NanoJ: a high-performance open-source super-resolution microscopy toolbox

Laine, R.; Tosheva, K.; Gustafsson, N.; Gray, R. D. M.; Almada, P.; Albrecht, D.; Risa, G. T.; Hurtig, F.; Lindas, A.-C.; Baum, B.; Mercer, J.; Leterrier, C.; Pereira, P. M.; Culley, S.; Henriques, R.

doi:10.1101/432674

bioRxiv · 10.1101/432674

NanoJ: a high-performance open-source super-resolution microscopy toolbox

Laine, R.·Tosheva, K.·Gustafsson, N.·Gray, R. D. M.·Almada, P.·Albrecht, D.·Risa, G. T.·Hurtig, F.·Lindas, A.-C.·Baum, B.·Mercer, J.·Leterrier, C.·Pereira, P. M.·Culley, S.·Henriques, R.

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Abstract

Super-resolution microscopy has become essential for the study of nanoscale biological processes. This type of imaging often requires the use of specialised image analysis tools to process a large volume of recorded data and extract quantitative information. In recent years, our team has built an open-source image analysis framework for super-resolution microscopy designed to combine high performance and ease of use. We named it NanoJ - a reference to the popular ImageJ software it was de-veloped for. In this paper, we highlight the current capabilities of NanoJ for several essential processing steps: spatio-temporal alignment of raw data (NanoJ-Core), super-resolution image re-construction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics). We expect to expand NanoJ in the future through the development of new tools designed to improve quantitative data analysis and measure the reliability of fluorescent microscopy studies.

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Laine, R., Tosheva, K., Gustafsson, N., Gray, R. D. M., Almada, P., Albrecht, D., Risa, G. T., Hurtig, F., Lindas, A.-C., Baum, B., Mercer, J., Leterrier, C., Pereira, P. M., Culley, S., Henriques, R.. 2018-10-01. NanoJ: a high-performance open-source super-resolution microscopy toolbox. https://doi.org/10.1101/432674

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