RT Journal Article
SR Electronic
T1 A framework for multiplex imaging optimization and reproducible analysis
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.11.29.470281
DO 10.1101/2021.11.29.470281
A1 Eng, Jennifer
A1 Bucher, Elmar
A1 Hu, Zhi
A1 Zheng, Ting
A1 Gibbs, Summer L.
A1 Chin, Koei
A1 Gray, Joe W.
YR 2021
UL http://biorxiv.org/content/early/2021/11/30/2021.11.29.470281.abstract
AB Multiplex imaging technologies are increasingly used for single-cell phenotyping and spatial characterization of tissues; however, transparent methods are needed for comparing the performance of platforms, protocols and analytical pipelines. We developed a python software, jinxif, for reproducible image processing and utilize Jupyter notebooks to share our optimization of signal removal, antibody specificity, background correction and batch normalization of the multiplex imaging with a focus on cyclic immunofluorescence (CyCIF). Our work both improves the CyCIF methodology and provides a framework for multiplexed image analytics that can be easily shared and reproduced.Competing Interest StatementThe authors have declared no competing interest.