GenoBrew: Interactive Marker Panel Evaluation, CNV Visualization and Curation

A user-friendly Shiny application for genomic variant analysis with two main modules. The Marker Selection module evaluates VCF files against marker panel information, visualizing marker distribution across the genome with filtering options for minor allele frequency (MAF), read depth, missing data, repeated regions, and copy number differences from expected ploidy. The CNV Profiles module enables interactive visualization of copy number variation patterns by sample

Cris Taniguti
56 steps
8 minutes

GitHub

Shinyapps

Alert! You can explore GenoBrew features accessing the website, but the page has limited resources, for larger datasets you will need to install the app in our local computer. For that install R and type the commands: [[install.packages("devtools")]] # Sometimes R asks if you want to update libraries, make sure you answer their question [[devtools::install_github("Breeding-Insight/GenoBrew")]] [[GenoBrew::run_app()]]

Getting Started

Navigate to [GenoBrew in shinyapps.io](https://cris-taniguti.shinyapps.io/genobrew/) or deploy it in your local computer

Click "Select Markers" to access the Interactive Marker Panel Evaluation features.

Select Markers on the left hand menu screen highlighted

Click "Browse..." to upload the described input files.

Upload VCF file select button highlighted

Note that some of the input files are optional.

Browse option for other optional files highlighted

Select the ploidy level for your species.

Once all your files are loaded and your selections made, click "Load VCF".

Alternatively, if you just want to explore the app features click on "Load Dataset" to load the built-in alfalfa dataset.

Filtering Your Results

Once the files are evaluated. The app will show the number of markers in the VCF file, in the marker panel file and the ones in common between them in the respective blue, green and purple boxes. You can apply filter considering only the Common Markers or all the markers in the VCF file.

Click the "Min MAF (higher = fewer, more informative markers)" field to adjust your MAF threshold.

Double-click the "Max % Missing (lower = less missing data allowed)" field to adjust your missing data threshold. Do the same for the other filter options.

Max % Missing options selector highlighted

Adjust the ranges by dragging the edges.

If you uploaded the \_*by*\_window.csv.gz Qploidy file, you are also able to filter by Max % CNV different than defined ploidy. If you uploaded the repeated regions file, you will be able to filter by markers present or not in these regions.

Max % CNV does not equal defined ploidy box highlighted

You can select specific samples by expanding the samples list.

Samples included selection box highlighted

You can type the name of the samples you are looking for and select them. Make sure the ones you want to keep received a "check sign" in the right side.

Name of sample file selected and highlighted

Once you are done with the filter thresholds adjustments click "Apply Filters".

This will generate an interactive plot in the box below.

Marker Distribution interactive plot screenshot with the plot area as the main visual.

You can color the markers by different variables.

Choose your colour by parameters. (Shown here is the "missing" parameter.)

Color parameters drop down menu highlighted

Hovering the mouse through the graphic you can see all the metrics by marker.

You can click "CNV (samples != ploidy)" if you uploaded the Qploidy file.

CNV (samples != ploidy) option in Color parameter menu highlighted

Note that here is an example of resulted image for the CNV (samples !=ploidy).

Click "Save" to download the figure.

You can choose different formats and dimensions.

Different options within the Save Marker Distribution

Click in the "plus icon" in the right side to visualize the metrics table.

Plus icon to display metrics table highlighted

The interactive visualization allow you to search specific markers and values in the entire table.

Click "Save Table (.csv)" to download the full table.

Click "Save Filtered VCF (.vcf.gz)" to download the processed VCF considering the filter applied.

Save Filtered VCF (.vcf.gz) button highlighted

CNV Visualization and Curation

Now, let's explore the features for CNV visualization and curation. Click "CNV profiles".

CNV profiles on the left hand menu highlighted

Click "Browse..." to load the required files from Qploidy results.

File browse option under HMM results by marker highlighted

Click "Load Files" for the files to be evaluated.

Alternatively, Click "Load Dataset" to explore the app features using the built-in dataset.

Click "185 of 185 samples selected" to select specific samples to be visualized. You can also select whole families by accessing the By Family tab.

Search and select the samples you want to keep. Make sure they receive a "check sign" in the right side.

Click the "Gray color CN" field to define which ploidy should receive the gray color. Our suggestion is to include the most common copy number in your dataset.

Click "Build Plot".

GenoBrew generates an interactive plot. Your can hover your mouse through the cells to obtain sample and marker information. You can also click and drag to zoom in.

If you click on the row of a specific sample. The next box plot will be updated for its specific sample.

A specific row inside the screenshot of the plot is highlighted and extra details appear.

You can also select a sample by searching its name in the list below the graphic.

Adjust the plot options according to your interests.

Check to see if the graphic is referring to the correct sample you are hoping to evaluate.

Graph details highlighted in order for user to check if this is the one they want to use.

If you want to select another sample for evaluation. Click in the "home sign" in the top right to reset the graphic dimensions.

You can then zoom in another spot to inspect the data more closely.

A specific location in the plot is highlighted

Note that this sample has a different pattern compared to the rest.

Checking the detailed plot for this sample we see it was estimated as CNV 5 and the distributions is slightly different than the others indicating more noise in the markers.

Click in the "plus sign" in the right side if you want to adjust Qploidy parameters and re-run this sample.

Qploidy parameter adjustment tool plus sign highlighted

Click "Browse..." to upload the Qploidy standardization file.

Adjust the parameters as required.

Click "Run analysis".

The plot will update automatically. Evaluate if the new CNV profile makes more sense for your context.

If you get the conclusion that the results doesn't make sense doesn't matter the combination of parameters, you may want to remove the sample from your dataset. For this, choose TRUE at "Remove sample from analysis". If changing the parameters solved the problem, keep if "FALSE".

Remove samples from analysis option and choices highlighted

Click "Update full results" to update your initial Qploidy files.

Click "Build Plot" to visualize the updated set.

The updated samples will be at the top of the graphic.

Zoom in to view the data more closely.

Zoomed in version of previous screenshot

Yep! Updated!

Specific section on plot highlighted to show updated information

Click "Download HMM Files" to download the updated Qploidy files.

Congrats! You have finished this tutorial for GenoBrew. If you have more questions or concerns, please reach out to Cris Taniguti at [ctaniguti@ufl.edu](mailto:ctaniguti@ufl.edu).