Name Mode Size
R 040000
inst 040000
man 040000
tests 040000
vignettes 040000
.Rbuildignore 100644 0 kb
.gitignore 100644 0 kb
.travis.yml 100644 0 kb
DESCRIPTION 100644 2 kb
LICENSE 100644 7 kb
NAMESPACE 100644 1 kb
README.md 100644 5 kb
README.md
<p align="center"> <img src="https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/glimma_des1.png"> </p> [![Build Status](https://travis-ci.org/hasaru-k/GlimmaV2.svg?branch=master)](https://travis-ci.org/hasaru-k/GlimmaV2) [![codecov](https://codecov.io/gh/hasaru-k/GlimmaV2/branch/master/graph/badge.svg)](https://codecov.io/gh/hasaru-k/GlimmaV2) # 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 R markdown - 🖼 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. ## *glimmaMA*: MA plot ![MA plot](https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/maplot.gif "MA Plot") ## *glimmaVolcano*: Volcano plot ![Volcano plot](https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/volcano_plot.gif "Volcano Plot") ## *glimmaMDS*: Multidimensional scaling plot ![MDS plot](https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/MDS_numeric.gif "MDS Plot") ## Installation You can install the development version of GlimmaV2 using devtools from the R command line. ```R devtools::install_github("hasaru-k/GlimmaV2") ``` ## Options ### 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") ``` ### Fixing Expression Y-Axis (MA/Volcano/XY) GlimmaV2 automatically rescales the y-axis of the expression plot depending on which gene is currently selected. This can make it difficult to compare the expression of different genes. In order to fix the y-axis when selecting between multiple genes, you can specify a maximum y-value in the ```max_y_axis``` input form. | Rescaling Axis | Fixed Axis | | ------------- | ------------- | | ![](https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/unfixed_axis.gif "") | ![](https://github.com/hasaru-k/GlimmaV2-docs/blob/master/documentation/fix_axis.gif "") | ### 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.