Multi-association network calculation method, device and equipment for microorganisms and a storage medium
A technology of association network and calculation method, applied in the fields of biostatistics, biological systems, bioinformatics, etc., can solve the problems of ignoring the nature of dynamic changes in microbial interaction and misleading research on microbial interaction
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Embodiment 1
[0050] see figure 1 , figure 1 It is a schematic flowchart of a multi-association network calculation method for microorganisms disclosed in the embodiment of this application. Such as figure 1 , the multi-association network calculation method of the microorganisms comprises steps:
[0051] 101. Obtain sequencing sample data set and environmental factor set
[0052] 102. Initialize the root node node of the sequencing sample data set and the environmental factor set 0 , where |node 0 |=N;
[0053] According to the root node node of the sequencing sample data set and the environmental factor set 0 , the two-component Gaussian mixture model recursively divides the sequencing sample data set and the environmental factor set, and obtains at least two sub-nodes of the sequencing sample data set and the environmental factor set, among them, a node node k+1 ={X k+1 ,M k+1}, another child node node k+2 ={X k+2 ,M k+2}, and|node k+1 |=N k+1 ,|node k+2 |=N k+2 , nod...
Embodiment 2
[0077] see figure 2 , figure 2 It is a structural schematic diagram of a multi-association network computing device for microorganisms disclosed in the embodiment of this application. Such as figure 2 , the multi-association network computing device of the microorganism includes modules:
[0078] Obtaining module 201, configured to obtain a sequencing sample data set and environmental factor set
[0079] Initialization module 202, for initializing the root node node of the sequencing sample data set and the environmental factor set 0 , where |node 0 |=N
[0080] The division module 203 is used for the root node node of the sequencing sample data set and the environmental factor set 0 , the two-component Gaussian mixture model recursively divides the sequencing sample data set and the environmental factor set, and obtains at least two sub-nodes of the sequencing sample data set and the environmental factor set, among them, a node node k+1 ={X k+1 ,M k+1}, anothe...
Embodiment 3
[0102] The third aspect of the present application discloses a multi-association network computing device for microorganisms. The device includes:
[0103] processor 302; and
[0104] The memory 301 is configured to store machine-readable instructions, and when the instructions are executed by the processor 302, the multi-association network computing method for microorganisms as disclosed in Embodiment 1 of the present application is executed.
[0105] Compared with the existing technology, the device of the embodiment of the present application provides a new hierarchical Bayesian model by implementing the multi-association network calculation method of microorganisms, inferring multiple associations in consideration of changes in environmental factors network, which in turn is able to automatically infer the number of environmental conditions in the dataset and the microbe-microbe and microbe-environment factor associations for each environmental condition. At the same tim...
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