The introduction provides context as to why the software tool was developed and what need it addresses. It is good scholarly practice to mention previously developed tools that address similar needs, and why the current tool is needed.
For software tool papers, this section should address how the tool works and any relevant technical details required for implementation of the tool by other developers.
This part of the methods should include the minimal system requirements needed to run the software and an overview of the workflow for the tool for users of the tool.
This section is only required if the paper includes novel data or analyses, and should be written as a traditional results section.
This section is required if the paper does not include novel data or analyses. Examples of input and output files should be provided with some explanatory context. Any novel or complex variable parameters should also be explained in sufficient detail to allow users to understand and use the tool's functionality.
This section is only required if the paper includes novel data or analyses, and should be written in the same style as a traditional discussion section. Please include a brief discussion of allowances made (if any) for controlling bias or unwanted sources of variability, and the limitations of any novel datasets.
This section is only required if the paper includes novel data or analyses, and should be written as a traditional conclusion.
This section is required if the paper does not include novel data or analyses. It allows authors to briefly summarize the key points from the article.
Please add details of where any datasets that are mentioned in the paper, and that have not have not previously been formally published, can be found. If previously published datasets are mentioned, these should be cited in the references, as per usual scholarly conventions.
This section will be generated by the Editorial Office before publication. Authors are asked to provide some initial information to assist the Editorial Office, as detailed below.
In order to give appropriate credit to each author of an article, the individual contributions of each author to the manuscript should be detailed in this section. We recommend using author initials and then stating briefly how they contributed.
All financial, personal, or professional competing interests for any of the authors that could be construed to unduly influence the content of the article must be disclosed and will be displayed alongside the article. If there are no relevant competing interests to declare, please add the following: 'No competing interests were disclosed'.
Please state who funded the work discussed in this article, whether it is your employer, a grant funder etc. Please do not list funding that you have that is not relevant to this specific piece of research. For each funder, please state the funder’s name, the grant number where applicable, and the individual to whom the grant was assigned. If your work was not funded by any grants, please include the line: ‘The author(s) declared that no grants were involved in supporting this work.’
This section should acknowledge anyone who contributed to the research or the article but who does not qualify as an author based on the criteria provided earlier (e.g. someone or an organization that provided writing assistance). Please state how they contributed; authors should obtain permission to acknowledge from all those mentioned in the Acknowledgments section. Please do not list grant funding in this section.
x <- 1:10 x
You can specify the caption for a plot using the fig.cap
argument at the start of the Rmarkdown code chunk.
plot(x)
We can use LaTeX syntax to typeset mathematics. If you're already familiar with LaTeX this should work as you expect. Let $X_1, X_2, \ldots, X_n$ be a sequence of independent and identically distributed random variables with $\text{E}[X_i] = \mu$ and $\text{Var}[X_i] = \sigma^2 < \infty$, and let $$S_n = \frac{X_1 + X_2 + \cdots + X_n}{n} = \frac{1}{n}\sum_{i}^{n} X_i$$ denote their mean. Then as $n$ approaches infinity, the random variables $\sqrt{n}(S_n - \mu)$ converge in distribution to a normal $\mathcal{N}(0, \sigma^2)$.
We can create tables using the pipe symbol. Markdown tables tend to lack some of the more sophisticated formatting available in LaTeX, so you may need to edit this later to get the desired format.
| First name | Last Name | Grade | | ----------- | --------- | ----- | | John | Doe | 7.5 | | Richard | Miles | 2 |
Table: Hello Caption!
Here is another table
| First name | Last Name | Grade | | ----------- | :-------: | ----: | | John | Doe | 7.5 | | Richard | Miles | 2 |
Table: This table has text justification!
Please give figures appropriate filenames eg: figure1.pdf, figure2.png.
Figure legends should briefly describe the key messages of the figure such that the figure can stand alone from the main text. However, all figures should also be discussed in the article text. Each legend should have a concise title of no more than 15 words. The legend itself should be succinct, while still explaining all symbols and abbreviations. Avoid lengthy descriptions of methods.
For any figures reproduced from another publication (as long as appropriate permission has been obtained from the copyright holder —see under the heading 'Submission'), please include a line in the legend to state that: 'This figure has been reproduced with kind permission from [include original publication citation]'.
You can make lists with numbering:
or bullet points
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