to reduce FDR and improve aggregation. Class Efficiency Effects

Inactive Publication Date: 2017-10-27
XIDIAN UNIV
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[0003] To sum up, the problem existing in the prior art is that traditional statistical methods have high requirements on the distribution of data, that is, the distribution of data is required to be definite, but the d

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  • Method for mining methylation pattern by whole genome data
  • Method for mining methylation pattern by whole genome data
  • Method for mining methylation pattern by whole genome data

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[0036] In order to make the object, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0037] The application principle of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0038] Such as figure 1 As shown, the method for mining methylation patterns using genome-wide data provided by the embodiments of the present invention includes the following steps:

[0039] S101: Use the gene chip significance analysis SAM method on various data sample sets to screen out the differential methylation sites on the whole genome respectively; take the intersection of the methylation differential sites of multiple sample sets to obtain the common difference set of sites...

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Abstract

The invention belongs to the technical field of data processing of bioinformatics, and discloses a method for mining the methylation pattern by whole genome data. The method comprises the following steps that: using a SAM (Significance Analysis of Microarrays) method in various data sample sets to independently screen differential methylation sites on a whole genome; taking an intersection from the differential methylation sites of a plurality of sample sets to obtain a common difference site set; calculating a Pearson correlation coefficient between the methylation levels of the differential methylation sites and a corresponding gene expression level, and identifying a methylation regulation and control site; and carrying out AP (Affinity Propagation) clustering on the differential methylation site set to obtain a methylation cluster, independently carrying out pattern analysis on each methylation cluster, and carrying out demonstration through gene annotation and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis. By use of the method, references can be provided by aiming at a demethylation medicine, different types of diseases have generality on a methylation pattern, and the method has a practical and clinic meaning for researching a relationship between the methylation pattern and the disease from a perspective of the whole genome.

Description

technical field [0001] The invention belongs to the technical field of data processing of bioinformatics, and in particular relates to a method for mining methylation patterns by using whole genome data. Background technique [0002] With the continuous development and progress of high-throughput sequencing technology and gene chip technology, efficient and massive genetic data can be obtained. Gene data contains many intricate life phenomena, making it possible to comprehensively explore the genetic and epigenetic basis of diseases. Modern life science research provides new directions and ideas. However, massive data cannot intuitively reveal life phenomena or reflect biological laws. Complex statistical methods and other means and techniques must be used to analyze and explore the biological phenomena contained in massive data. Thus, the discipline of bioinformatics was derived. Bioinformatics is an emerging discipline combining life science and computer science. It stud...

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Application Information

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IPC IPC(8): G06F19/24G06F19/20
CPCG16B25/00G16B40/00
Inventor 杨利英杨胜楠
Owner XIDIAN UNIV
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