Closed anchormok closed 3 years ago
sqjin
commented
3 years ago @anchormok the input data is not correct and it should be the normalized data. data.input <- seob@assays$RNA@data or cellchat <- createCellChat(object = seob, group.by = "celltype")
chi16
commented
3 years ago @sqjin i was also troubled in this problem, and my code was as follows:
data.input <- fl@assays$RNA@data meta <- data.frame(celltype =fl$celltype , row.names = names(fl$celltype)) cellchat2 <- createCellChat(object = data.input, meta = meta, group.by = "celltype") CellChatDB.mouse <- CellChatDB.mouse CellChatDB.use <- subsetDB(CellChatDB.mouse, search = "Secreted Signaling") cellchat2@DB <- CellChatDB.use cellchat2 <- subsetData(cellchat2) future::plan("multiprocess", workers = 4) cellchat2 <- identifyOverExpressedGenes(cellchat2) cellchat2 <- identifyOverExpressedInteractions(cellchat2) cellchat2 <- projectData(cellchat2, PPI.mouse) cellchat2 <- computeCommunProb(cellchat2, raw.use = TRUE)
then 'Error in Prob[, , i] <- Pnull' can you help me? thanks a lot!
sqjin
commented
3 years ago @chi16 The codes look fine. Can you check object@data.signaling and unique(object@idents) to see if they look OK?
chi16
commented
3 years ago @sqjin Got it. The level of idents was wrong. Thanks for your help!
jessicook
commented
3 years ago Hi, I'm having the same issue. I tried the solutions above with no success. The odd thing is, I'm running cellchat on a subset of a seurat object, and the rest of the subsets looks fine. Here is my code:
uw <- subset(om.db, subset = orig.ident == "UW")
cellchat.uw <- createCellChat(object = uw, group.by = "jc_annos")
groupSize <- as.numeric(table(cellchat.uw@idents))
cellchat.uw <- setIdent(cellchat.uw, ident.use = "jc_annos") # set "jc_annos" as default cell identity
levels(cellchat.uw@idents) # show factor levels of the cell labels
groupSize <- as.numeric(table(cellchat.uw@idents)) # number of cells in each cell group
CellChatDB <- CellChatDB.mouse # use CellChatDB.human if running on human data
showDatabaseCategory(CellChatDB)
CellChatDB.use <- CellChatDB
# set the used database in the object
cellchat.uw@DB <- CellChatDB.use
cellchat.uw <- subsetData(cellchat.uw)
cellchat.uw <- identifyOverExpressedGenes(cellchat.uw)
cellchat.uw <- identifyOverExpressedInteractions(cellchat.uw)
cellchat.uw <- projectData(cellchat.uw, PPI.mouse)
cellchat.uw <- computeCommunProb(cellchat.uw, raw.use = TRUE)
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Error in Prob[, , i] <- Pnull :
number of items to replace is not a multiple of replacement lengthsession info:
R version 4.0.3 (2020-10-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.7
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] doParallel_1.0.16 iterators_1.0.13 foreach_1.5.1 patchwork_1.1.1
[5] forcats_0.5.1 stringr_1.4.0 purrr_0.3.4 readr_1.4.0
[9] tidyr_1.1.3 tibble_3.1.0 tidyverse_1.3.0 NMF_0.23.0
[13] cluster_2.1.0 rngtools_1.5 pkgmaker_0.32.2 registry_0.5-1
[17] CellChat_1.0.0 Biobase_2.50.0 BiocGenerics_0.36.0 ggplot2_3.3.3
[21] igraph_1.2.6 dplyr_1.0.5 SeuratObject_4.0.0 Seurat_4.0.0
loaded via a namespace (and not attached):
[1] utf8_1.2.1 reticulate_1.18
[3] tidyselect_1.1.0 htmlwidgets_1.5.3
[5] grid_4.0.3 Rtsne_0.15
[7] devtools_2.3.2 munsell_0.5.0
[9] codetools_0.2-18 ica_1.0-2
