Construction of a 5-feature gene model by support vector machine for classifying osteoporosis samples.

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Three gene expression datasets of osteoporosis samples were acquired from the Gene Expression Omnibus database with pre-set criteria. Differentially expressed genes (DEGs) between normal and diseased osteoporosis samples were screened using Limma package in R language. Protein-protein interaction (PPI) network was established based on interaction data of the DEGs from the Human Protein Reference Database. Classification accuracy of the classifier was assessed with sensitivity, specificity and area under curve (AUC) using the pROC package in the R. Pathway enrichment analysis was performed on feature genes with clusterProfiler. A total of 310 differentially expressed genes between two samples were associated with positive regulation of protein secretion and cytokine secretion, neutrophil-mediated immunity, and neutrophil activation. PPI network of DEGs consisted of 12 genes. A SVM classifier based on five feature genes was developed to classify osteoporosis samples, showing a higher prediction accuracy and AUC for GSE35959, GSE62402, GSE13850, GSE56814, GSE56815 and GSE7429 datasets. A SVM classifier with a high accuracy was developed for predicting osteoporosis. The genes included may be the potential feature genes in osteoporosis development.AbbreviationsDEGs: Differentially expressed genes; PPI: protein-protein interaction; WHO: World Health Organization; SVM: Support vector machine; GEO: Gene Expression Omnibus; KEGG: Kyoto Encyclopedia of Genes and Genomes; GO: Gene Ontology; BP: Biological Process; CC: Cellular Component; MF: Molecular Function; SVM: Support vector machines.", "claims": [{"id": "claim-data-access", "statement": "The data that support the findings of this study are openly available in GSE35959 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE35959], GSE62402 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi], GSE13850 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi], GSE56814 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi], GSE56815 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi], and GSE7429 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi] datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34622712", "locator": "sections[16] \"Availability of data and materials\" paragraph 2", "quote": "The data that support the findings of this study are openly available in GSE35959 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE35959], GSE62402 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi], GSE13850 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi], GSE56814 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi], GSE56815 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi], and GSE7429 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi] datasets."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A SVM classifier based on 5 feature genes was developed to classify different osteoporosis samples, showing a higher prediction accuracy and AUC for GSE35959, GSE62402, GSE13850, GSE56814, GSE56815 and GSE7429 datasets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34622712", "locator": "sections[8] \"Results\" paragraph 2", "quote": "A SVM classifier based on 5 feature genes was developed to classify different osteoporosis samples, showing a higher prediction accuracy and AUC for GSE35959, GSE62402, GSE13850, GSE56814, GSE56815 and GSE7429 datasets."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A SVM classifier based on 5 feature genes was developed to classify different osteoporosis samples, showing a higher prediction accuracy and AUC for GSE35959, GSE62402, GSE13850, GSE56814, GSE56815 and GSE7429 datasets.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34622712"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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