Tissue clearing renders entire organs transparent to enable combination with light sheet fluorescence microscopy to accelerate whole tissue imaging. Yet, challenges remain in analyzing the large resulting 3D datasets that consist of terabytes of images and information on millions of labeled cells. Previous work has established pipelines for automated analysis of tissue cleared mouse brains, but focus there was on single color channels and/or detection of nuclear localized signals in low-resolution images. Here, we present an automated workflow (COMBINe, Cell detectiOn in Mouse BraIN) to map sparsely labeled neurons and astrocytes in genetically distinct mouse forebrains using Mosaic Analysis with Double Markers (MADM). COMBINe blends modules from multiple pipelines with RetinaNet at its core. We quantitatively analyzed the regional and subregional effects of MADM-based deletion of the Epidermal Growth Factor Receptor (EGFR) on neuronal and astrocyte populations in the mouse forebrain. 

Left brain hemisphere of a male P30 Emx1^cre:MADM11^TG/GT:Egfr^+/+ (wildtype) mouse was collected, cleared and stained using iDISCO+ protocol. The cleared mouse brain hemisphere was imaged using a custom-built light sheet fluorescence microscope by illumination of 561 nm (RFP-Cy3) and 640 nm (GFP-AF647) respectively, with a voxel size of 0.65 × 0.65 × 10 μm³. 

This is an example dataset for running the COMBINe workflow. The dataset contains tiff images which can be opened with image tools (e.g. ImageJ) that support tiff format.