Open daxianghuibian opened 3 years ago
@daxianghuibian Can you show me your data in object@data.project
and object@data.signaling
str(cellchat@data.signaling) Formal class 'dgCMatrix' [package "Matrix"] with 6 slots ..@ i : int [1:1197638] 0 23 30 43 47 53 72 77 81 85 ... ..@ p : int [1:2815] 0 329 721 1094 1512 1895 2439 2941 3309 3767 ... ..@ Dim : int [1:2] 3000 2814 ..@ Dimnames:List of 2 .. ..$ : chr [1:3000] "Rb1cc1" "Mybl1" "Gsta3" "Gm28836" ... .. ..$ : chr [1:2814] "AAACCTGAGCGCTCCA-1_1" "AAACCTGAGTATCGAA-1_1" "AAACCTGCAACGCACC-1_1" "AAACCTGCAGCATGAG-1_1" ... ..@ x : num [1:1197638] 1.79 2.3 1.1 1.79 1.1 ... ..@ factors : list() str(cellchat@data.project) num [1:3000, 1:2814] 1.79 0 0 0 0 ...
- attr(*, "dimnames")=List of 2 ..$ : chr [1:3000] "Rb1cc1" "Mybl1" "Gsta3" "Gm28836" ... ..$ : chr [1:2814] "AAACCTGAGCGCTCCA-1_1" "AAACCTGAGTATCGAA-1_1" "AAACCTGCAACGCACC-1_1" "AAACCTGCAGCATGAG-1_1" ...
cellchat <- computeCommunProb(cellchat) Error in data.use[RsubunitsV, ] : subscript out of bounds
I have checked everything mentioned listed in issue #111, still got similar error message
@zpingfeng It looks like the genes in the @data.signaling is not the signaling genes. e.g., "Rb1cc1" "Mybl1" "Gsta3" "Gm28836" ... You cannot use the HVGs
Thanks for your beautiful work! I can only have results of “Secreted Signalling” from one sample and “Cell-Cell Contact” from another sample. Is this an issue from my data or have I done something incorrectly?
Hi,
I am having a bid diffrent problem please see below.
cellchat <- computeCommunProb(cellchat,raw.use = F,population.size = T)
triMean is used for calculating the average gene expression per cell group.
Error in computeCommunProb(cellchat, raw.use = F, population.size = T) :
Please check `unique(object@idents)` and ensure that the factor levels are correct!
You may need to drop unused levels using 'droplevels' function. e.g.,
`meta$labels = droplevels(meta$labels, exclude = setdiff(levels(meta$labels),unique(meta$labels)))`
I am not sure why I have <NA> in my dataset. This was appeared right after i run the
`
cellchat <- computeCommunProb(cellchat,raw.use = F,population.size = T)
`> unique(cellchat@idents)
[1] Cd4 Treg B cell Nk cell Myeloid
[5] CD4 T cell CD8 T cell RB_unknown CD4 naive
[9] Macrophage pDC Mast cell Fibroblasts
[13] Epithelial 4T1 epithelial <NA> EMT6 myofibroblast
[17] Neutrophils
16 Levels: 4T1 epithelial B cell CD4 T cell CD4 naive CD8 T cell Cd4 Treg ... pDC
Then I run this but still having error
meta$Cell_type = droplevels(meta$Cell_type, exclude = setdiff(levels(meta$Cell_type),unique(meta$Cell_type)))
Really appriciate your helps
@DRSEI When you see unique(cellchat@idents)
, you should check and correct your input cell label vector.
@sqjin I checked and my cell labell was correct when i load my file Please see below
levels(cellchat@idents) # show factor levels of the cell labels [1] "4T1 epithelial" "B cell" "CD4 T cell" "CD4 naive" [5] "CD8 T cell" "Cd4 Treg" "EMT6 myofibroblast" "Epithelial" [9] "Fibroblasts" "Macrophage" "Mast cell" "Myeloid" [13] "Neutrophils" "Nk cell" "RB_unknown" "pDC"
unique(meta$Cell_type)
[1] Cd4 Treg B cell Nk cell Myeloid
[5] CD4 T cell CD8 T cell RB_unknown CD4 naive
[9] Macrophage pDC Mast cell Fibroblasts
[13] Epithelial 4T1 epithelial <NA> EMT6 myofibroblast
[17] Neutrophils
16 Levels: 4T1 epithelial B cell CD4 T cell CD4 naive CD8 T cell Cd4 Treg ... pDC
But I still don't get why I am getting errors ?
I forget to mention that This dataset converted from the scanpy . based on this link https://htmlpreview.github.io/?https://github.com/sqjin/CellChat/blob/master/tutorial/Interface_with_other_single-cell_analysis_toolkits.html
@DRSEI You should correct your input data. unique(meta$Cell_type)
still contains 'NA'.
@sqjin I managed to removed "NA" but i have New issues which i posted in here https://github.com/sqjin/CellChat/issues/525
cellchat <- computeCommunProb(cellchat,raw.use = F,population.size = T) Error in computeCommunProb(cellchat, raw.use = F, population.size = T) : Please check your input data matrix and ensure that you use the normalized data instead of count data!
sorry, I had used normalized data, and other groups can run successful except this group. All groups data were from one seuratobject.