scverse / scverse/spatialdata-plot

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

未关闭
#370 15 条评论 0 个 reaction 已指派 0 人 在 GitHub 查看

还没有人认领这个 Issue。

images :framed_picture: needs info priority: low
主要语言
Python
星标
86
派生
21
平均合并
14 小时 50 分钟
30 天内合并 PR
3

描述

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

贡献指南

打开贡献指南

从这里开始

  1. 先读完整个 Issue,再读项目的贡献指南。
  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

调研方向

从 morphology_focus 上的 render_images 调用开始,跟踪其颜色参数如何影响绘制的图像。将绘制出的颜色与 Xenium Explorer 的参考值进行比较,并分别检查 bounding_box_query 如何对提供的物理坐标使用全局坐标系。完成的标准是:颜色行为和坐标转换已通过可复现示例记录或修正。

由索引模型根据 Issue 内容生成。

评估

技术栈
python
领域
data-visualization
Issue 类型
缺陷
难度
4/5
预计耗时
3-5 天
活跃度
停滞
描述清晰度
需要澄清
新手友好度
25/100

把新 issue 发到你的邮箱

精选适合新手参与的 GitHub issue 摘要。