README.Rmd

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output: github_document
---

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knitr::opts_chunk$set(
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# ggGWAS


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An R-Package (*work-in-progress*) that contains ggplot2-extensions of data visualisations used with GWAS data. 

Mainly, these are Q-Q plot and Manhattan plot that both use P-values from GWASs as input. 

An inspiration for ggGWAS has been the R-package [qqman](http://www.gettinggeneticsdone.com/2014/05/qqman-r-package-for-qq-and-manhattan-plots-for-gwas-results.html), except that ggGWAS aims to have the look and functionality of `ggplot2`.

## Installation

You can install the development version from [GitHub](https://github.com/) with:


```r
# install.packages("remotes")
remotes::install_github("sinarueeger/ggGWAS")
```

Install the `dev`b ranch:
```r
remotes::install_github("sinarueeger/ggGWAS", ref = "dev")
```


Install including vignettes: 

```r
remotes::install_github("sinarueeger/ggGWAS", build = TRUE, build_opts = c("--no-resave-data", "--no-manual"))
vignette("gggwas-reasoning")
vignette("gggwas-internals")
```


## Basic usage

```{r data}
library(ggGWAS)
library(ggplot2)

theme_set(theme_bw())
## Generate some random data
n <- 1000
n_chr <- 4

df <-
  data.frame(
    POS = rep(1:(n/n_chr), n_chr),
    CHR = rep(1:n_chr, rep(n/n_chr, n_chr)),
    SNP = paste0("rs", 1:n),
    P = runif(n),
    GWAS = sample(c("a", "b"), n, replace = TRUE)
  )

```



### Q-Q plot

Lightweight Q-Q plot (with hex tiles)

```{r qqplot-hex, fig.width = 6, fig.height = 6}
library(ggGWAS)
ggplot(data = df) + 
  stat_gwas_qq_hex(aes(y = P)) + 
  geom_abline(intercept = 0, slope = 1, linetype = 3)

?stat_gwas_qq_hex ## for more examples
```

Conventional Q-Q plot
```{r qqplot, fig.width = 6, fig.height = 6}
ggplot(data = df) +
  stat_gwas_qq(aes(y = P)) + 
  geom_abline(intercept = 0, slope = 1, linetype = 3)

?stat_gwas_qq ## for more examples
```


### Manhattan plot

Currently working on `stat_gwas_manhattan()` that should at one point look like this:

```
ggplot(data = df) + stat_gwas_manhattan(aes(pos = POS, y = -log10(P), chr = CHR))
```

Till then, use the `ggman::ggmanhattan` function:

```{r manhattanplot, message=FALSE, warning=FALSE, fig.width = 6, fig.height = 4}
library(dplyr)
library(ggman)
ggman::ggmanhattan(data = df, SNP = "SNP", chr = "CHR", bp = "POS", P = "P", sparsify = FALSE, theme_base = theme_bw(), build = 'hg18', highlight = df %>% slice(which.min(P)) %>% pull(SNP)) +
  labs(title = "MHTPLOT" )
```

##Contributing
 lease note that the 'ggGWAS' project is released with a
[Contributor Code of Conduct](CODE_OF_CONDUCT.md).
By contributing to this project, you agree to abide by its terms.