Review Comments JOSS, Reviewer Martin Wegrzyn

[mwegrzyn]

Dear @dvm-shlee et al.,

my name is Martin Wegrzyn and I am one of the reviewers assigned to your submission to JOSS. Thank you for your work on BrkRaw. The following are some comments I have regarding my first impression of the package and the manuscript:

code & examples

• [ ] I tried to run the notebook examples/BrkRaw_PythonAPI.ipynb but got a number of error messages and some inconsistencies with the outputs of the notebook you uploaded.

• Cell 8: Error: “AttributeError: module 'brkraw.lib.reference' has no attribute 'METADATA_FILED_INFO'”
• Cells 15, 20 “AttributeError: 'NoneType' object has no attribute 'T'”
• Cell 37: “TypeError: get_dataobj() got an unexpected keyword argument 'slp_correct'”
• Cell 39 (and others) different output than the one on GitHub: e.g. your affine matrix is

[[  0.4    -0.      0.004 -14.381]
 [ -0.     -0.4     0.     14.968]
 [ -0.004   0.      0.4     1.824]
 [  0.      0.      0.      1.   ]]

mine, when running the code, is

[[-0.399978	-0.000000	-0.004234	14.381493]
 [0.000000	-0.400000	-0.000000	14.968180]
 [0.004234	0.000000	-0.399978	-1.824436]
 [0.000000	0.000000	0.000000	1.000000]]

Hence, there are some changes in the signs (last column). Could this be a problem e.g. with left-right flips of the data?

compare: https://gist.github.com/mwegrzyn/1c8113631a4ab3fe19cf1838f3356b56

• [ ] regarding the example data, I wanted to ask whether there would be a possibility for me to confirm where left and right is in the image?

• [ ] also regarding the example data, the BOLD/EPI images seem to be 3D-files (single volume), not 4D timeseries; is this correct or should I be able to see different volumes? I think it would be useful to have 4D files for testing purposes. Thank you!

• [ ] the BIDS-conversion worked very well, however, it only worked for me if I did not use the .json file and only used the .xlsx file. The command

brkraw bids_convert 20190724_114946_BRKRAW_1_1 dataset_description.xlsx -r dataset_description.json

did not work:

brkraw: error: unrecognized arguments: -r dataset_description.json”

only using

brkraw bids_convert 20190724_114946_BRKRAW_1_1 dataset_description.xlsx”

did work fine!

Manuscript

• [ ] regarding the motivation of the project, when reading the manuscript I get the feeling that you argue that nifiti-conversion is useful; also, your package has the ability to convert to nifti; on the other hand, the companion website mentions that nifiti conversion is a "legacy" function. Hence, I am unsure what the nature of "BrkRaw" is and how much the “raw” handling of the data is desirable from your point of view. E.g. “The module has been built up upon robust low-level Python Application Programming Interface (API), allowing direct raw data access without conversion to provide the advanced and easy-to-use features for data analysis.”; here, I would like to learn more about the analysis on raw data mentioned and why Nifiti conversion is nevertheless such a central part of the package. Thank you.

• [ ] I think it is fair to say that the manuscript would need proofreading. Also, there are some sentences where the meaning is a bit unclear. For example at the end of 1st paragraph: “However, the preclinical MRI research using laboratory animals or objects does not require the DICOM conversion step and is rather inefficient.” > this sounds like preclinical MRI is inefficient, while I assume that the intended meaning is that the DICOM conversion step would be inefficient for preclinical MRI?

• [ ] Figures: Overall, I found the figures difficult to understand. Maybe more extensive figure legends or in-text descriptions could be helpful (although I saw in other JOSS papers, that figure descriptions are often as brief as yours. Still, it might be worth considering)

• [ ] Figure 1: Could you explain what we see in the “between dataset comparison” and how we can visually assess successful conversion?

• [ ] Figure 4: the contents of the four subplots are not readable. I would be great if you could increase the resolution of the figure. Thank you.

I hope you find these comments to be helpful. Please let me know if you have any questions regarding the points I raised. Thank you for your time and consideration.

Best regards, Martin Wegrzyn

[dvm-shlee]

Thank you for your comments! I will prepare the response soon and revise the code and paper as well soon!