Extraction and comparison of gene expression patterns from 2D RNA in situ hybridization images.

Bioinformatics
Daniel L MaceUwe Ohler

Abstract

Recent advancements in high-throughput imaging have created new large datasets with tens of thousands of gene expression images. Methods for capturing these spatial and/or temporal expression patterns include in situ hybridization or fluorescent reporter constructs or tags, and results are still frequently assessed by subjective qualitative comparisons. In order to deal with available large datasets, fully automated analysis methods must be developed to properly normalize and model spatial expression patterns. We have developed image segmentation and registration methods to identify and extract spatial gene expression patterns from RNA in situ hybridization experiments of Drosophila embryos. These methods allow us to normalize and extract expression information for 78,621 images from 3724 genes across six time stages. The similarity between gene expression patterns is computed using four scoring metrics: mean squared error, Haar wavelet distance, mutual information and spatial mutual information (SMI). We additionally propose a strategy to calculate the significance of the similarity between two expression images, by generating surrogate datasets with similar spatial expression patterns using a Monte Carlo swap sampler. On data...Continue Reading

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Citations

Mar 2, 2011·Bioinformatics·Liangxiu HanRichard A Baldock
Aug 5, 2011·PLoS Computational Biology·Iulian Pruteanu-MaliniciUwe Ohler
Jan 4, 2013·PLoS Computational Biology·Lior KirschGal Chechik
Oct 17, 2013·PLoS Computational Biology·Kriti Puniyani, Eric P Xing
Feb 23, 2011·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Qi Li, Chandra Kambhamettu
Apr 14, 2016·Proceedings of the National Academy of Sciences of the United States of America·Siqi WuErwin Frise
Apr 16, 2014·Methods : a Companion to Methods in Enzymology·Florian JugPavel Tomancak
Jan 4, 2018·BMC Systems Biology·Qi Li, Yongyi Gong
Jun 4, 2020·Integrative and Comparative Biology·Erica L WestermanChristopher P J Sanford

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