Trinh, AnneRye, Inga HAlmendro, VanessaHelland, ÅslaugRussnes, Hege GMarkowetz, Florian2014-11-032014Trinh, Anne, Inga H Rye, Vanessa Almendro, Åslaug Helland, Hege G Russnes, and Florian Markowetz. 2014. “GoIFISH: a system for the quantification of single cell heterogeneity from IFISH images.” Genome Biology 15 (8): 442. doi:10.1186/s13059-014-0442-y. http://dx.doi.org/10.1186/s13059-014-0442-y.1465-6906http://nrs.harvard.edu/urn-3:HUL.InstRepos:13347625Molecular analysis has revealed extensive intra-tumor heterogeneity in human cancer samples, but cannot identify cell-to-cell variations within the tissue microenvironment. In contrast, in situ analysis can identify genetic aberrations in phenotypically defined cell subpopulations while preserving tissue-context specificity. GoIFISH is a widely applicable, user-friendly system tailored for the objective and semi-automated visualization, detection and quantification of genomic alterations and protein expression obtained from fluorescence in situ analysis. In a sample set of HER2-positive breast cancers GoIFISH is highly robust in visual analysis and its accuracy compares favorably to other leading image analysis methods. GoIFISH is freely available at www.sourceforge.net/projects/goifish/. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0442-y) contains supplementary material, which is available to authorized users.en-USJournal Article2014-11-0310.1186/s13059-014-0442-y