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  "Title": "Signature Overrepresentation Analysis",
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  "Date": "2026-03-21",
  "Authors@R": "c(\nperson(\"Amir\", \"Foroushani\",\nemail = c(\"sigora.dev@gmail.com\"),\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0003-2748-3009\")),\nperson(\"Fiona\", \"Brinkman\",\nemail = c(\"sigora.dev@gmail.com\"),\nrole = c(\"aut\")),\nperson(\"David\", \"Lynn\",\nemail = c(\"sigora.dev@gmail.com\"),\nrole = c(\"aut\")),\nperson(\"Witold\", \"Wolski\",\nemail = c(\"witold.wolski@fgcz.uzh.ch\"),\nrole = c(\"cre\"),\ncomment = c(ORCID = \"0000-0002-6468-120X\"))\n)",
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  "Description": "Pathway Analysis is statistically linking observations on\nthe molecular level to biological processes or pathways on the\nsystems(i.e., organism, organ, tissue, cell) level.\nTraditionally, pathway analysis methods regard pathways as\ncollections of single genes and treat all genes in a pathway as\nequally informative. However, this can lead to identifying\nspurious pathways as statistically significant since components\nare often shared amongst pathways. SIGORA seeks to avoid this\npitfall by focusing on genes or gene pairs that are (as a\ncombination) specific to a single pathway. In relying on such\npathway gene-pair signatures (Pathway-GPS), SIGORA inherently\nuses the status of other genes in the experimental context to\nidentify the most relevant pathways. The current version allows\nfor pathway analysis of human and mouse datasets. In addition,\nit contains pre-computed Pathway-GPS data for pathways in the\nKEGG and Reactome pathway repositories and mechanisms for\nextracting GPS for user-supplied repositories.",
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