Dear Dr Koutsovoulos,

Thank you very much for submitting your manuscript "AvP: a software package for automatic phylogenetic detection of candidate horizontal gene transfers." 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.

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

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

[1] A letter containing a detailed list of your responses to the 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.

Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.

Thank you again for your submission. 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,

Mark Ziemann

Academic Editor

PLOS Computational Biology

William Noble

Section Editor

PLOS Computational Biology

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Dear Dr Koutsovoulos,

The manuscript has been reviewed by two experts in the field and overall impressions of the software and manuscript were positive, although both reviewers requested greater clarity in the writing and explanation of certain points. Reviewer 2 point 2 has requested the software to detect non-protein coding genes, which is an excellent suggestion and of reat value to the field, however I am mindful that this may require extensive retooling of the software. I would like to flag this software feature as optional for the authors to address, however it must be mentioned as a limitation/future direction in the discussion of the manuscript along with any challenges that may be apparent when detecting HGT of non-coding genes. I look forward to receiving a revised version of the manuscript.

Regards,

Mark Ziemann, PhD

Reviewer's Responses to Questions

Comments to the Authors:

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

Reviewer #1: Koutsovolous et al. present AvP, a pipeline to automatically identify horizontally transferred genes, along with a set of metrics that allow users to evaluate these predictions. By using phylogenetics at its core, AvP represents a substantial improvement compared to existing best BLAST hit-based approaches. Moreover, the metrics they develop help to address many of the issues with HGT detection (e.g. contamination in assemblies and databases). I was able to install the software from GitHub and the documentation is clear. I have no doubt that AvP will be well used and well cited by researchers interested in HGT. I struggled to find anything to complain about and, as such, I would be happy to recommend the manuscript once a few of my very minor comments (below) have been addressed/considered.

1. Lines 32-38: It took me a few readings of this paragraph to work out that the authors were suggesting that the existing methods that reconcile gene/species trees were not ideal because of the requirement of a species tree - could it be reworked slightly to make the message clearer? Even adding “However” before “To achieve this” would help. Note there are a few typos in here too: hundred > hundreds, compare > comparing, wth > with.

2. Lines 57-59: “AI features file can be automatically generated with the Alienness webserver” - I note that this is scored out in the GitHub instructions; is this no longer true?

3. Lines 91-92: “is all not in Ingroup” > “is all species not in Ingroup”

4. Lines 153-154: note that the sequenced Sciento strain of tardigrades was redescribed as H. exemplaris. I’ll let the authors decide if they'd rather use H. dujardini for consistency with previous publications or H. exemplaris for taxonomic correctness.

5. Lines 185-204: The authors only discuss the two problematic cases in their run on C. elegans, which is valuable, but what about all the other predicted HGT loci? How many were there? Were any of interest or consistent with previous work? I understand that analysing this in-depth is beyond the remit of this manuscript, but it seems odd to not mention anything other than where this had problems. A few examples of what can be discovered with the pipeline would be a valuable addition.

6. Lines 201-203: “Consequently, it seems that this new AHS metric is able to correct errors due to contamination and taxonomic assignment bias.” Perhaps I’m confused but doesn’t the AHS value, which suggests that the rodent protein is a strong HGT candidate (10356), suggests the opposite? Surely AHS is positively misleading in this case, and even more so than AI? Or are the authors suggesting that it’s the difference between AHS and AI that is indicative of a false positive?

7. Github: it would be great if the authors could add some worked examples (e.g. the tardigrade and/or C. elegans examples in the paper) to show users how to set this up.

Reviewer #2: I appreciate that Koutsovoulos et al. put multiple steps that are used to detect HGT into one automatic tool called “AvP”. The study is written well and the tool is friendly to users.

I have four main concerns that authors might wish to address.

1. The AvP incorporated the AI values and phylogenetic robustness. Not sure how different AI cutoff will influence outputs. Of courses, there is no standard criterion. Given the complexity of the database, sometimes, the database could contain contamination so that the query protein is highly similar to the hit from contamination. A recent paper (https://pubmed.ncbi.nlm.nih.gov/35853453/) has considered anther parameter “outg_pct”, that is the percentage of species from OUTGROUP lineage in the list of the top 1,000 hits that have different taxonomic species names. Did you consider this too? If not, why or discuss it?

2. The AvP is aiming to detect HGT based on protein-coding genes (or protein sequence), which has been done many previous studies (although they built their own pipelines). Would you please extend your tool to non-coding sequences? If you can make it, that will be much helpful, because nearly all published studies have not done this. And I think non-coding sequences could aslo be HGT too.

3. It seems that the graph neural network (or machine learning) was used to predict the HGT. if it is possible, please compare your tool with it in term of accuracy of HGT identification. If this’s hard, it would be good to discuss this aspect in your study for future direction.

4. If The AvP tool can also report the characteristics of HGT including the codon usage bias, dn/ds, the sequence similarity between donor and recipient, which would be better.

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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.

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Reviewer #1: No

Reviewer #2: 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, we recommend that you deposit your 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. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Dear Dr Koutsovoulos,

Thank you for the revised manuscript which I see has addressed most of the reviewer comments.

For your general information, if you agree with the reviewers' comments, it is good form to address them in the manuscript, as it is likely that the readership will have similar concerns. In the rebuttal letter, indicate which lines of the manuscript have been added/amended. This is relevant to points R1P2, R2P1, R2P2. If you could please amend the manuscript and rebuttal letter to this effect it can be send to reviewer 2 again.

Regards,

Mark Ziemann, PhD

---------------

We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments. Your revised manuscript is also likely to be sent to reviewers for further evaluation.

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

[1] A letter containing a detailed list of your responses to the 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.

Please prepare and submit your revised manuscript within 60 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. Please note that revised manuscripts received after the 60-day due date may require evaluation and peer review similar to newly submitted manuscripts.

Thank you again for your submission. 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,

Mark Ziemann

Academic Editor

PLOS Computational Biology

William Noble

Section Editor

PLOS Computational Biology

***********************

Dear Dr Koutsovoulos,

Thank you for the revised manuscript which I see has addressed most of the reviewer comments.

For your general information, if you agree with the reviewers' comments, it is good form to address them in the manuscript, as it is likely that the readership will have similar concerns. In the rebuttal letter, indicate which lines of the manuscript have been added/amended. This is relevant to points R1P2, R2P1, R2P2. If you could please amend the manuscript and rebuttal letter to this effect it can be send to reviewer 2 again.

Regards,

Mark Ziemann, PhD

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, we recommend that you deposit your 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. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Dear Koutsovoulos,

We are pleased to inform you that your manuscript 'AvP: a software package for automatic phylogenetic detection of candidate horizontal gene transfers.' 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,

Mark Ziemann

Academic Editor

PLOS Computational Biology

William Noble

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 #2: Thank you very much for including my suggestions! I don’t have any concerns and think it’s ready for publication.

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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 #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 #2: Yes: Xing-Xing Shen