---
title: "Introduction into R markdown"
author: "Vendula"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(
	echo = FALSE,
	fig.height = 8,
	fig.width = 14,
	message = FALSE,
	warning = FALSE,
	comment = "",
	results = "asis",
	supressMessage = TRUE
	)

library(tidyverse)
```

## Creating an R Markdown file


Each R markddown file contains three types of text:

* An (optional) YAML header surrounded by ---s
* R code chunks surrounded by ```s
* text mixed with simple text formatting

###YAML header

* title: "...."
* author: "...."
* date: "...."
* output: html_document/pdf_document/word_document

     
###Plain text

formating is done using marks  
# Header  
## Header 2  

**bold** with double-asterisks  
_italics_ with underscores  
`code-type` font with backticks  


###Chunk options

write in the bracketes after letter "r" or as general statment e.g. knitr::opts_chunk$set(echo = TRUE) on the beginning

* include = FALSE prevents code and results from appearing in the finished file. R Markdown still runs the code in the chunk, and the results can be used by other chunks.
* echo = FALSE prevents code, but not the results from appearing in the finished file. This is a useful way to embed figures.
* message = FALSE prevents messages that are generated by code from appearing in the finished file.
* warning = FALSE prevents warnings that are generated by code from appearing in the finished.
* fig.cap = "..." adds a caption to graphical results.
* fig.height, fig.width
* results = "markpup" or "asis" or "hide" or "hold"

### Inside chunk
Sometimes is good to have formated text also inside the chunks e.g. when you create the figures or data analysis by loop

* `cat` start for header
* `knitr::kable()` formated table

## Printing the table

```{r table}
df<-read.csv("https://course.img.cas.cz/R/material/Tiverse/mice.csv",  check.names=F, stringsAsFactors = FALSE)
mice_sel<-df[1:5,1:5]
print(knitr::kable(mice_sel))
```

## Plotting the data and save them

```{r graphs }
data_sel2<-df[1:22,c(1:5,38:57)]
data_long3<-data_sel2%>%
  gather(-(ID:cohort), key = "Variable", value = "values")%>%
  separate(col="Variable", into=c("Var", "Time"), sep =-2)%>%
  mutate(Var=str_replace_all(Var,"\\s+$",replacement = "" ))%>%
  spread(key=Var, value = values)
data_long3$Time<-as.numeric(data_long3$Time)


for (i in 7:11){
  data_long3$var<-data_long3[,i]
  p<-ggplot(data=data_long3, aes (x=Time, y=var, color=strain))+geom_smooth(method = "loess")+
  facet_grid(sex~.)+theme_light() +theme(axis.text = element_text(size=12), strip.text = element_text(size=14, color="black"), axis.title=element_text(size=14,face="bold"), legend.text=element_text(size=12))+labs(y=colnames(data_long3)[i], x="Time [min]", title=colnames(data_long3)[i] )
print(p)
ggsave(paste(colnames(data_long3)[i],".jpg"))
}

```


## Tasks

1. Write a sentence containing words with bold, italics, and underlined formatting.
1. Create a  plot generated with 3 inches wide and 5 inches high 
1. test different Chunk options for final document