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Interactive Sequencing Quality Control Reports

We’ve just released a new application on Genestack: the Multiple QC Report!

It allows you to integrate the analysis of multiple quality control reports on large-scale datasets by producing an interactive graph combining data from individual assay reports.

Imagine you’ve just done a high-throughput sequencing experiment (RNA-seq, exome sequencing, ChIP-seq…) with a 100 samples. Now you want to check the quality of the data to see if there’s anything suspicious going on, or to identify outliers. So you produce QC reports. But obviously, you don’t want to go through all of your 100 QC reports one by one and look at all the plots.

That’s why we have the Multiple QC Report! It is a visual analytics app, interactive and pretty easy to use. Say you have a folder with several QC report files. Select all these files in the File Manager, and under the “Explore” menu, click on “Multiple QC Analytics”. Now, click on the dropdown “Select QC keys to display”, pick a few stats and there you go! You get a nice interactive plot with QC stats plotted across all your samples.

The Multiple QC Report app supports both Raw Reads QC reports and Mapped Reads QC reports. It can display all of the main statistics available in both (number of reads, GC content, mapping statistics, etc). Feel free to play around with the app, and let us know what you think! To try it out, just login or register for free to Genestack.

But the coolest thing about this app is that these plots are a powerful data exploration and filtering tool. Here’s what you can do:

Sorting samples

You can sort your samples in the graph by any QC statistic, such as number of mapped reads, or GC content, say. Moreover, if your original Raw Reads file has interesting metadata attributes, e.g., tissue, sex, cell line, age, you can also sort your samples by that value.

For example, let’s say your 100 samples originated from five different cell lines. You can sort your samples by cell line and display the number of reads for each sample to see if there was any systematic difference in the quality of your samples from one cell line to another.

Selecting samples

The plot axis tick labels are interactive! Click any sample name and it will open the usual actions menu on the respective file.

Multiple QC Plotter screenshot

You can also select multiple samples from the graph at once. Just draw a rectangle on the plot over all the samples you’re interested in (selected samples are highlighted in red). Then you can click the button “New folder with selection” to automatically collect the source samples you’ve selected into a single folder. You can then use this filtered data selection for further analysis.

Everything is saved

And as usual, all changes you make to the plot (displayed keys, sorting order, etc.) are automatically saved, you don’t need to worry about losing your work. When you open it again or share it with a colleague, you get to see exactly the same plot! Shared  visualisations can only be modified by their authors; viewers can make their own copies to modify and play with.

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