Description
I am starting to look into options to analyse a VisiumHD dataset. I am really excited to see that Sopa supports this technology now.
I was testing before the bin2cell
workflow, and something that got my attention is that in that workflow there is a "destriping
" step. I paste its functionality below:
"Visium HD suffers from variable bin sizing. When printing the chips, the 2um bins have some variability in their width/height. Inspecting the total counts per spot reveals a characteristic striped appearance, with some rows/columns capturing visibly fewer transcripts than others.
To overcome this,b2c.destripe()
identifies a user-specified quantile (by default 0.99) of total counts for each row, then divides the counts of the spots in that row by that value. This procedure is then repeated for the columns..obs[adjusted_counts_key]
(by default"n_counts_adjusted"
) is obtained by multiplying the resulting per-spot factor by the global quantile of count totals, and the count matrix is by default rescaled to match it."
This seemed an interesting correction and I was wondering if it would be possible to implement something similar with the SpacialData object used in Sopa?
Activity