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License: MIT License
The dash app currently produces a static html table with some statistics for top 10 brain structure results.
I've looked around the dash forum and found this interactive table component which seems like a great way to display and explore the results.
Down the line this would be helpful to select the brain structures of interest to be displayed in the expression heatmap and other figures.
I'm also wondering if there are other suggestions for how to present this data.
Multiple types of tests should probably be used.
I think the most essential would be testing to make sure the user input is in the format as expected (each gene separated by white space) -- what happens if a user puts in a comma separated list of genes?
Which other tests are essential for ensuring that the results can be trusted?
In the notebook, I show a heatmap of the expression of the geneset in the top 10 brain structure hits using the genometools library which builds on top of plotly.
If it would be great to incorporate a heatmap based off the displayed table output.
It would help from a reproducibility perspective if the data processing could run by pulling the data directly from the Allen Brain API.
There is currently a download_HBA_adult_human_data() function in the make_dataset.py along with the essential Well_Known_File IDs. This hasn't been incorporated yet because the donor information wasn't tracked in the same way as when you download the data directly from the Allen website.
Currently, this works with the 6 adult human brains from the Allen Human Brain Atlas. Other datasets to be included are
Examples analyses can be shown in the Jupyter Notebook. This will also provide more context for future steps for the Dash application which should incorporate a selection button so that the analysis is run on a specific dataset.
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