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Andy's Algorithms: new automated digital image analysis pipelines for FIJI

Abstract

Quantification of cellular antigens and their interactions via antibody-based detection methods are widely used in scientific research. Accurate high-throughput quantitation of these assays using general image analysis software can be time consuming and challenging, particularly when attempted by users with limited image processing and analysis knowledge. To overcome this, we have designed Andy's Algorithms, a series of automated image analysis pipelines for FIJI, that permits rapid, accurate and reproducible batch-processing of 3,3'-diaminobenzidine (DAB) immunohistochemistry, proximity ligation assays (PLAs) and other common assays. Andy's Algorithms incorporates a step-by-step tutorial and optimization pipeline to make batch image analysis simple for the untrained user and adaptable across laboratories. Andy's algorithms provide a simpler, faster, standardized work flow compared to existing programs, while offering equivalent performance and additional features, in a free to use open-source application of FIJI. Andy's Algorithms are available at GitHub, publicly accessed at https://github.com/andlaw1841/Andy-s-Algorithm .

Type Journal
ISBN 2045-2322 (Electronic) 2045-2322 (Linking)
Authors Law, A. M. K.; Yin, J. X. M.; Castillo, L.; Young, A. I. J.; Piggin, C.; Rogers, S.; Caldon, C. E.; Burgess, A.; Millar, E. K. A.; O'Toole, S. A.; Gallego-Ortega, D.; Ormandy, C. J.; Oakes, S. R.
Responsible Garvan Author Dr Samantha Oakes
Publisher Name Scientific Reports
Published Date 2017-11-16
Published Volume 7
Published Issue 1
Published Pages 15717
Status Published in-print
DOI 10.1038/s41598-017-15885-6
URL link to publisher's version https://www.ncbi.nlm.nih.gov/pubmed/29146920