Identifying differentially abundant antimicrobial resistance genes in resistome data using ResistoXplorer

Welcome back to another video. In this video, we will learn how we can perform statistical testing using various methods to identify differentially abundant antimicrobial resistant genes between [INAUDIBLE] using Resist Xplorer. So in order to do that, we have to go to the Resist Xplorer. And here, as you can, see the main analysis page. We have already learned from the previous video on how to reach to this page. For demonstration purpose, I have uploaded and process the [INAUDIBLE] example data set using default parameters. So as we see here that we have a separate section named Differentially Abundance Testing under which we have several buttons or we can say modules. Each button we present one method of identifying or performing statistical testing.

So the EdgeR and DESeq are present under only one module called RNA-seq method. So let’s click on one of these in order to go to the main analysis page. This might be a bit time consuming as compared to another analysis, but probably soon we can reach to the main page of it. As you can see on the top of the page, we have various parameters. For example, function provide level, algorithm, or adjusted p-value that one can choose from. Additionally, user can also select different experimental factor of interest that he or she wants the analysis to be performed at. While in the bottom half of the page, we have the result table for the analysis.

Here the features are ranked by their adjusted p-value and the features which are below the predefined cutoff are highlighted in orange. Additionally, you can always go to the last column and click on the Detail button in order to view the box plot summary of specific features or resistant gene. Last but not the least, you can always go to the Result Table button and download the result in CSV format. So this is one of the analysis. But all the differentially analysis method follow the same layout in Resist Xplorer. So just in order to check that, let’s go to the Analysis page again. And let’s say click on another method called ALDEx2. This might take some time to load.

But yeah, as you can see, this page is very similar to what we have seen for RNA-seq method. In addition to this, we have a lot of these small tool tips which provide the detailed explanation of parameters which are unique to that specific analysis. Last but not least, we recommend you to try different statistical method on your own data or any example data set present in Resist Xplorer. We recommend you to use multiple method consensus based approach in order to make robust biological interpretation from your own data. That’s it for this video. Hope you learned something new and enjoyed this video. Till then, bye bye, and take care.