An automated pipeline to create an atlas of in situ hybridization gene expression data in the adult marmoset brain
This work addresses the need for efficient, unbiased analysis of genome-wide gene expression data in primate brains, which is incremental as it automates existing methods for a specific domain.
The researchers tackled the problem of creating an atlas of gene expression in the adult marmoset brain by developing an automated pipeline for segmentation and registration, resulting in the first such atlas in a standard stereotaxic space to enable large-scale analysis and comparative studies.
We present the first automated pipeline to create an atlas of in situ hybridization gene expression in the adult marmoset brain in the same stereotaxic space. The pipeline consists of segmentation of gene expression from microscopy images and registration of images to a standard space. Automation of this pipeline is necessary to analyze the large volume of data in the genome-wide whole-brain dataset, and to process images that have varying intensity profiles and expression patterns with minimal human bias. To reduce the number of labelled images required for training, we develop a semi-supervised segmentation model. We further develop an iterative algorithm to register images to a standard space, enabling comparative analysis between genes and concurrent visualization with other datasets, thereby facilitating a more holistic understanding of primate brain structure and function.