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Can t use the plotSasRidgeplot() function #208

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wuxiangning opened this issue Dec 16, 2024 · 2 comments
Open

Can t use the plotSasRidgeplot() function #208

wuxiangning opened this issue Dec 16, 2024 · 2 comments

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@wuxiangning
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Hello! Recently when i use plotSasRidgeplot to draw something, the strange error happened.But the plotSasLineplot() still work.I dont know how to solve it.Help!
Thanks!
My code is:

ids <- getSpatAnnIds(object, ids = c("spat_ann_1","spat_ann_2","spat_ann_3"))
plotSasLineplot(object, ids = ids, variables = c("VEGFA", "HM_HYPOXIA", "RCTM_TCR_SIGNALING", "CD74")) +

  • labs(x = "Distance to Necrosis")

visualize with ridgeplots

plotSasRidgeplot(object, ids = ids, variables = c("VEGFA", "HM_HYPOXIA", "RCTM_TCR_SIGNALING", "CD74")) +

  • labs(x = "Distance to Necrosis")
    Error in map():
    ℹ In index: 1.
    Caused by error:
    ! 缺少参数"..5",也缺失默认值
    Run rlang::last_trace() to see where the error occurred.
@kueckelj
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Collaborator

Can you provide a translation for the error message in English please?

@wuxiangning
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Author

Hi, I reran the code and found that it now works for generating the plots. However, some files still produce this kind of warning. Could you please explain why?
Additionally, I sent another question that I'm quite confused about to your email: I would like to know if it is possible to automatically define points with a score for a certain gene set or gene that is greater than the average value across the entire section as "high" points, and then assign them to the annotations so that I can perform neighborhood analysis?
I hope you can reply when you have time.
Thank you!

plotSasRidgeplot(object, ids = Angio_Transition_ids, variables = c("VEGFA", "HM_HYPOXIA", "RCTM_TCR_SIGNALING", "SPP1")) +

  • labs(x = "Distance to Necrosis")
    Warning messages:
    1: In sqrt(sum.squares/one.delta) : NaNs produced
    2: In sqrt(sum.squares/one.delta) : NaNs produced
    3: In sqrt(sum.squares/one.delta) : NaNs produced
    4: In sqrt(sum.squares/one.delta) : NaNs produced
    5: In sqrt(sum.squares/one.delta) : NaNs produced
    6: In sqrt(sum.squares/one.delta) : NaNs produced
    7: In sqrt(sum.squares/one.delta) : NaNs produced
    8: In sqrt(sum.squares/one.delta) : NaNs produced

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