Mars, a molecule archive suite for reproducible analysis and reporting of single-molecule properties from bioimages

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    Evaluation Summary:

    This manuscript reports an open-source platform for the storage and processing of single-molecule, camera-based, imaging data. This platform would facilitate data sharing and reproducibility and would be of great interest to practitioners of single-molecule imaging experiments, both experienced and new to the field. Although the platform requires a bit more testing, troubleshooting, and documenting, it represents significant and important steps towards unifying and standardizing how the field stores and processes data and towards expanding the base of researchers who can easily employ single-molecule imaging methods.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their name with the authors.)

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Abstract

The rapid development of new imaging approaches is generating larger and more complex datasets, revealing the time evolution of individual cells and biomolecules. Single-molecule techniques, in particular, provide access to rare intermediates in complex, multistage molecular pathways. However, few standards exist for processing these information-rich datasets, posing challenges for wider dissemination. Here, we present Mars, an open-source platform for storing and processing image-derived properties of biomolecules. Mars provides Fiji/ImageJ2 commands written in Java for common single-molecule analysis tasks using a Molecule Archive architecture that is easily adapted to complex, multistep analysis workflows. Three diverse workflows involving molecule tracking, multichannel fluorescence imaging, and force spectroscopy, demonstrate the range of analysis applications. A comprehensive graphical user interface written in JavaFX enhances biomolecule feature exploration by providing charting, tagging, region highlighting, scriptable dashboards, and interactive image views. The interoperability of ImageJ2 ensures Molecule Archives can easily be opened in multiple environments, including those written in Python using PyImageJ, for interactive scripting and visualization. Mars provides a flexible solution for reproducible analysis of image-derived properties, facilitating the discovery and quantitative classification of new biological phenomena with an open data format accessible to everyone.

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  1. Author Response

    Reviewer 2

    The manuscript by Huisjes et al presented an open-source platform for the storage and processing of imaging data, particularly for single-molecule imaging experiments. Compared to sequencing data, which have a more standardized format for data storage, imaging data have more diverse formats due to the fact that different research labs tend to use different instruments and software (either commercial or home-built) for data collection and analysis. Manual input is almost always necessary at certain steps of data analysis. All these create difficulties in data storage and reproducibility. The authors provide a practical solution to this problem by the molecular archive suite, "Mars". This platform is integrated into imageJ/Fiji, and can be used for storing detailed description of experimental settings, performing standard imaging processing steps, and recording manual input information during data analysis. I judge this platform, if fully functional and generalizable, will be very useful to many labs who are using single-molecule imaging methods in the research.

    Strength:

    1. The work presented a fairly user friendly interface (using Fiji directly), and fairly detailed protocol and other documentations in a very nicely designed website. I was able to download and use it based on the tutorial.
    1. It is integrated very well with Fiji, and some analysis modules are directly from existing Fiji analysis/plugins.

    Weakness:

    I invited one of my students to co-test the suite. We tried on both Mac and Windows systems, using the example FRET data set described in the manuscript and one of our own single-molecule images. We encountered some technical issues.

    We are very happy with the overall positive assessment of the reviewer that Mars could offer a common format that helps to enforce reproducible analysis workflows that can easily be shared with others.

    We are grateful for the additional feedback and testing done by the reviewer and her student. Ensuring that Mars works as expected on all computers and configurations is difficult given that we don’t have them at hand for testing ourselves. During the revision period, we have done more testing on more computer systems and we hope we have addressed the issues. We believe it will be impossible for us to guarantee that Mars works without problems on the first try for everyone. Therefore, Mars is a community partner on the Scientific Community Image Forum where users can report their problems in posts with the mars tag and we can help troubleshoot them (https://forum.image.sc/tag/mars). We believe this approach will offer the best support going forward. Nevertheless, we continue to make improvements and test to make sure all bugs we discover are addressed.

    In the revision, we completely reworked the smFRET example workflow and added two additional workflows to address all the comments from the reviewers and reviewing editor. In addition to expanding the explanations, and troubleshooting information on the Mars documentation website, we also created a YouTube channel with tutorial and example videos (https://www.youtube.com/channel/UCkkYodMAeotj0aYxjw87pBQ). We go through the new dynamic smFRET workflow from start to finish in one of the videos provided (https://www.youtube.com/watch?v=JsyznI8APlQ). We hope this will make it clear what inputs and outputs are expected and how the workflow should proceed. This was done on a mac but we have also tested this workflow on windows without encountering problems.

  2. Evaluation Summary:

    This manuscript reports an open-source platform for the storage and processing of single-molecule, camera-based, imaging data. This platform would facilitate data sharing and reproducibility and would be of great interest to practitioners of single-molecule imaging experiments, both experienced and new to the field. Although the platform requires a bit more testing, troubleshooting, and documenting, it represents significant and important steps towards unifying and standardizing how the field stores and processes data and towards expanding the base of researchers who can easily employ single-molecule imaging methods.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their name with the authors.)

  3. Reviewer #1 (Public Review):

    With the ever increasing interest in single-molecule imaging techniques, accompanied by ever increasing experimental schemes and analytical frameworks it becomes difficult to report such experimental results in a manner that is universal, one which can adapt to any type of experiment and analysis, one which assists in reproducibility, and one which will keep the data as compact as possible, yet its usage as efficient as possible. This work ("Mars, a molecule archive suite for reproducible analysis and reporting of single molecule properties from bioimages", by Huisjes, Retzer et al. ) introduces a novel platform for the reproducible archiving of camera-based single-molecule imaging experiments. This work will appeal to practitioners of single-molecule imaging experiments, both experienced and newbies. The readers of this work would benefit from understanding how to employ a rational data archiving process using Mars, following three examples the authors provide, which exhibit the generality of the platform and its ease of use. Readers who might want to employ Mars for their own single-molecule imaging measurements can also experience an intuitive guide on Mars GitHub or in Jupyter Notebooks the authors provide.

    I judge that it would even be better if several items that will assist audiences who are not experts in single-molecule imaging (such as a guidance chapter in the manuscript itself, in addition and before sending the readers to the guide online) could be provided in the text. Additionally, adding a layer of data validation can enhance the archiving procedure even more. Aside from this and a few other FRET-related comments and suggestions, I conclude that this work can be quite useful and presents a major step forward towards open science in single-molecule imaging.

  4. Reviewer #2 (Public Review):

    The manuscript by Huisjes et al presented an open-source platform for the storage and processing of imaging data, particularly for single-molecule imaging experiments. Compared to sequencing data, which have a more standardized format for data storage, imaging data have more diverse formats due to the fact that different research labs tend to use different instruments and software (either commercial or home-built) for data collection and analysis. Manual input is almost always necessary at certain steps of data analysis. All these create difficulties in data storage and reproducibility. The authors provide a practical solution to this problem by the molecular archive suite, "Mars". This platform is integrated into imageJ/Fiji, and can be used for storing detailed description of experimental settings, performing standard imaging processing steps, and recording manual input information during data analysis. I judge this platform, if fully functional and generalizable, will be very useful to many labs who are using single-molecule imaging methods in the research.

    Strength:

    1. The work presented a fairly user friendly interface (using Fiji directly), and fairly detailed protocol and other documentations in a very nicely designed website. I was able to download and use it based on the tutorial.
    2. It is integrated very well with Fiji, and some analysis modules are directly from existing Fiji analysis/plugins.

    Weakness:

    I invited one of my students to co-test the suite. We tried on both Mac and Windows systems, using the example FRET data set described in the manuscript and one of our own single-molecule images. We encountered some technical issues.