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Guide for GigaScience reviewers

Thank you for agreeing to review a manuscript submitted to GigaScience. Our aim with GigaScience is to champion high standards of documentation, testing, and reproducibility of the creation and analyses of large-scale data. GigaScience therefore has strict requirements on data availability, licensing, documentation and testing. To achieve this, as a referee we will ask you to review manuscripts that present novel datasets with a specific eye toward making certain that the minimum standards for the field are fulfilled and that all appropriate testing of data accuracy has been carried out. If reviewers feel they are unable to assess specific issues concerning data, please state this in your comments to the editor.


Open Peer-Review Policy. GigaScience has an open (non-anonymous) peer-review as it improves the transparency of review processes and publication as a whole. Therefore, as a default, we will pass a reviewer's name on to the authors along with the comments. We do not have an option for anonymous peer review. Reviewers are asked to declare any competing interests and to agree to Open Peer Review, which works on two levels: the authors receive the signed report and, if the manuscript is published, the same report will be made available to the readers. Reviewer reports are made public under an Open Access license Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/). The pre-publication history (initial submission, reviews and revisions - see, for example, pre-publication history) will also be posted on the Web with the published article. For further information please see our Editorial.


Giving Reviewers Credit. GigaScience has partnered with Publons (blogs.biomedcentral.com/bmcblog/2014/06/26/gigascience-helping-reviewers-get-credit-through-publons) to give our reviewers credit for their reviews. Reviews published by GigaScience will automatically be imported to Publons and will appear as verified pre-publication reviews, giving GigaScience reviewers greater recognition for their contributions, and further showcasing the robustness of GigaScience’s review process (see GigaScience on Publons). To credit our hard working reviewers further, DOIs are issued to reviews so they can be individually cited and integrated onto ORCID profiles.

For our reviewers, this partnership makes setting up your cross-publisher reviewer record on Publons even easier. Once you complete a review with GigaScience, you will find it curated and automatically added to your Publons reviewer profile, along with reviews from other journals partnered with Publons. As always, you can edit the level of information that is displayed about each review at any time.

GigaScience supports the open science approach to peer-review and the publication process. We support the principles of the open peer-review oath and encourage reviewers to use such an approach (see Aleksic et al. 2015, doi: 10.12688/f1000research.5686.2 for more details):

Principles of the open peer-review oath

  • Principle 1: I will sign my name to my review

  • Principle 2: I will review with integrity

  • Principle 3: I will treat the review as a discourse with you; in particular, I will provide constructive criticism

  • Principle 4: I will be an ambassador for the practice of open science

Reviewing of the manuscript. Suitability of research for publication in GigaScience is dependent primarily on the data quality and utility and on the soundness of the biological conclusions from all data analyses, rather than on a subjective assessment of its immediate impact. Note, that although GigaScience will not make general interest level the primary criterion for publication, it aims to provide its readership with the highest quality large-scale data, data analyses tools, and analyses that will have significant usability and utility for the community.

As a referee we ask that you assess the paper on its own merits. The following list of potential issues may be helpful.

1. Is the rationale for collecting and analyzing the data well defined?

Is the work carried out on a dataset that can be described as "large-scale" within the context of its field? Does it clearly describe the dataset and provide sufficient context for the reader to understand its potential uses? Does it properly describe previous work?

2. Is it clear how data was collected and curated?

Credit should be given for transparency and provision of all supporting information.

3. Is it clear - and was a statement provided - on how data and analyses tools used in the study can be accessed?

While we make every effort to make sure this information is available, we appreciate reviewers providing an extra eye to make absolutely certain that this information is clearly stated and properly available. Data availability and access to tools are essential for reproducibility and provide the best means for reuse.

4. Are accession numbers given or links provided for data that, as a standard, should be submitted to a community approved public repository?

Following community standards for data sharing is a requirement of the journal. Additionally, data sharing in the broadest possible manner expands the ways in which data and tools can be accessed and used.

5. Is the data and software available in the public domain under a Creative Commons license?

Note, that unless otherwise stated, data hosted in our database (GigaDB) is available under a CC0 waiver. Additionally, did the authors indicate where the software tools and relevant source code are available, under an appropriate Open Source Initiative compliant license? If the source code is currently not in a hosted repository, we can help authors copy it over to a GigaScience GitHub repository.

6. Are the data sound and well controlled?

If you feel that inappropriate controls have been used please say so, indicating the reasons for your concerns, and suggesting alternative controls where appropriate. If you feel that further experimental/clinical evidence is required for obtaining solid biological conclusions and substantiating the results, please provide details.

7. Is the interpretation (Analysis and Discussion) well balanced and supported by the data?

The interpretation should discuss the relevance of all the results in an unbiased manner. Are the interpretations overly positive or negative? Note that the authors may include opinions and speculations in an optional 'Potential Implications' section of the manuscript; thus, if there is material in other parts of the manuscript that you feel would be better suited in such a section, please state that. Conclusions drawn from the study should be valid and result directly from the data shown, with reference to other relevant work as applicable. Have the authors provided references wherever necessary?

8. Are the methods appropriate, well described, and include sufficient details and supporting information to allow others to evaluate and replicate the work?

Please remark on the suitability of the methods for the study.

If statistical analyses have been carried out, please indicate if you feel they need to be assessed specifically by an additional reviewer with statistical expertise.

9. What are the strengths and weaknesses of the methods?

Please comment on any improvements that could be made to the study design to enhance the quality of the results. If any additional experiments are required, please give details. If novel experimental techniques were used please pay special attention to their reliability and validity.

10. Have the authors followed best-practices in reporting standards?

This is an essential component as ease of reproducibility and usability are key criteria for manuscript publication. Please note, the methodology sections should never contain “protocol available upon request” or “e-mail author for detailed protocol”. Have the authors followed and used reporting checklists recommended in our page on the Biosharing network and if the methods are amenable, have the authors used workflow management systems such as Galaxy, Taverna or one of the many related systems listed on MyExperiment? We can also host these in our GigaGalaxy server if they currently do not have a home. We also encourage use of virtual machines and containers such as Docker. And the use and deposition of both wet-lab and computational protocols in a protocols repository like protocols.io.

11. Can the writing, organization, tables and figures be improved?

Although the editorial team may also assess the quality of the written English, please do comment if you consider the standard is below that expected for a scientific publication.

If the manuscript is organized in such a manner that it is illogical or not easily accessible to the reader please suggest improvements. Please provide feedback on whether the data are presented in the most appropriate manner; for example, is a table being used where a graph would give increased clarity? Do the figures appear to be genuine, i.e. without evidence of manipulation, and of a high enough quality to be published in their present form?

12. When revisions are requested.

Reviewers may recommend revisions for any or all of the following reasons: the data require additional testing to ensure their quality, additional data are required to support the authors' conclusions; better justification is needed for the arguments based on existing data; or the clarity and/or coherence of the paper needs to be improved.

13. Are there any ethical or competing interests issues you would like to raise?

The study should adhere to ethical standards of scientific/medical research and the authors should declare that they have received ethics approval and/or patient consent for the study, where appropriate.

Whilst we do not expect reviewers to delve into authors' competing interests, if you are aware of any issues that you do not think have been adequately addressed, please inform the Editorial office.


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