[11] future_1.21.0 miniUI_0.1.1.1
[13] withr_2.4.1 colorspace_2.0-0
[15] knitr_1.31 ggalluvial_0.12.3
[17] rstudioapi_0.13 stats4_4.0.3
[19] ROCR_1.0-11 tensor_1.5
[21] listenv_0.8.0 labeling_0.4.2
[23] MatrixGenerics_1.2.1 GenomeInfoDbData_1.2.4
[25] polyclip_1.10-0 farver_2.1.0
[27] rprojroot_2.0.2 coda_0.19-4
[29] parallelly_1.24.0 vctrs_0.3.6
[31] generics_0.1.0 xfun_0.20
[33] R6_2.5.0 GenomeInfoDb_1.26.2
[35] clue_0.3-58 gg.gap_1.3
[37] cachem_1.0.3 bitops_1.0-6
[39] spatstat.utils_2.0-0 DelayedArray_0.16.1
[41] assertthat_0.2.1 promises_1.1.1
[43] scales_1.1.1 gtable_0.3.0
[45] Cairo_1.5-12.2 globals_0.14.0
[47] processx_3.4.5 goftest_1.2-2
[49] rlang_0.4.10 systemfonts_1.0.1
[51] GlobalOptions_0.1.2 splines_4.0.3
[53] lazyeval_0.2.2 broom_0.7.4
[55] yaml_2.2.1 reshape2_1.4.4
[57] abind_1.4-5 modelr_0.1.8
[59] backports_1.2.1 httpuv_1.5.5
[61] usethis_2.0.0 tools_4.0.3
[63] gridBase_0.4-7 statnet.common_4.4.1
[65] ellipsis_0.3.1 RColorBrewer_1.1-2
[67] sessioninfo_1.1.1 ggridges_0.5.3
[69] Rcpp_1.0.6 plyr_1.8.6
[71] zlibbioc_1.36.0 RCurl_1.98-1.2
[73] prettyunits_1.1.1 ps_1.5.0
[75] rpart_4.1-15 deldir_0.2-9
[77] pbapply_1.4-3 GetoptLong_1.0.5
[79] cowplot_1.1.1 S4Vectors_0.28.1
[81] zoo_1.8-8 SummarizedExperiment_1.20.0
[83] haven_2.3.1 ggrepel_0.9.1
[85] fs_1.5.0 tinytex_0.29
[87] magrittr_2.0.1 data.table_1.13.6
[89] RSpectra_0.16-0 sna_2.6
[91] scattermore_0.7 circlize_0.4.13.1001
[93] lmtest_0.9-38 reprex_1.0.0
[95] RANN_2.6.1 fitdistrplus_1.1-3
[97] matrixStats_0.58.0 pkgload_1.1.0
[99] hms_1.0.0 mime_0.9
[101] evaluate_0.14 xtable_1.8-4
[103] readxl_1.3.1 IRanges_2.24.1
[105] gridExtra_2.3 shape_1.4.5
[107] testthat_3.0.1 compiler_4.0.3
[109] KernSmooth_2.23-18 crayon_1.4.1
[111] htmltools_0.5.1.1 mgcv_1.8-33
[113] later_1.1.0.1 lubridate_1.7.9.2
[115] DBI_1.1.1 dbplyr_2.1.0
[117] ComplexHeatmap_2.7.9.1006 MASS_7.3-53
[119] Matrix_1.3-2 cli_2.3.1
[121] GenomicRanges_1.42.0 pkgconfig_2.0.3
[123] plotly_4.9.3 xml2_1.3.2
[125] svglite_2.0.0 XVector_0.30.0
[127] rvest_0.3.6 callr_3.5.1
[129] digest_0.6.27 sctransform_0.3.2
[131] RcppAnnoy_0.0.18 rle_0.9.2
[133] spatstat.data_1.7-0 rmarkdown_2.6
[135] cellranger_1.1.0 leiden_0.3.7
[137] uwot_0.1.10 shiny_1.6.0
[139] rjson_0.2.20 lifecycle_1.0.0
[141] nlme_3.1-152 jsonlite_1.7.2
[143] network_1.16.1 desc_1.2.0
[145] viridisLite_0.3.0 fansi_0.4.2
[147] pillar_1.5.1 lattice_0.20-41
[149] pkgbuild_1.2.0 fastmap_1.1.0
[151] httr_1.4.2 survival_3.2-7
[153] remotes_2.2.0 glue_1.4.2
[155] FNN_1.1.3 spatstat_1.64-1
[157] png_0.1-7 stringi_1.5.3
[159] memoise_2.0.0 irlba_2.3.3
[161] future.apply_1.7.0 object@data.signaling:
1035 x 2404 sparse Matrix of class "dgCMatrix"
[[ suppressing 35 column names ‘UW_AAACCCACACATGGTT-1’, ‘UW_AAACCCACACATGTTG-1’, ‘UW_AAACCCACATTCGGGC-1’ ... ]]
[[ suppressing 35 column names ‘UW_AAACCCACACATGGTT-1’, ‘UW_AAACCCACACATGTTG-1’, ‘UW_AAACCCACATTCGGGC-1’ ... ]]
Oprk1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Npbwr1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Il17a . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Il17f . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Col9a1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Cfc1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Sema4c 4 . . . . 1 1 . . . . . . . . . 1 . 1 . . . . . 2 1 . 1 . . . . . 1 . ......
