a novel model for identifying driver genes via knowledge-driven matrix factorization with prior knowledge from interactome and pathways
Developer: Jianing Xi xjn@mail.ustc.edu.cn from Health Informatics Lab, School of Information Science and Technology, University of Science and Technology of China
- 4GB memory
- MATLAB R2015a or later
- Prior knowledge from pathways
The file
./PriorKnowledge/Pathway_map_bipartite.matcontains the bipartite matrix of the mapping from genes to pathways, and the lists including genes and pathways. The pathway used here is KEGG [1], Reactome [2] and BioCarta [3], which are downloaded from a previous study [4]. - Prior knowledge from interactome
The file
./PriorKnowledge/iRefIndex_adj_matrix.matcontains the adjanceny matrix of interaction network iRefIndex 9 [5] and the list of genes in the network.
We provide the input data files of TCGA somatic mutation data of three cancers from cBioPortal [6] respectively.
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| CANCER NAME | Abbreviation | FILE DIRECTORY |
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|Breast invasive carcinoma | BRCA |`./Input_data/BRCA.mat` |
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|Glioblastoma multiforme | GBM |`./Input_data/KIRC.mat` |
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|Thyroid carcinoma | THCA |`./Input_data/THCA.mat` |
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To apply DGPathinter on the example input datasets with the default configurations, please run the script file ./example.m and the result file will be automatically saved as .mat file in directory ./Output_data when the program is finished.
The descriptions of output variables of mCGfinder are provided below:
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| VARIABLE NAME | DESCRIPTION |
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|GeneSelected |The top 200 genes selected by DGPathinter as potential driver genes. |
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|U_sample_indicator |The sample indicator matrix indicates the assignment of tumor samples to|
| |each layer of the reconstructed matrix. The entry U_ij = 1 indicate that|
| |the i-th samples are assigned to the j-th layer, and 0 otherwise. |
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|V_gene_score |The gene score matrix for each layers of the reconstructed matrix and |
| |the investigated genes. Higher scores represent the larger possibility |
| |of the related genes to be potential driver genes. |
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The configurations of DGPathinter can be set as Struct variables Gene2Path and Net_Conf in ./example.m, with their descriptions provided below:
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| PARAMETER NAME | DESCRIPTION |
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|Gene2Path.lambda_C |The tuning parameter of prior knowledge from pathways. |
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|Gene2Path.lambda_V |The tuning parameter of regularization term of pathway score vectors. |
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|Net_Conf.lambda_L |The tuning parameter of prior knowledge from interactome. |
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|MC |Maximum layer number or maximum rank of the reconstructed matrix. |
| |The default value is 5. |
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|LLP |Least proportion of samples assigned to each layers. The default value |
| |is 15%. |
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[1] Ogata H, Goto S, Sato K, et al. KEGG: Kyoto encyclopedia of genes and genomes[J]. Nucleic acids research, 1999, 27(1): 29-34.
[2] Schmidt E, Birney E, Croft D, et al. Reactome¨Ca knowledgebase of biological pathways[C]//OTM Confederated International Conferences" On the Move to Meaningful Internet Systems". Springer, Berlin, Heidelberg, 2006: 710-719.
[3] Nishimura D. BioCarta[J]. Biotech Software & Internet Report: The Computer Software Journal for Scient, 2001, 2(3): 117-120.
[4] Park S, Kim S J, Yu D, et al. An integrative somatic mutation analysis to identify pathways linked with survival outcomes across 19 cancer types[J]. Bioinformatics, 2015, 32(11): 1643-1651.
[5] Razick S, Magklaras G, Donaldson I M. iRefIndex: a consolidated protein interaction database with provenance[J]. BMC bioinformatics, 2008, 9(1): 405.
[6] Gao J, Aksoy B A, Dogrusoz U, et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal[J]. Science signaling, 2013, 6(269): pl1.