Q: How to render xenium morphology image with original colors?

Abierto
#370 15 comentarios 0 reacciones 0 asignados Ver en GitHub

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Evaluación

Dificultad
4/5
Tiempo estimado
3-5 días
Aptitud para principiantes
25/100
Tipo de issue
Error
Claridad
Necesita aclaración
Estado de actividad
Estancado
Stack tecnológico
python

Línea de trabajo

Start with the render_images call on morphology_focus and trace how its color arguments affect the plotted image. Compare the rendered colors with the Xenium Explorer reference values, and separately inspect how bounding_box_query uses the global coordinate system for the supplied physical coordinates. Done means the color behavior and coordinate conversion are documented or corrected with a reproducible example.

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Descripción

images :framed_picture: needs info priority: low

Hello @LucaMarconato!

Thank you very much for this tool. I want to plot a part of morphology image acquired with xenium + multimodal segmentation kit. It is loaded into spatialdata and plotted without errors, but the colors are dim and they are different from what I'd expected (DAPI - #0F73E6, Boundary - #F300A5, Interior RNA - #A4A400, interior protein - #008A00, reference values from Xenium Explorer). I tried passing a list of colors like this:

crop = lambda sdata: spatialdata.bounding_box_query(
    sdata,
    min_coordinate=[17_500, 55_000],
    max_coordinate=[19_500, 57_000],
    axes=("x", "y"),
    target_coordinate_system="global",
)

crop(sdata).pl.render_images("morphology_focus", ["#0F73E6", "#F300A5", "#A4A400", "#008A00"]).pl.show(
    ax=axes[0], title="Morphology image", coordinate_systems="global"
)

The code does not produce an error, it works twice as long, and it results in the same image with colors unchanged.

The key question is how to adjust the colors and saturation of the plot, so that it looked closer to what I see in Xenium Explorer?

Secondary question is how to translate physical coordinates into spatialdata's global coordinate system? Am I supposed to get transformation and then apply transformation to a single or a couple points to get min and max for cropping above? I can make a separate issue with this question, if necessary.

Best,
Vasily

Lenguaje dominante
Python
Estrellas
86
Forks
21
Merge medio
14 h 50 min
PR fusionados (30 d)
3

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