cellassign
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Published
20 hours ago •
Irrationone
Irrationone
SizeFactors() does not add size factors to SingleCellObject
Hi,
I want to classify 1,047 cells from a Seurat object in 16 possible phenotypes and I used the cellassign package for that. I ran the below code, but I had the mentioned error. I think I followed the vignette correctly, but it seems like the sizeFactors() does not add the size factors to the SingleCellObject. Any suggestions?
CellAssign
# Import data as SingleCellExperiment object
counts <- tcelldataset@assays$RNA@counts
sce <- SingleCellExperiment(assays = list(counts = counts))
# Prepare the marker gene set
marker.gene.set<-merge(x=df.cd4, y=df.cd8, by='test', all=T, sort=F)
marker.gene.set<-merge(x=marker.gene.set, y=df.tregs, by='test', all=T, sort=F)
marker.gene.set[is.na(marker.gene.set)] <- 0
rownames(marker.gene.set)<-marker.gene.set$test
marker.gene.set$test<-NULL
marker.gene.set<-as.matrix(marker.gene.set)
# Compute size factors
sf <- sizeFactors(sce)
# Run cellassign
sce_marker <- sce[intersect(rownames(marker.gene.set), rownames(sce)),]
marker.gene.set<-marker.gene.set[intersect(rownames(marker.gene.set), rownames(sce)),]
fit <- cellassign(exprs_obj = sce_marker,
marker_gene_info = marker.gene.set,
s = sf,
#X=X,
learning_rate = 1e-2,
shrinkage = TRUE,
verbose = FALSE)
No size factors supplied - computing from matrix. It is highly recommended to supply size factors calculated using the full gene set
Error in py_module_import(module, convert = convert) :
ModuleNotFoundError: No module named 'tensorflow_probability'
In addition: Warning messages:
1: In cellassign(exprs_obj = sce_marker, marker_gene_info = marker.gene.set, :
Genes with no mapping counts are present. Make sure this is expected -- this can be valid input in some cases (e.g. when cell types are overspecified).
2: In cellassign(exprs_obj = sce_marker, marker_gene_info = marker.gene.set, :
You have specified 1564 input genes. Are you sure these are just your markers? Only the marker genes should be used as input
3: use 'calculateSumFactors' for any 'x' that is not a SingleCellExperiment
I attach my SessionInfo() in case it may be useful
sessionInfo()
R version 3.6.2 (2019-12-12)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 10 (buster)
Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.3.5.so
Random number generation:
RNG: Mersenne-Twister
Normal: Inversion
Sample: Rounding
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=C LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] scran_1.14.6 SingleR_1.0.5 org.Hs.eg.db_3.10.0 org.Mm.eg.db_3.10.0
[5] AnnotationDbi_1.48.0 DOSE_3.12.0 clusterProfiler_3.14.3 genefilter_1.68.0
[9] ggrepel_0.8.1 jsonlite_1.6 backports_1.1.5 ggExtra_0.9
[13] Matrix_1.2-18 RColorBrewer_1.1-2 dplyr_0.8.3 readr_1.3.1
