Default_Rmarkdown.rmd

---
title: "Title of Markdown Document" 
author: "Author: Your Name"
date: "Last update: `r format(Sys.time(), '%d %B, %Y')`" 
output:
  html_document:
    toc: true
    toc_float:
        collapsed: true
        smooth_scroll: true
    toc_depth: 3
    fig_caption: yes
    code_folding: show
    number_sections: true

fontsize: 14pt
#bibliography: bibliography.bib
---

<!---
- Compile from command-line
Rscript -e "rmarkdown::render('sample.Rmd', c('html_document'), clean=FALSE)"
-->


# Section 1

## Overview 

Provide some overview about the data, code, analysis and results. 

## Subsection 1.2

### Subsubsection 1.2.1

```{r install_rmarkdown, eval=FALSE}
install.packages("rmarkdown")
```
### Metadata section

The metadata section (YAML header) in an R Markdown script defines how it will be processed and 
rendered. The metadata section also includes both title, author, and date information as well as 
options for customizing the output format. 

```
 ---
title: "My First R Markdown Document"
author: "Author: First Last"
date: "Last update: `r format(Sys.time(), '%d %B, %Y')`"
output:
  BiocStyle::html_document:
    toc: true
    toc_depth: 3
    fig_caption: yes

fontsize: 14pt
bibliography: bibtex.bib
 ---
```

### R code chunks

R Code Chunks can be embedded in an R Markdown script by using three backticks
at the beginning of a new line along with arguments enclosed in curly braces
controlling the behavior of the code. 

```{r code_chunk_name, eval=FALSE}
	x <- 1:10
```

The following lists the most important arguments to control the behavior of R code chunks:

+ `r`: specifies language for code chunk, here R
+ `chode_chunk_name`: name of code chunk; this name needs to be unique
+ `eval`: if assigned `TRUE` the code will be evaluated
+ `warning`: if assigned `FALSE` warnings will not be shown
+ `message`: if assigned `FALSE` messages will not be shown
+ `cache`: if assigned `TRUE` results will be cached to reuse in future rendering instances
+ `fig.height`: allows to specify height of figures in inches
+ `fig.width`: allows to specify width of figures in inches

For more details on code chunk options see [here](https://www.rstudio.com/wp-content/uploads/2015/03/rmarkdown-reference.pdf).


### Python code chunks
```{python python.reticulate = FALSE}
```
### SQL code chunks
```{SQL }
```


### Render `Rmd` script

An R Markdown script can be evaluated and rendered with the following `render` command or by pressing the `knit` button in RStudio.
The `output_format` argument defines the format of the output (_e.g._ `html_document`). The setting `output_format="all"` will generate 
all supported output formats. Alternatively, one can specify several output formats in the metadata section as shown in the above example.

```{r render_rmarkdown, eval=FALSE, message=FALSE}
rmarkdown::render("sample.Rmd", clean=TRUE, output_format="html_document")
```

The following shows two options how to run the rendering from the command-line.

```{sh render_commandline, eval=FALSE, message=FALSE}
$ Rscript -e "rmarkdown::render('sample.Rmd', clean=TRUE)"
```

Alternatively, one can use a Makefile to evaluate and render an R Markdown
script. A sample Makefile for rendering the above `sample.Rmd` can be
downloaded [`here`](https://raw.githubusercontent.com/tgirke/GEN242/gh-pages/_vignettes/07_Rbasics/Makefile).
To apply it to a custom `Rmd` file, one needs open the Makefile in a text
editor and change the value assigned to `MAIN` (line 13) to the base name of
the corresponding `.Rmd` file (_e.g._ assign `systemPipeRNAseq` if the file
name is `systemPipeRNAseq.Rmd`).  To execute the `Makefile`, run the following
command from the command-line.

```{sh render_makefile, eval=FALSE, message=FALSE}
$ make -B
```


### Learning Markdown

The basic syntax of Markdown and derivatives like kramdown is extremely easy to learn. Rather
than providing another introduction on this topic, here are some useful sites for learning Markdown:

+ [Markdown Intro on GitHub](https://guides.github.com/features/mastering-markdown/)
+ [Markdown Cheet Sheet](https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet)
+ [Markdown Basics from RStudio](http://rmarkdown.rstudio.com/authoring_basics.html) 
+ [R Markdown Cheat Sheet](http://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf)
+ [kramdown Syntax](http://kramdown.gettalong.org/syntax.html)

### Tables

There are several ways to render tables. First, they can be printed within the R code chunks. Second, 
much nicer formatted tables can be generated with the functions `kable`, `pander` or `xtable`. The following
example uses `kable` from the `knitr` package.

```{r kable}
library(knitr)
kable(iris[1:12,])
```

