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Alpha diversity analysis of resistome data in ResistoXplorer

Alpha diversity analysis of resistome data in ResistoXplorer
Hi again. Welcome back to another video. In this video, we will learn how we can perform alpha diversity analysis using Resist Xplorer. By far, we have already seen how we can upload, process, and even visualise our system data using Resist Xplorer. So in this video, we will directly start from the Analysis Panel page. Just to let you know, here I’m using the pig and [INAUDIBLE] example data set. So if you wanted to do alpha diversity analysis, we simply have to click the third button present under the Composition Profiling section, which will bring us to the main page of alpha diversity analysis.
As you can see at the top panel, we have various drop downs which enable us to explore different diversity measures or even allow us to choose at which functional profile level we wanted to perform alpha diversity analysis. By default, alpha diversity analysis is performed using Chao1 measure. And the significant difference between groups based on the selected experimental factor here, for example, via species is evaluated using parametric tests. The result of parametric test is present here. Also we can choose to perform non-parametric test. While in the bottom half of the page, we have two graphical summaries of the results. On the left, we can see a dot plot representing the diversity measure or value across each sample.
And on the right, we have a box plot summarising the diversity measure across [INAUDIBLE]. From these results, you can see there is a clear difference in the alpha diversity measure between the pig and the [INAUDIBLE] samples. And this difference is statistically significant. Lastly, you can always go to the Download section to download the image and the results in a different format which can be further analysed and edited in softwares like Adobe and Graphpad. So for now, we recommend you to try uploading your own data set or example data set and perform alpha diversity analysis. You can try using different diversity measure, as each one of them reveal different aspects of a system composition.
Also you can try and performing diversity analysis at higher functional level just to check whether the same pattern exists at those level also. But that’s it for this video. Hope you enjoyed it. We’ll see you very soon. Bye bye, and take care.

In this video, you will learn how to perform and infer results from alpha diversity analysis on resistome data in ResistoXplorer. Based on it, you need to complete the exercise present below.


Go to the ResistoXplorer and upload your own data or use an example dataset, such as the ‘Pig and Broiler’, in ARG table module and complete the data filtration and normalization step. Do not remove any features from data by dragging all the sliders to the left during the Data Filtration step. Once you reached the Analysis Panel page, you can see the “Alpha diversity analysis” module under Composition profiling section. Click on it and view the diversity within samples using different measures and at different functional levels. Based on it, try to answer these questions:

  • Which group or sample in your data shows the highest ARG richness?
  • Which index will you use if you have too many low abundant features (ARGs) present in your sample? Why?
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