Closed ccoltharp-Akoya closed 4 years ago
That's a good idea. I didn't want to include all the columns from the cell seg data but including the columns needed for the phenotypes makes a lot of sense. If I copy the original column then the same expression can be used in the spatial map viewer.
Yep - that would work for me!
Regarding your tangent -- agreed, the column names for the expression-based phenotypes are awkward. A couple of options:
`
and ~
, so your column would become Membrane PD1 (Opal 650) Mean>15.2 within 25
and the spatial maps selector would be ~`Membrane PD1 (Opal 650) Mean>15.2 within 25`>0
~
and change `
to "
, so your column would become "Membrane PD1 (Opal 650) Mean">15.2 within 25
and the spatial maps selector would be ~`"Membrane PD1 (Opal 650) Mean">15.2 within 25`>0
I prefer the first option, I don't think the "
is needed and it adds noise. What do you think?
Agree - the first option is fine with me.
We're missing a couple columns in 'count_within.txt' that we'd like to use for making a spatial plot using the Spatial Map Viewer. Our goal was to plot two phenotypes, but only those cells that are within 25 microns of the opposite phenotype. This would be pretty easy to do with the count_within.txt file if we had 'normal' phenotypes, but we were using two expression-based phenotypes (e.g. using
Membrane PD1 (Opal 650) Mean
>15.2 for PD1+). In the count_within.txt, we do see the proximity columns for how many PD1+ cells are near each cell. But, we can't tell the PD1 phenotype of each cell. The only phenotype columns listed are those where the column name starts with "Phenotype". Looks like 'nearest_neighbors.txt' is the same way.If we input expression-based phenotypes to the Analysis app, could those phenotype columns be added to count_within.txt and nearest_neighbors.txt?
(slight tangent -- the expression we needed in order to plot the cells with a close-by PD1+ cell is ugly:
~`~\`Membrane PD1 (Opal 650) Mean\`>15.2 within 25`>0)