Method of identifying cancer drive pathway

A cancer and pathway technology, applied in instrumentation, genomics, proteomics, etc., can solve problems such as low efficiency

Active Publication Date: 2021-01-26
GUANGXI NORMAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] Therefore, a new omics integration method is needed to fuse each data, instead of calculating them separately when calculating the weight of the driving pathway, and designing a reasonable calculation model to calculate the weight of t

Method used

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  • Method of identifying cancer drive pathway
  • Method of identifying cancer drive pathway
  • Method of identifying cancer drive pathway

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0048]A method for identifying cancer-driven pathways includes the following steps:

[0049]1) Construct a weighted non-binary mutation matrix:

[0050]Existing glioblastoma GBM somatic mutation matrixCopy number variation matrixAnd gene expression matrixMedium mutation matrixCopy number variation matrixAnd gene expression matrixThe middle row represents the same sample set p of a cancer, and the columns represent the gene set GS, GCAnd GE, In the matrixMiddle, sij ∈{0,1}(i=1,2,...,|p|,j=1,2,...,|GS|), j gene mutation in i sample, sij The value is 1, otherwise the value is 0; matrixEach element in cij ∈{-2,-1,0,1,2}(i=1,2,...,|p|,j=1,2,...,|GC|), represents the copy number variation value of j gene in i sample; in the matrixMiddle eij ∈R(i=1, 2,..., |p|, j=1, 2,..., |GE|), represents the expression of j gene in i sample; let the matrixGene set GA=GS∪GC, The sample set is p, letaij ∈{0,1}(i=1,2,...,|p|,j=1,2,...,|GA|), whereIs the mutation matrix, when sij The value is 1 or when the j gene...

Embodiment 2

[0079]Set λ in step 1) of this example1= 3 and λ2=7, construct a weighted non-binary mutation matrix A|p|×|G| , Where |p|=90, |G|=920;

[0080]Step 7 of this example) Enter the weighted non-binary mutation matrix A|p|×|G| , Where |p|=90, |G|=920, the model in formula (2), the drive path size k=10, CGA-MWS related parameters, population size P=460, mutation probability Pm=0.3, the maximum evolutionary algebra maxstep=1000, the optimal value is kept constant threshold maxt=10;

[0081]In this example, step 9) get the drive path with size k=10, the operation diagram is as followsfigure 2 Shown.

[0082]The remaining steps are the same as in Example 1.

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Abstract

The invention discloses a method for identifying a cancer driving path. The method comprises the following steps of 1) constructing a weighted non-binary mutation matrix; (2) setting an identificationmodel, (3) setting a fitness function, (4) setting a crossover operator, (5) setting a mutation operator, (6) setting a cooperation strategy, (7) setting parameters, (8) constructing the initial population, and (9) executing iterative operation.

Description

Technical field[0001]The present invention relates to the field of cancer driving pathway identification, in particular to a method for identifying cancer driving pathways.Background technique[0002]With the rapid development of deep sequencing technology, in recent years, large-scale cancer projects such as The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) have provided a large number of cancers. Multiple omics data. In the past several studies, designing effective calculation methods to identify "driving mutations" in the process of cancer has become a hot spot. However, most methods cannot determine the heterogeneity of gene mutations, that is, different samples from the same cancer may have different mutant genes. Researchers have found that there is a high probability that different mutated genes target the same biological pathway, and that the development of cancer is essentially controlled by biological pathways. Therefore, it is necessary to...

Claims

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Application Information

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IPC IPC(8): G16B20/10G16B20/50
CPCG16B20/10G16B20/50
Inventor 朱凯吴璟莉李高仕
Owner GUANGXI NORMAL UNIV
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