- Large domain-specific datasets should be deposited in a public repository (e.g. GenBank, INSDC, Protein Data Bank, UK Stem Cell Bank, Addgene, RIKEN Bioresource Centre) and an accession number or access address provided in the published article. Additional databases may be found by consulting the BioSharing database, re3data.org, or the NIH Data Sharing Repositories list.
- Where suitable domain-specific repositories do not exist, authors may deposit in either Dryad, Dataverse, the Open Science Framework, or an institutional repository and provide the access information with the manuscript. Alternately, authors may choose to deposit non-standard data (including figures, posters, rich media) on Figshare or PeerJ Preprints, for example. In all cases, the DOI reference (where applicable) should be provided in the article.
- Any supporting data sets for which there are no suitable repositories must be made available as publishable Supplemental Information files by PeerJ Preprints.
- Where appropriate, physical materials (for example mutant seed stock, or paleontological specimens), should be deposited in recognized centers (for example seed stock centers for the former, or recognized museums or institutions for the latter).
- A non exhaustive list of repositories for physical materials such as cell lines or mutant strains includes the RIKEN Bioresource Centre; the Jackson Laboratory; the European Mouse Mutant Archive; the European Conditional Mouse Mutagenesis Program; the American Type Culture Collection; the Knockout Mouse Project; Addgene; the Mutant Mouse Regional Resource Centers.
- Where novel research compounds are used, their chemical identity must be disclosed.
- In accordance with the principles in Sharing Publication-Related Data and Materials (National Academies Press, 2003), research using proprietary data must also evaluate a piece of comparable public data if the authors cannot or do not make the proprietary data available.
- We strongly encourage that the software be made open source, available under an appropriate license, and deposited in an appropriate archive.
PeerJ Preprints will consider timely and well-targeted literature reviews of fields with broad cross-disciplinary interest. While we do not impose a hard limit, we recommend a maximum of 8,000-12,000 words in order to keep the review focussed. The review should include a rationale for why it is needed, describe who it is intended for, and include a description of the procedures used to ensure that it is comprehensive and unbiased (for example, the search strategies that were employed). Gaps in the literature, future avenues of research and opportunities for cross-disciplinary collaborations should be clearly identified.
Since, by their nature, literature reviews rely heavily on the published work of others, it is especially important to avoid inadvertent plagiarism by copying and pasting sections of text from the original source. In addition, it is very important when quoting or paraphrasing, to correctly acknowledge your sources.
We recommend that your review is structured following the guidelines for Literature Review Articles in standard sections.
PeerJ Preprints welcomes articles describing bioinformatics software tools. These articles should present new software tools (or significant new functionality in existing software) of particular interest to the bioinformatics and/or computational biology communities. The described tools should provide new computational or analytical functionality for researchers.
The functionality of the software should be validated using real-world biological data and, where appropriate, be compared to existing tools. If available as a package (e.g. Python, R, Matlab, Octave), it should be accompanied by a minimal script that downloads the data (if not included in the package), loads it, and performs the analysis to reproduce the results (tables, plots, visualizations etc.) in the manuscript. Documentation & comments should be clear and sufficient to allow a typical user to perform the analysis described in the article. Ideally, the tools should be usable in a workflow that encourages reproducible research practices.
We encourage you to release the software early under an open source license (e.g. MIT, GPL) and make it widely available (i.e. hosted in a public repository such as Github or Bitbucket, or an institutional repository). Use of a version control system (e.g. Git, Subversion etc.) is strongly encouraged as is adherence to language-specific packaging practices where appropriate. We also recommend the inclusion of appropriate unit tests. If made available in this way, the software should be free to noncommercial users and be accessible without requiring any personally identifiable information. Software and validation data sets must comply with PeerJ Preprints Data and Materials Sharing policies. Reliance on a proprietary software such as Matlab does not preclude the publication but in general, a fully open source method is to be preferred.
Note PeerJ Preprints should not be used to name or propose new nomenclatural acts (as per the policies which have been put in place by organizations such as the ICZN and ICN). Instead these articles should be submitted to the peer-reviewed PeerJ journal.
These policies are made available under the Creative Commons CC BY 4.0 license and can be copied for reuse with attribution.