{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["26(1)"],"submitter":["Towle-Miller L"],"pubmed_abstract":["<h4>Background</h4>Biological pathways are sets of genes that jointly drive biological processes. Rather than analyzing genes individually, it is common practice to summarize sets of related genes using gene set variation analysis (GSVA). In short, GSVA summarizes a set of genes into a single score bounded between -1 and 1, where negative values suggest downregulation and positive values suggest upregulation. Although this interpretation is simple in theory, it depends on unbiased estimation of individual gene distributions. In the current version of GSVA, gene distributions are estimated using the input dataset (i.e., the scores are calculated based on the gene distributions from the same dataset). This becomes a major issue when study data does not adequately represent the full distribut"],"journal":["BMC genomics"],"pagination":["596"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12211894"],"repository":["biostudies-literature"],"pubmed_title":["Extending gene set variation analysis with a reference dataset to stabilize scores."],"pmcid":["PMC12211894"],"pubmed_authors":["Towle-Miller L","Miecznikowski J","Virmani A","Freudenburg J","Jordan W","Lockhart A","Powley W","Bergquist M"],"additional_accession":[]},"is_claimable":false,"name":"Extending gene set variation analysis with a reference dataset to stabilize scores.","description":"<h4>Background</h4>Biological pathways are sets of genes that jointly drive biological processes. Rather than analyzing genes individually, it is common practice to summarize sets of related genes using gene set variation analysis (GSVA). In short, GSVA summarizes a set of genes into a single score bounded between -1 and 1, where negative values suggest downregulation and positive values suggest upregulation. Although this interpretation is simple in theory, it depends on unbiased estimation of individual gene distributions. In the current version of GSVA, gene distributions are estimated using the input dataset (i.e., the scores are calculated based on the gene distributions from the same dataset). This becomes a major issue when study data does not adequately represent the full distribut","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Jul","modification":"2026-06-03T06:39:40.181Z","creation":"2026-04-25T03:22:02.624Z"},"accession":"S-EPMC12211894","cross_references":{"pubmed":["40597576"],"doi":["10.1186/s12864-025-11769-6"]}}