In shijianasdf/BasicBioinformaticsAnalysisFromZhongShan: Launch Usual Clinical tool for Kind Yield

knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

Introduction

Medicine researchers are always disturbed by how to draw a publish-level plot for their medical project.Package lucky is a assembly functions of my own in daily use.It contains several critical modules as following.

• Fast way to get plot of ggplot2 style
• Fast way to do analysis for GEO database
• Fast way to make bioinformatic analysis

The theory of lucky package

Name rule

Lower Camel Case is the most usual name rule in R programing.However,I plan to use Upper Camel Case,which is also another good choice but make lucky functions easier to be searched.It looks like FastBar,FastExtra and so on.

Lucky structure

A good output of a standard publish-level object(including plot) should have these features:

• outstanding visulization
• individual environment for repetition
• powerful debugger
• easy function expansion

parameters

• save.file whether to save file in present work space.
• names part of the names of saved filed.If you set names like lucky,the name of output file would looks like lucky_barplot.pdf

design

This is defined by parameter repeat and output as an element of list It is supported by LuckyDebug function as a S4 method repeat the present parameters data the important data of this function plot the plot of the

Fast-Plot series

FastBar

see also

library(lucky)
library(ggpubr)
# Data
df <- data.frame(dose=c("D0.5", "D1", "D2"),
                 len=c(4.2, 10, 29.5))
print(df)

FastBar is based on ggpubr::ggboxplot.

# draw a barplot
FastBar(data = df,
        x = "dose",y = "len",
        fill = "dose",
        title = "Test_lucky::FastBar",
        legend.position = "right",
        size = 10)

# white fill
FastBar(data = df,
        x = "dose",y = "len",
        fill = "white", 
        title = "Test_lucky::FastBar",
        legend.position = "right",
        size = 10)

# no legend
FastBar(data = df,
        x = "dose",y = "len",
        fill = "white",
        title = "Test_lucky::FastBar",
        legend.position = "none",#with no legend
        size = 10)

## larger size
FastBar(data = df,
        x = "dose",y = "len",
        fill = "white",
        title = "Test_lucky::FastBar",
        legend.position = "none",#with no legend
        size = 15)

Example

Vignettes are long form documentation commonly included in packages. Because they are part of the distribution of the package, they need to be as compact as possible. The html_vignette output type provides a custom style sheet (and tweaks some options) to ensure that the resulting html is as small as possible. The html_vignette format:

• Never uses retina figures
• Has a smaller default figure size
• Uses a custom CSS stylesheet instead of the default Twitter Bootstrap style

Vignette Info

Note the various macros within the vignette section of the metadata block above. These are required in order to instruct R how to build the vignette. Note that you should change the title field and the \VignetteIndexEntry to match the title of your vignette.

Styles

The html_vignette template includes a basic CSS theme. To override this theme you can specify your own CSS in the document metadata as follows:

output: 
  rmarkdown::html_vignette:
    css: mystyles.css

Figures

The figure sizes have been customised so that you can easily put two images side-by-side.

plot(1:10)
plot(10:1)

You can enable figure captions by fig_caption: yes in YAML:

output:
  rmarkdown::html_vignette:
    fig_caption: yes

Then you can use the chunk option fig.cap = "Your figure caption." in knitr.

More Examples

You can write math expressions, e.g. $Y = X\beta + \epsilon$, footnotes^[A footnote here.], and tables, e.g. using knitr::kable().

knitr::kable(head(mtcars, 10))

Also a quote using >:

"He who gives up [code] safety for [code] speed deserves neither." (via)

shijianasdf/BasicBioinformaticsAnalysisFromZhongShan documentation built on Jan. 3, 2020, 10:08 p.m.