PNNL

Abstract

Thinly sliced serial tissue sections of an organ can be imaged using optical microscopy at a resolution detailing individual cells. When the tissue sections are first subjected to in situ hybridization or immunohistochemistry, these datasets can be analyzed for changes in gene expression and gene products. Such spatial information is important for understanding the functional effects of experimental or environmental challenges to the organism. However, a critical step in analyzing these datasets is mitigating artifacts that result from the preparation of the tissue sections. In this paper, we describe an automated method with manual validation tools that together enable detecting and addressing artifacts including dust particles and air bubbles.