Transfer Alert

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Dear Dr Patel,

Thank you very much for submitting your manuscript 'A systematic machine learning and data type comparison yields robust metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type' for review by PLOS Computational Biology. Your manuscript has been fully evaluated by the PLOS Computational Biology editorial team and in this case also by independent peer reviewers. The reviewers appreciated the attention to an important problem, but raised some substantial concerns about the manuscript as it currently stands. While your manuscript cannot be accepted in its present form, we are willing to consider a revised version in which the issues raised by the reviewers have been adequately addressed. We cannot, of course, promise publication at that time.

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We are sorry that we cannot be more positive about your manuscript at this stage, but if you have any concerns or questions, please do not hesitate to contact us.

Sincerely,

Nicola Segata

Associate Editor

PLOS Computational Biology

Jason Papin

Editor-in-Chief

PLOS Computational Biology

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

[LINK]

While the reviewers found the paper of potential interest, they all rised substantial concerns. If the authors are able to address all the issued raised by the reviewer, I would be willing to consider a revised manuscript.

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: The authors present a systematic comparison of machine learning tools applied to microbiome data.

Overall, this may be interesting, but I'm lacking three major parts:

1. The motivation is not sufficient to explain what we're gaining in this paper.

2. Very much related, the outcome of this paper is unclear to me. It reads more like a grocery list of models and their results, and which model will find which variable, without any profound conclusion that the reader can take home.

3. Personally, I think papers should be accessible to undergraduate students. This paper is not deductive enough. It is difficult to read. It uses terms (and acronyms) without explaining them, and it doesn't tell a story that the reader can follow.

The introduction is lacking some papers that have worked on these problems before, with addressing their successes and limitations. A big portion of the introduction is really results from this paper. As the reader reaches the real results section the motivation is still unclear.

Maybe if such an intro was present, the authors would not have claimed to be the "first to successfully predict infant age and sex from microbiome data". For example, age was predicted in a paper that examined malnutrition from the Gordon lab (Subramanian et al, Nature 2014), and used to find that malnutritioned children had a "younger microbiome age". If the authors meant to say that others may have predicted age, but they are the first to predict both age and sex, then this current text in misleading. Also, again, the motivation of why such a prediction would be useful is greatly missing.

Overall, I think that comparing many tools could be interesting, but current paper does not teach its readers about why some models are better than others, and does not reveal any novel biological insight from this comparison.

Reviewer #2: Review is uploaded as an attachment.

Reviewer #3: Attached

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Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Computational Biology data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No: The supplemental figures appear to be missing.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Attachments

Attachment

Submitted filename: plos_comp_bio_review.pdf

Attachment

Submitted filename: PLOS_CB_Le_Goallec_and_Tierney_et_al_review.pdf

Dear Dr. Patel,

Thank you very much for submitting your manuscript "A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.

Thanks for your revised manuscript. The reviewers faviourably evaluated it. They still have some comments and suggestions to clarify some points and further improve readbility that should be possible to address with a minor revision.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. 

When you are ready to resubmit, please upload the following:

[1] A letter containing a detailed list of your responses to all review comments, and a description of the changes you have made in the manuscript. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out

[2] Two versions of the revised manuscript: one with either highlights or tracked changes denoting where the text has been changed; the other a clean version (uploaded as the manuscript file).

Important additional instructions are given below your reviewer comments.

Thank you again for your submission to our journal. We hope that our editorial process has been constructive so far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.

Sincerely,

Nicola Segata

Associate Editor

PLOS Computational Biology

Jason Papin

Editor-in-Chief

PLOS Computational Biology

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A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

[LINK]

Thanks for your revised manuscript. The reviewers faviourably evaluated it. They still have some comments and suggestions to clarify some points and further improve readbility that should be possible to address with a minor revision.

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: The authors have addressed my previous comments.

I would still consider narrowing down the number of models tested (while moving some to the supp material) so the paper can be more concise and (yet again) more educating to the reader in terms of types of models and their expected behavior.

Reviewer #2: Uploaded as an attachment

Reviewer #3: The authors have addressed my concerns.

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Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Computational Biology data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Figure Files:

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

Data Requirements:

Please note that, as a condition of publication, PLOS' data policy requires that you make available all data used to draw the conclusions outlined in your manuscript. Data must be deposited in an appropriate repository, included within the body of the manuscript, or uploaded as supporting information. This includes all numerical values that were used to generate graphs, histograms etc.. For an example in PLOS Biology see here: http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001908#s5.

Reproducibility:

To enhance the reproducibility of your results, PLOS recommends that you deposit laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see http://journals.plos.org/ploscompbiol/s/submission-guidelines#loc-materials-and-methods

Attachments

Attachment

Submitted filename: review_revised_version.pdf

Dear Dr. Patel,

We are pleased to inform you that your manuscript 'A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type' has been provisionally accepted for publication in PLOS Computational Biology.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Computational Biology. 

Best regards,

Nicola Segata

Associate Editor

PLOS Computational Biology

Jason Papin

Editor-in-Chief

PLOS Computational Biology

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