{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Krupa O"],"funding":["National Institute of Neurological Disorders and Stroke","National Institute of Environmental Health Sciences","NICHD NIH HHS","NIA NIH HHS","NIEHS NIH HHS","NIMH NIH HHS","National Institutes of Health","National Institute on Aging","U.S. Department of Defense","NINDS NIH HHS","NCI NIH HHS","University of North Carolina Wilmington","National Institute of Mental Health","North Carolina Biotechnology Center","University of Arizona Cancer Center","Hope Foundation","National Science Foundation","Children's Tumor Foundation"],"pagination":["109802"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8530274"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["37(2)"],"pubmed_abstract":["Tissue-clearing methods allow every cell in the mouse brain to be imaged without physical sectioning. However, the computational tools currently available for cell quantification in cleared tissue images have been limited to counting sparse cell populations in stereotypical mice. Here, we introduce NuMorph, a group of analysis tools to quantify all nuclei and nuclear markers within the mouse cortex after clearing and imaging by light-sheet microscopy. We apply NuMorph to investigate two distinct mouse models: a Topoisomerase 1 (Top1) model with severe neurodegenerative deficits and a Neurofibromin 1 (Nf1) model with a more subtle brain overgrowth phenotype. In each case, we identify differential effects of gene deletion on individual cell-type counts and distribution across cortical regions that manifest as alterations of gross brain morphology. These results underline the value of whole-brain imaging approaches, and the tools are widely applicable for studying brain structure phenotypes at cellular resolution."],"journal":["Cell reports"],"pubmed_title":["NuMorph: Tools for cortical cellular phenotyping in tissue-cleared whole-brain images."],"pmcid":["PMC8530274"],"funding_grant_id":["R56AG058663","R01 MH118349","R35 ES028366","2016-IDG-1016","P30 ES010126","P50 HD103573","R01MH118349","R01NS110791","R56 AG058663","P30 CA016086","CTF-YIA 2015-01-013","R35ES028366","R01 MH120125","R01 MH121433","ACI-16449916","R01MH120125","P30 NS045892","R01 NS110791","R01MH121433","W81XWH-19-1-0402"],"pubmed_authors":["Hadden-Ford E","Mory JT","Rees BW","Liu T","Wu G","Snider WD","Zylka MJ","Krupa O","Stein JL","Fragola G","Xing L","Krishnamurthy A","Humphrey Z"],"additional_accession":[]},"is_claimable":false,"name":"NuMorph: Tools for cortical cellular phenotyping in tissue-cleared whole-brain images.","description":"Tissue-clearing methods allow every cell in the mouse brain to be imaged without physical sectioning. However, the computational tools currently available for cell quantification in cleared tissue images have been limited to counting sparse cell populations in stereotypical mice. Here, we introduce NuMorph, a group of analysis tools to quantify all nuclei and nuclear markers within the mouse cortex after clearing and imaging by light-sheet microscopy. We apply NuMorph to investigate two distinct mouse models: a Topoisomerase 1 (Top1) model with severe neurodegenerative deficits and a Neurofibromin 1 (Nf1) model with a more subtle brain overgrowth phenotype. In each case, we identify differential effects of gene deletion on individual cell-type counts and distribution across cortical regions that manifest as alterations of gross brain morphology. These results underline the value of whole-brain imaging approaches, and the tools are widely applicable for studying brain structure phenotypes at cellular resolution.","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Oct","modification":"2026-05-08T10:39:10.119Z","creation":"2025-05-18T12:08:47.534Z"},"accession":"S-EPMC8530274","cross_references":{"pubmed":["34644582"],"doi":["10.1016/j.celrep.2021.109802"]}}