Differential Expression Analysis Toolbox
Differential gene expression analysis has become an increasingly popular tool in determining and viewing up and/or down experssed genes between two sets of samples. The goal of Differential gene expression analysis is to find genes or transcripts whose difference in expression, when accounting for the variance within condition, is higher than expected by chance. DESeq2 https://bioconductor.org/packages/release/bioc/html/DESeq2.html is an R package available via Bioconductor and is designed to normalize count data from high-throughput sequencing assays such as RNA-Seq and test for differential expression (Love et al. 2014). With multiple parameters such as padjust values, log fold changes, plot styles, and so on, altering plots created with your DE data can be a hassle as well as time consuming. The Differential Expression Browser uses DESeq2 coupled with shiny to produce real-time changes within your plot queries and allows for interactive browsing of your DESeq results. In addition to DESeq analyzation, DEBrowser also offers a variety of other analyzation plots and tools to help visualize your data even further.
Running these simple command will launch the DEBrowser within your local machine.
library(debrowser)
startDEBrowser()
Once you have the DEBrowser running, a page will load asking to choose a CSV file. In order to run DESeq2, we are going to need gene quantifications for those genes contained in a CSV or TSV format.
IE:
gene transcript exper_rep1 exper_rep2 control_rep1 control_rep2
DQ714826 uc007tfl.1 0.00 0.00 0.00 0.00
DQ551521 uc008bml.1 0.00 0.00 0.00 0.00
AK028549 uc011wpi.1 2.00 1.29 0.00 0.00
You can also view/use the data.tsv located within the data directory as an example. After obtaining and loading in the gene quantifications file, you are then able to select which samples will be selected for your first condition and second condition for differential expression based on the column headers within your data file. Once you've selected your conditions, you are then ready to run DESeq2 to calculate differential expression by clicking on the Run DESeq! button.
After clicking on the Run DESeq! button, DESeq will run, analyzing your data and shiny will output the information obtained from DESeq into an interactive graph format. You will have options to adjudt the padjust value and fold change cut off, as well as selecting a different dataset such as upregulated genes only and changing the type of plot you will be viewing on the left hand side of the screen.
On the right hand side of the screen will be your plots and graphs that shiny has created for you. By hovering over specific plot points, bar graphs will be generated for that specific plot point. You also have the ability to select/highlight specific portions of your graph to be able to zoom in. Making a selection will populate the graph on the right as a graph of your selected original graph.
Additional plots and tables are generated by selecting one of the many tabs at the top of the screen. Additional plots allows you to create an all-to-all plot, a specific type of heatmap, as well as a principal component analysis plot. The GO Term tab allows you access various Gene Ontology databases to create a variety of GO Term plots. The rest of the tabs contain specific tabled information about your DESeq data that you can then search or export for your own personal use. All detected describes all the genes detected while the Up/Down tabs show the up or down regulated genes. The final tab Selected is populated based on your current selection of your graph.
With that, you've now successfully navigated the DEBrowser and are ready to start inserting your own data files and browsing your own experiments. Enjoy the DESeq browser!