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PONE-D-22-14030The Image Data Explorer: interactive exploration of image-derived dataPLOS ONE

Dear Dr. Heriche,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Both reviewers found the idea and work to have value for the analysis of imaging data.   Both reviewers had some constructive comments that I believe would help improve.  Reviewer #1 had four specific comments and questions that I believe are specific and helpful.  Please respond to each in your response.  Also, please improve the WIKI as suggested and answer the questions in comment #4 and  in #1.  This would be necessary for acceptance of the manuscript for publication in PLoS One.        

Reviewer #2  also had several useful suggestions.  This reviewer listed two drawbacks.  Even if you decide not to directly address them in the manuscript (something I suggest, but will not require), please address/answer them in your response. This reviewer also sought a way to make the use of the software easier by suggesting a video. Please be thoughtful in how you can make the use of this tool easier, which has direct befits for the paper and the tool's adoption by the imaging community.    

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Gregg Roman, PhD

Academic Editor

PLOS ONE

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: N/A

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: This Manuscript introduced a tool for interactive image data visualization. The image data explorer (IDE) can be used as a web application or installed on local computers. IDE integrates interactive linked visualization of images and derived data points with exploratory data analysis methods, annotation, classification and feature selection functionalities. The manual of the Software needs to be optimized for new users.

1. How to input the images to your data base if users do not have a S3-compatible object store? What is the address of the ‘one common root directory accessible by the server component of the IDE’?

2. The IDE wiki need to be updated and optimized. I tried RStudio installation based on the wiki, but still could not get the code running. I would suggest to provide corresponding compatible RStudio download links and step-by-step installation and screenshots.

3. With all these plotting, machine learning and interactive functions, it is better to provide some statistical tools for better data analysis and exploring. For example, incorporating the ANOVAs and Post-hoc test would be very helpful.

4. In the Results session, In this case, how do you conclude ‘the resulting classifier has an accuracy of 74% which is above the no information rate and the most significant feature corresponds to nucleolus size’? How do you define the no information rate? In figure 3, what is the range (x-axis) of feature importance? The most important feature is the Nucleoli size and is less than 0.2, what does this mean?

Reviewer #2: This paper presents a tool (more precisely a web application also available as a Desktop application) that permits dynamic visualization of images and their (numerous) features and offers a set of statistical tools to apply to these features. This goes from exploratory data analysis to classification and seems very flexible, so that you could integrate your own algorithms.

Acquisition of big data in microscopy becomes more and more frequent (e.g. high content screening or mosaic acquisitions). The community definitely needs tools to be able to visualize and classify features obtained by any analysis workflow on this amount of data. This is offered by this software, with very simple inputs: the images and the associated features stored in a table (CSV type e.g.), generated by any workflow beforehand.

With no doubt, a specific attention has been paid to the interface: it seems very user-friendly and the dynamic interaction between the results table and the corresponding structures in the image is really effective; it can help detect anomalies in the workflow (e.g. bad segmentations) and then create more accurate results.

However, two drawbacks:

- the limitation to 3-dimensions for analyzed data (today data acquired on the microscope are often 5D); I do not understand this limitation since color-z-time information could be included in the table and the application already reads TIFF images (of course one would be limited by its own computer memory)

- the ROIs are only represented by one point (if I understood well) and not by the "real" shape; I understand that it is due to the fact that the analysis is performed beforehand but maybe could be interesting to find a way to display them as Region of Interest

Some (minor) remarks:

- The authors could also cite the Plugin BAR of ImageJ; even if it does not implement any statistical tool, the ROI color-coding can really help the user to define (instinctively) which parameter can describe the best, for instance, the difference between structures morphology

- I understand the choice of R and shiny framework that offers the adequate tools for this project, but I suggest to find a way (if possible of course) to launch it from another software in order to avoid a workflow using several softwares separately

- a video showing how the software works could also be a bonus

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Reviewer #1: No

Reviewer #2: No

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The Image Data Explorer: interactive exploration of image-derived data

PONE-D-22-14030R1

Dear Dr. Heriche,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Gregg Roman, PhD

Academic Editor

PLOS ONE

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