We strongly recommend (and in some cases require) that authors adhere to the reporting standards which have been adopted by their field (or which apply to their study design).
All statistical results should be reported in full, including the test that was performed, the reason for choosing that test, the corresponding test statistic, sample size, degrees of freedom, the exact p-value expressed up to 2 decimal spaces unless 'p<0.001' or confidence interval, and effect sizes. Where multiple testing is performed, suitable corrections must be made.
Do not report inferential statistics such as p values or confidence intervals for known quantities such as baseline measurements. The spread of the data can be indicated by descriptive statistics such as standard deviation, or quantiles and ranges.
Where appropriate, we recommend that you overlay bar graphs with scatter plots showing individual data points, or use another method to show the distribution of the data, such as boxplots, violin plots, etc.
PeerJ will consider timely and well-targeted literature reviews of fields with broad cross-disciplinary interest within the journal's scope. While we do not impose a hard limit, we recommend a maximum of 8,000-12,000 words in order to keep the review focused. 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 welcomes articles describing chemoinformatics 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, where appropriate, be validated using real-world chemical data and/or 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 must 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.
The software must be released under an open source license (e.g. MIT, GPL) and be 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. The software must be free to noncommercial users, and must be accessible without requiring any personally identifiable information. Software and validation data sets must comply with PeerJ 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.
Bioinformatics studies that are based on the analysis of previously published datasets (for instance, sequences from TCGA, microarray experiments from GEO, data from TARGET, SEER, NHIRD, NHANES, etc.) must both (i) answer a biological question not considered in the original publication (if there is one) or reassess the data to arrive at a different conclusion and (ii) validate the findings using an independent dataset or using previously unreported clinical or experimental data.
If the submission searches or extracts information from a public database but does not either compare independent datasets or validate the findings using primary data, then this will be considered out of scope (as it is an initial exploration rather than a full research article). Splitting a dataset to form a training and testing set, or pooling multiple datasets without a completely independent validation set will not be considered (see e.g. https://doi.org/10.1073/pnas.102102699).
Multiple testing correction (False discovery rate and family-wise error rate control) must be used for omics data analysis.
The analysis code must be provided and made publicly available - this must allow the reader to reproduce the analysis starting with the raw data to the results. Where the analysis was performed using online or GUI tools, the workflow must be described in enough detail (including where appropriate, version numbers, parameter settings, date the online analysis was performed, etc.) to allow readers to reproduce the findings.
In general, it is expected that work involving animal experiments will be submitted to PeerJ - the Journal of Life and Environmental Science, but if the intended audience is the chemistry community and the animal experiments are a minor part of the overall work then it will be considered for publication in PeerJ Chemistry journals, so long as it complies with the usual ethical requirements.
In general, it is expected that work involving human subjects will be submitted to PeerJ - the Journal of Life and Environmental Science, but if the intended audience is the chemistry community and the human experiments are a minor part of the overall work then it will be considered for publication in PeerJ Chemistry journals, so long as it complies with the usual ethical requirements.
These policies are made available under the Creative Commons CC BY 4.0 license and can be copied for reuse with attribution.