{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["12"],"submitter":["Martini P"],"pubmed_abstract":["<h4>Background</h4>In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focused on the identification of significant differentially expressed genes. Later, researchers moved toward the systematic integration of gene expression profiles with additional biological information, such as chromosomal location, ontological annotations or sequence features. The analysis of gene expression linked to physical location of genes on chromosomes allows the identification of transcriptionally imbalanced regions, while, Gene Set Analysis focuses on the detection of coordinated changes in transcriptional levels among sets of biologically related genes. In this field, meta-analysis offers the possibil"],"journal":["BMC bioinformatics"],"pagination":["92"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC3094239"],"repository":["biostudies-literature"],"pubmed_title":["Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies."],"pmcid":["PMC3094239"],"pubmed_authors":["Cagnin S","Martini P","Risso D","Romualdi C","Lanfranchi G","Sales G"],"additional_accession":[]},"is_claimable":false,"name":"Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies.","description":"<h4>Background</h4>In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focused on the identification of significant differentially expressed genes. Later, researchers moved toward the systematic integration of gene expression profiles with additional biological information, such as chromosomal location, ontological annotations or sequence features. The analysis of gene expression linked to physical location of genes on chromosomes allows the identification of transcriptionally imbalanced regions, while, Gene Set Analysis focuses on the detection of coordinated changes in transcriptional levels among sets of biologically related genes. In this field, meta-analysis offers the possibil","dates":{"release":"2011-01-01T00:00:00Z","publication":"2011 Apr","modification":"2026-04-07T18:38:50.142Z","creation":"2026-04-07T16:41:01.39Z"},"accession":"S-EPMC3094239","cross_references":{"pubmed":["21481242"],"doi":["10.1186/1471-2105-12-92"]}}