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No new tutorial updated? #169

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LiuCanidk opened this issue Dec 27, 2024 · 1 comment
Open

No new tutorial updated? #169

LiuCanidk opened this issue Dec 27, 2024 · 1 comment

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@LiuCanidk
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LiuCanidk commented Dec 27, 2024

Hi, thanks for developing this nice tool

I am currently working with it on my own data but found it confusing with some new functions updated in version 2 but not updated in the tutorial, something like DSS, functions like bcRecompute, bcRegressout, which I found in the issue mentioned by others.

For example, I do not know what metadata column should be placed into the parameter vars.to.regress. I also do not know when to use bcRegressout (I searched all the issue if I did not miss something important). Also, when should I use PSc or when should I use SSc. Different results were obtained after I tried both. I think these details are important for us users to interpret the results correctly and conclude the right biological meaning. Maybe the tutorial need to be updated.

The code I used after I refer to the issues opened by others is below:

bc=bcScore(seu, gs, expr.thres = 0.1)
bc=bcRegressOut(bc, vars.to.regress = c('nFeature_SCT','S.Score','G2M.Score'))
bc=bcRanks(bc, 'seurat_clusters')
bc=bcRanks(bc, 'orig.ident')
saveRDS(bc, file='beyondcell_res_sensitivity.rds')
bc4Squares(bc, idents = "seurat_clusters", top = 3)
ggsave('beyondcell_cluster_drug_sensitivity.pdf', width=24, height=15)
#seu is the seurat object

Is there anything wrong or my process is OK?

Any discussion or suggestions would be greatly appreciated
Thanks in advance

@LiuCanidk
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In fact, not using bcRegressOut produce extreme results:
image
many drugs' switching points are 0 and 1

After I ran bcRegressOut, results seemed more normal, which was like the result in the tutorial:
image
although there were still some 0 switching points. By the way, my sample of single cell expression were some different cell strains after artificial selection under nutrient deprivation

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