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#
Glimma 2.0 is an interactive R widget for creating plots for differential expression analysis, created using the [Vega](https://vega.github.io/vega/) and [htmlwidgets](https://www.htmlwidgets.org/) frameworks. It's an update/reimplementation of [Glimma 1.0](https://github.com/Shians/Glimma)! New features include:
- 🧬 multiple gene selections
- 📓 full integration with Quarto and R markdown
- 🎨 support for interactive switching between contrasts in limma-style objects
- 🖼 exporting plots to PNG/SVG/CSV formats
#### Available on [Bioconductor](https://bioconductor.org/packages/release/bioc/html/Glimma.html).
Feedback is welcome, please feel free to open an issue for any enhancements you would like to see in future.
| Function | Example |
| ------------- | ------------- |
| **glimmaMA**: _MA plot_ | <img src="https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/MA.gif" /> |
| **glimmaVolcano**: _Volcano plot_ | <img src="https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/volcano.gif"/> |
| **glimmaMDS**: _Multidimensional scaling plot_ | <img src="https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/MDS.png"/> |
## Installation
You can install the development version of GlimmaV2 using devtools from the R command line.
```R
devtools::install_github("mritchielab/GlimmaV2")
```
## Features
### Multiple contrast selection
You now can interactively switch between multiple contrasts within _limma_ style objects:
<img src="https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/contrasts.gif" width="600px"/>
### Expression plot controls
| Y-axis | Jitter |
| ------------- | ------------- |
| You can **fix** the **y-axis** when switching between genes by specifying ```Y min``` and ```Y max``` values: <img src="https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/axis.gif"/> | Jitter can be interactively applied when samples are overlying each other: <img src="https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/jitter.gif"/> |
### Plot Colouring (MA/Volcano/XY)
The default mapping between the status vector and color of the gene is given below:
```
-1 (downreg) => blue
0 (not DE) => silver
1 (upreg) => red
```
Accordingly, the default status.colours argument is ```c("dodgerblue", "silver", "firebrick")```. If no status vector is provided, all genes are given a status value of 0. The colour mapping can be changed by varying the status.colours argument which must be a vector of three valid CSS strings (for example: ```#f304d3```, ```#fff```, ```rgb(253, 12, 134)```, ```steelblue```):
```R
glimmaMA(fit, dge=rnaseq, status.colours=c("#3977db","#3d3f42","#db0d4e"))
```
```R
glimmaVolcano(fit, dge=rnaseq, status.colours=c("blue", "darkgrey", "red"))
```
```R
glimmaXY(x=fit$coef, y=fit$lod, dge=rnaseq, status=dtFit, status.colours=c("cyan", "grey", "hotpink"))
```
### Gene Symbol Text (MA/Volcano/XY)
Gene symbol text will be displayed above selected points if there is a ```symbol``` column (case-insensitive) within the gene annotation supplied as per the example plots shown above. The gene annotation is the ```anno``` argument.
- for the glimmaVolcano and glimmaMA functions, ```anno``` defaults to ```x$genes``` for DGELRT/DGEExact and MArrayLM objects and defaults to ```NULL``` for DESeqDataSet objects - see ```?glimmaMA```, ```?glimmaVolcano``` for further detail
- for glimmaXY, ```anno``` is always ```NULL``` by default
### MDS Options
The ```scale_by``` dropdown menu contains *numeric* features provided the ```groups``` dataframe, while the ```shape_by``` dropdown contains *discrete* features provided by the ```groups``` dataframe. The ```colour_by``` dropdown contains discrete features by default but can be altered to take numeric features such as library size by setting ```continuous.colour=TRUE```:
```R
glimmaMDS(rnaseq, groups=groups, continuous.colour=TRUE)
```
The test used to distinguish numeric vs discrete features in the groups dataframe is ```sapply(groups, is.numeric)```, so the appropriate coercions can be used toggle ambiguous features between numeric/discrete.
### Exporting Standalone HTML
Specifying a filename using the ```html``` argument (*including the extension*) in any of the GlimmaV2 functions will export the widget to a standalone single HTML file, rather than displaying/returning the widget in R Markdown.
```R
glimmaMA(fit, dge=rnaseq, html="MA_plot.html")
```
If more flexibility is required (ex. varying the background colour, whether or not the file should be standalone), the user can call ```htmlwidgets::saveWidget()``` on instantiated widgets which has [further options](https://rdrr.io/cran/htmlwidgets/man/saveWidget.html).
```R
glMA <- glimmaMA(fit, dge=rnaseq)
htmlwidgets::saveWidget(glMA, file="glimmaV2Example.html")
```
### Sizing
The width and height parameters can be adjusted to change the dimensions of the widget in pixels in the RStudio viewer and in knitted HTML:
```R
glimmaMA(fit, dge=rnaseq, width=1200, height=1200)
```
All GlimmaV2 functions take optional width/height arguments. The default glimmaMA/glimmaXY width and height are both 920px, so they should be modified in a 1:1 ratio if preserving the original scale is desired.
