Zhong, Q. et al. Image-based computational quantification and visualization of genetic
alterations and tumour heterogeneity. Scientific Reports. 6, 24146; doi: 10.1038/srep24146 (2016).

Zhong, Q. et al. A curated collection of tissue microarray images and clinical outcome data of prostate cancer patients. Scientific Data. (in press).


We introduce an integrative method that combines a dual-color chromogenic and silver in situ hybridization assay (DISH) and an image-based computational workflow (ISHProfiler). It automatically evaluates copy number variation (CNV) and quantifies tumor heterogeneity at multiple levels with visualisation tools for various genes in different human tumours.


The demo (Download, password: srep2016) shows the computational workflow, which is applied to a set of 71 tissue cores of prostate cancer, hybridised with PTEN and CEP10. The demo is written in MATLAB and uses the LIBSVM library (Version 3.18). The workflow has been integrated into the open source software TMARKER as a JAVA plug-in.


Tissue images are available in the following links. (High resolution images available upon request)