Abstract
Molecular 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. GoIFISHGoIFISH 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 GoIFISHGoIFISH is highly robust in visual analysis and its accuracy compares favorably to other leading image analysis methods. GoIFISHGoIFISH is freely available at www.sourceforge.net/projects/goifish/.
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CITATION STYLE
Trinh, A., Rye, I. H., Almendro, V., Helland, A., Russnes, H. G., & Markowetz, F. (2014). GoIFISH: a system for the quantification of single cell heterogeneity from IFISH images. Genome Biology, 15(8), 442. https://doi.org/10.1186/s13059-014-0442-y
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