Nms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Il1r2 . . . . . . . . 37 . . . . . . 1 . . . . . 2 . . . 4 . . . . . . . . . ......
Il1r1 . . . . . . . . . . . 2 . . 1 . . . . . . 1 1 . . . . . . . . . . . . ......
Il1rl2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Il1rl1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Il18r1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Il18rap . . . . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . . . . ......
..............................
........suppressing 2369 columns and 1007 rows in show(); maybe adjust 'options(max.print= *, width = *)'
..............................
[[ suppressing 35 column names ‘UW_AAACCCACACATGGTT-1’, ‘UW_AAACCCACACATGTTG-1’, ‘UW_AAACCCACATTCGGGC-1’ ... ]]
Pdcd1lg2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Il33 . . . . . . . 2 . . . . . . . . . . . . 1 . . . . 2 . . . . . . . . . ......
Dkk1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Fas 2 1 . . . . 1 . . . . . . . 1 1 . . . . . . . . . . . . . . . . . . . ......
Entpd1 3 . . . . 2 . . . . . . . . . . 1 . . . . . 1 . . . . . 1 1 . . . . . ......
Sfrp5 . . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . . . . ......
Wnt8b . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Sema4g . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Fgf8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Ins1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Gfra1 . . . . . . . 1 . . . . . . . . . . 1 . . . . . . . . . . 1 . 1 . 1 . ......
Prlhr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Csf2ra . . . 3 . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . . . . ......
Ccl21c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ......unique(object@idents):
[1] Endothelium ECM Int. Fibroblasts 2 M2 Macrophages
[4] Translation Fibroblasts 1 ECM Org. Fibroblasts 2 Dendritic Cells
[7] Repair Fibroblasts Activated Endothelium Signaling Fibroblasts 2
[10] Translation Fibroblasts 2 ECM Int. Fibroblasts 1 Myofibroblasts
[13] ECM Org. Fibroblasts 1 T Cells Signaling Fibroblasts 1
[16] Epithelium
17 Levels: Translation Fibroblasts 1 Translation Fibroblasts 2 ... M2 Macrophages@jessicook Two mistakes in your data: 1) The input data should be normalized data instead of count data. 2) The number of levels in object@idents is not the same number of cell groups. You should drop the levels in the factor variable.
Dear Professor,
Thanks for your development of this excellent package. When I performed the function "computeCommunProb", there is an error named "Error in Prob[, , i] <- Pnull, The replaced item is not a multiple of the length of the replacement value".
And my code was as follows:
data.input <- seob@assays$RNA@counts meta = seob@meta.data cellchat <- createCellChat(object = data.input, meta = meta, group.by = "celltype") cellchat <- addMeta(cellchat, meta = meta) cellchat <- setIdent(cellchat, ident.use = "celltype") levels(cellchat@idents) groupSize <- as.numeric(table(cellchat@idents)) CellChatDB <- CellChatDB.human CellChatDB.use <- subsetDB(CellChatDB, search="Secreted Signaling") cellchat@DB <- CellChatDB.use cellchat <- subsetData(cellchat) cellchat <- identifyOverExpressedGenes(cellchat) cellchat <- identifyOverExpressedInteractions(cellchat) cellchat <- projectData(cellchat, PPI.human) cellchat <- computeCommunProb(cellchat, raw.use = TRUE)
I confirmed that the seurat object was the same as the sample data, and the annotation of celltype was defined as the "idents" of cellchat object.
I am looking forward to your reply. Thanks again!