A much more elegant and powerful solution is to create fully interactive tables with the [`DT` package](https://rstudio.github.io/DT/). 
This JavaScirpt based environment provides a wrapper to the DataTables library using jQuery. The resulting tables can be sorted, queried and resized by the
user. 

```{r dt}
library(DT)
datatable(iris, filter = 'top', options = list(
  pageLength = 100, scrollX = TRUE, scrollY = "600px", autoWidth = TRUE
))
```

### Figures

Plots generated by the R code chunks in an R Markdown document can be automatically 
inserted in the output file. The size of the figure can be controlled with the `fig.height`
and `fig.width` arguments.

```{r some_jitter_plot, eval=TRUE}
library(ggplot2)
dsmall <- diamonds[sample(nrow(diamonds), 1000), ]
ggplot(dsmall, aes(color, price/carat)) + geom_jitter(alpha = I(1 / 2), aes(color=color))
```

Sometimes it can be useful to explicitly write an image to a file and then insert that 
image into the final document by referencing its file name in the R Markdown source. For 
instance, this can be useful for time consuming analyses. The following code will generate a 
file named `myplot.png`. To insert the file  in the final document, one can use standard 
Markdown or HTML syntax, _e.g._: `<img src="myplot.png"/>`.  

```{r some_custom_inserted_plot, eval=TRUE, warning=FALSE, message=FALSE}
png("myplot.png")
ggplot(dsmall, aes(color, price/carat)) + geom_jitter(alpha = I(1 / 2), aes(color=color))
dev.off()
```
<center><img title="some_title" src="myplot.png"/></center>

### Inline R code

To evaluate R code inline, one can enclose an R expression with a single back-tick
followed by `r` and then the actual expression.  For instance, the back-ticked version 
of 'r 1 + 1' evaluates to `r 1 + 1` and 'r pi' evaluates to `r pi`.

### Mathematical equations

To render mathematical equations, one can use standard Latex syntax. When expressions are 
enclosed with single `$` signs then they will be shown inline, while 
enclosing them with double `$$` signs will show them in display mode. For instance, the following 
Latex syntax `d(X,Y) = \sqrt[]{ \sum_{i=1}^{n}{(x_{i}-y_{i})^2} }` renders in display mode as follows:

$$d(X,Y) = \sqrt[]{ \sum_{i=1}^{n}{(x_{i}-y_{i})^2} }$$

### Citations and bibliographies

Citations and bibliographies can be autogenerated in R Markdown in a similar
way as in Latex/Bibtex. Reference collections should be stored in a separate
file in Bibtex or other supported formats. To cite a publication in an R Markdown 
script, one uses the syntax `[@<id1>]` where `<id1>` needs to be replaced with a 
reference identifier present in the Bibtex database listed in the metadata section 
of the R Markdown script  (_e.g._ `bibtex.bib`). For instance, to cite Lawrence et al. 
(2013), one  uses its reference identifier (_e.g._ `Lawrence2013-kt`) as `<id1>` [@Lawrence2013-kt]. 
This will place the citation inline in the text and add the corresponding
reference to a reference list at the end of the output document. For the latter a 
special section called `References` needs to be specified at the end of the R Markdown script.
To fine control the formatting of citations and reference lists, users want to consult this 
the corresponding [R Markdown page](http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html).
Also, for general reference management and outputting references in Bibtex format [Paperpile](https://paperpile.com/features) 
can be very helpful.


### Viewing R Markdown report on HPCC cluster

R Markdown reports located on UCR's HPCC Cluster can be viewed locally in a web browser (without moving 
the source HTML) by creating a symbolic link from a user's `.html` directory. This way any updates to 
the report will show up immediately without creating another copy of the HTML file. For instance, if user 
`ttest` has generated an R Markdown report under `~/bigdata/today/rmarkdown/sample.html`, then the 
symbolic link can be created as follows:

```{r rmarkdown_symbolic_link, eval=FALSE}
cd ~/.html
ln -s ~/bigdata/today/rmarkdown/sample.html sample.html
```

After this one can view the report in a web browser using this URL [http://biocluster.ucr.edu/~ttest/rmarkdown/sample.html](http://biocluster.ucr.edu/~ttest/rmarkdown/sample.html).
If necessary access to the URL can be restricted with a password following the instructions [here](http://hpcc.ucr.edu/manuals_linux-cluster_sharing.html#sharing-files-on-the-web).


# Session Info

```{r sessionInfo}
sessionInfo()
```

# References