Visualizing 'omic feature rankings and log-ratios with q2-qurro

Visualizing 'omic feature rankings and log-ratios with q2-qurro

Hi everyone! We recently put together a new visualization tool that can be used through QIIME 2 named Qurro. A paper was just published on the tool last week here.

What does this tool do?

Long story short, this tool provides an interface that should make it easier to interpret measures of feature-wise variation (e.g. estimated log-fold changes across sample types; loadings in a biplot) alongside log-ratios of selected features, which you can then relate back to your sample metadata. We initially designed it to make doing the sorts of analyses suggested in Morton/Marotz et al. 2019 easier.

What plugins’ outputs can I use with Qurro?

Qurro can visualize the outputs of various QIIME 2 (community) plugins, including but not limited to DEICODE, ALDEx2, and Songbird. The interpretation will of course differ somewhat depending on where the “feature rankings” you’re using come from, but the tool’s interface works pretty well with all of these tools’ outputs. (You can also use Qurro outside of QIIME 2, which is shown in a few of the tutorials mentioned above.)

Installing Qurro

See the installation instructions here. You can install Qurro through either pip or conda—in either case installation should be straightforward if you already have a QIIME 2 conda environment set up.

We just released a new version of Qurro (v0.7.0) yesterday, so even if you’ve used Qurro before you may want to update the version you have installed.

Tutorials

Tutorials are available in Qurro’s README here. Any of the first three tutorials listed (color composition, moving pictures, transcriptomics) should be a good place to start out; for QIIME 2 users I recommend starting with the moving pictures tutorial, which uses Qurro through QIIME 2.

In closing

We hope you find Qurro useful! Feel free to ask questions in the Community Plugin Support section, and I’ll do my best to answer them.

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