Dear Dr. Solis-Lemus,

Thank you very much for submitting your manuscript "HighDimMixedModels.jl: Robust High Dimensional Mixed Models across Omics Data" 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. In light of the reviews (below this email), we would like to invite the resubmission of a significantly-revised version that takes into account the reviewers' comments.

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[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).

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Sincerely,

Sonika Tyagi

Academic Editor

PLOS Computational Biology

Alison Marsden

Section Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: The reviewer report has been attached.

Reviewer #2: The authors introduce an algorithmic approach suited to longitudinal (i.e. time-series) and high-dimensional biological data i.e. (where p >> n). The main novelty is the generalisability of the approach to many conventional omics data types. Software is accessible under a MIT licence with comprehensive documentation and worked examples.

Major comments:

1. Benchmarking of the various omics studies is carried out, but addressed individually. It would be useful for the reader to see a combined summary table or figure indicating the performance of the HigDimMixedModels approach against the results/models of each study featured in the manuscript.

Line 39-40

“We provide a table summarising existing methods”

It is possible that I missed it, but it seems that this table is missing from the supplementary material at this time? A direct reference to the table number would also be useful.

Minor comments:

1. Scripts, data, documentation and results are available and well-organised, which streamlines the review process, boosts reproducibility and software use. However, it would be useful for the authors to provide an estimate of compute resource use and time for a given dataset (e.g. those outlined in the manuscript and documentation).

2. The scope of this package and study is focused on analysing single-omics data. However, many studies now incorporate multi-omics data analyses instead of single-omics analyses. If I understand correctly, it appears that this work may complement multi-omics studies by standardising data in a generic way though before multi-omics data integration (eg by using the mixOmics package). Can the authors discuss the potential use of this method for this application?

3. The discussion section implies that the authors intend to refine and expand their work. For the future, it would be useful to add biological examples (e.g. those in the manuscript) to the documentation directly covering multiple use case scenarios. Currently, the documentation has an example of its use on a small non-biological dataset, although this is understandable for testing purposes.

Line 362

Binary or count data is common in biology and is often transformed into a continuous distribution for analysis, for example in the case of RNA-Seq data. The authors may be interested in adding some comments on the potential feasibility of adapting this method for non-continuous data.

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data or code —e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes: Tyrone Chen

Figure Files:

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Attachments

Attachment

Submitted filename: review report.docx

Dear Dr. Solís-Lemus,

We are pleased to inform you that your manuscript 'HighDimMixedModels.jl: Robust High Dimensional Mixed Models across Omics Data' 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,

Marc R Birtwistle, PhD

Section Editor

PLOS Computational Biology

Alison Marsden

Academic Editor

PLOS Computational Biology

Feilim Mac Gabhann

Editor-in-Chief

PLOS Computational Biology

Jason Papin

Editor-in-Chief

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: Thank you for addressing the comments.

Reviewer #2: The authors have addressed all comments, congratulations on the article.

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data or code —e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: 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: Yes: Tyrone Chen