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GUI-based, extensible, scalable framework for neural image data analysis --- OptiNiSt
Yukako Yamane, Yuzhe Li, Shogo Akiyama, Shuya Saeki, Masaru Kuwabara, Shigeki Hasui, Ryota Kanai, Carlos Enrique Gutierrez, Kenji Doya
Presenting author:
Yukako Yamane
As calcium imaging is becoming a standard tool in neuroscience, vast volumes of imaging data are being collected. The number of data processing software tools is also increasing. However, researchers who wish to apply new methods to their dataset need to prepare the environment for each new analysis tool and reshape their data to fit each tool. Thus, analysis pipelines can be complex and challenging to maintain their reproducibility.

Here we developed Optical Neuroimage Studio (OptiNiSt) that helps researchers quickly try multiple data analysis methods, interactively visualize the results, and construct data analysis pipelines for reproducible analysis and efficient processing on HPC clusters. OptiNiSt is composed of a Web browser-based frontend and python-based backend. The workflow and their environment are managed by snakemake (Mölder et al., F1000Research 2021). Users can add their own analysis tools as Python modules. The results are saved in .nwb (Neurodata Without Borders) standard format.

The source code is made available from GitHub (https://github.com/oist/optinist). Users can install OptiNiSt to Linux, Mac, and Windows machines by Python “pip install” command or by downloading a virtual machine from DockerHub. OptiNiSt aims to make advanced analysis methods accessible to a wide range of researchers and to promote standardization of analysis protocols, as tools like SPM and MRtrix have served in the MRI community.