Error with FindConservedMarkers()
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6 weeks ago
Chris ▴ 70

I try to run FindConservedMarkers() but I got this message:

Warning: Identity: 8 not present in group B. Skipping VVWarning: Identity: 8 not present in group A. Skipping NCError in marker.test[[i]] : subscript out of bounds.

This error appears in many clusters I chose. Would you have a suggestion? Thank you so much!

FindConservedMarkers • 730 views
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What is the actual line of code your are running? Your function parentheses are empty.

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Hi @seidel. I run this one:

markers_cluster_8 <- FindConservedMarkers(CV.harmony,
ident.1 = 8,
grouping.var = 'condition')

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Have you checked to make sure that you have cells from each condition in each cluster?

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Sorry if this is a basic question but how can I check that? I would like to perform pseudo-bulk RNA-Seq but I still struggle to get the count matrix. My seurat objects haven't had sample column and also cell-type annotated yet. Admins on this site are highly experienced so how can my questions get their attention? I could not tag any admins, right?

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Admins are just people who've answered lots of questions and gaze over questions that may interest them and that they may know the answer to. You have their attention. Often people don't know the answer directly, so much as they know they can figure it out, but they need the pressure of an impending deadline to come here and seek distraction by solving puzzles for relief. :)

Did you create your Seurat objects, or were they handed to you from an unknown source? If you're following some workflow such as one of the Seurat Tutorials, you can access the metadata.table associated with your cells. For instance:

# what meta data do I have?
colnames(immune.combined@meta.data)
[1] "orig.ident"             "nCount_RNA"             "nFeature_RNA"           "stim"
[5] "integrated_snn_res.0.5" "seurat_clusters"

# how many cells are in each cluster?
table(immune.combined@meta.data$integrated_snn_res.0.5) 0 1 2 3 4 5 6 7 8 9 10 11 12 13 4339 2587 1682 1048 976 815 631 619 486 392 181 108 82 53 # what are my conditions? table(immune.combined@meta.data$stim)

CTRL STIM
6548 7451

# how many cells of each type are in cluster 8?
table(immune.combined@meta.data$stim[immune.combined@meta.data$integrated_snn_res.0.5 == 8])

CTRL STIM
263  223

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Thank you for the info! I created my own seurat object from features.tsv.gz, barcode.tsv.gz, and matrix.mtx.gz. And unlike the sample data which is well-annotated cell type, my seurat object is like this

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I can get the info as you wrote above 🙂. However my data is not balance for each condition: 17900 vs 5579.

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Balance may or may not matter. Sometimes people sample down (randomly select 5579 cells from the 17900 data set) to match. However, this means you have two seurat objects, correct? And you are trying to integrate them and find conserved markers, right? Have you successfully integrated them to a single object? And if so, do you have cell counts per condition?

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Thank you for following up on my question. Yes, 2 seurat objects. I tried to find conserved markers. For a reason, I used merge function to integrate into a single object. Cell counts per condition are 17900 vs 5579.

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Could other admins have a look?