[17] Seurat_3.1.2 useful_1.2.6 scales_1.1.0 ggplot2_3.2.1
[21] data.table_1.12.8 gdata_2.18.0 SingleCellExperiment_1.8.0 SummarizedExperiment_1.16.1
[25] DelayedArray_0.12.2 BiocParallel_1.20.1 matrixStats_0.55.0 Biobase_2.46.0
[29] GenomicRanges_1.38.0 GenomeInfoDb_1.22.0 IRanges_2.20.1 S4Vectors_0.24.1
[33] BiocGenerics_0.32.0 tensorflow_2.0.0 cellassign_0.99.16 BiocManager_1.30.10
loaded via a namespace (and not attached):
[1] rappdirs_0.3.1 R.methodsS3_1.7.1 tidyr_1.0.0
[4] bit64_0.9-7 irlba_2.3.3 multcomp_1.4-11
[7] R.utils_2.9.2 RCurl_1.95-4.12 metap_1.2
[10] callr_3.4.0 cowplot_1.0.0 TH.data_1.0-10
[13] usethis_1.5.1 RSQLite_2.2.0 RANN_2.6.1
[16] europepmc_0.3 future_1.15.1 bit_1.1-14
[19] enrichplot_1.6.1 mutoss_0.1-12 xml2_1.2.2
[22] httpuv_1.5.2 assertthat_0.2.1 viridis_0.5.1
[25] hms_0.5.3 promises_1.1.0 fansi_0.4.1
[28] progress_1.2.2 caTools_1.17.1.3 dbplyr_1.4.2
[31] igraph_1.2.4.2 DBI_1.1.0 htmlwidgets_1.5.1
[34] purrr_0.3.3 ellipsis_0.3.0 annotate_1.64.0
[37] gbRd_0.4-11 RcppParallel_4.4.4 vctrs_0.2.1
[40] remotes_2.1.0 ROCR_1.0-7 withr_2.1.2
[43] ggforce_0.3.1 triebeard_0.3.0 sctransform_0.2.0
[46] prettyunits_1.1.0 mnormt_1.5-5 cluster_2.1.0
[49] ExperimentHub_1.12.0 ape_5.3 lazyeval_0.2.2
[52] crayon_1.3.4 edgeR_3.28.0 pkgconfig_2.0.3
[55] tweenr_1.0.1 vipor_0.4.5 nlme_3.1-143
[58] pkgload_1.0.2 devtools_2.2.1 rlang_0.4.2
[61] globals_0.12.5 lifecycle_0.1.0 miniUI_0.1.1.1
[64] sandwich_2.5-1 BiocFileCache_1.10.2 rsvd_1.0.2
[67] AnnotationHub_2.18.0 rprojroot_1.3-2 polyclip_1.10-0
[70] lmtest_0.9-37 urltools_1.7.3 zoo_1.8-6
[73] beeswarm_0.2.3 base64enc_0.1-3 pheatmap_1.0.12
[76] whisker_0.4 ggridges_0.5.1 processx_3.4.1
[79] png_0.1-7 viridisLite_0.3.0 bitops_1.0-6
[82] R.oo_1.23.0 KernSmooth_2.23-16 blob_1.2.0
[85] DelayedMatrixStats_1.8.0 stringr_1.4.0 qvalue_2.18.0
[88] gridGraphics_0.4-1 memoise_1.1.0 magrittr_1.5
[91] plyr_1.8.5 ica_1.0-2 gplots_3.0.1.1
[94] bibtex_0.4.2.2 zlibbioc_1.32.0 compiler_3.6.2
[97] lsei_1.2-0 dqrng_0.2.1 plotrix_3.7-7
[100] fitdistrplus_1.0-14 cli_2.0.1 XVector_0.26.0
[103] listenv_0.8.0 pbapply_1.4-2 ps_1.3.0
[106] MASS_7.3-51.5 tidyselect_0.2.5 stringi_1.4.4
[109] yaml_2.2.0 GOSemSim_2.12.0 locfit_1.5-9.1
[112] BiocSingular_1.2.1 grid_3.6.2 fastmatch_1.1-0
[115] tools_3.6.2 future.apply_1.4.0 rstudioapi_0.10
[118] gridExtra_2.3 farver_2.0.1 Rtsne_0.15
[121] ggraph_2.0.0 digest_0.6.23 rvcheck_0.1.7
[124] shiny_1.4.0 Rcpp_1.0.3 SDMTools_1.1-221.2
[127] BiocVersion_3.10.1 later_1.0.0 RcppAnnoy_0.0.14
[130] httr_1.4.1 npsurv_0.4-0 Rdpack_0.11-1
[133] colorspace_1.4-1 XML_3.98-1.20 fs_1.3.1
[136] reticulate_1.14 splines_3.6.2 statmod_1.4.32
[139] uwot_0.1.5 sn_1.5-4 scater_1.14.6
[142] graphlayouts_0.5.0 multtest_2.42.0 ggplotify_0.0.4
[145] plotly_4.9.1 sessioninfo_1.1.1 xtable_1.8-4
[148] tidygraph_1.1.2 zeallot_0.1.0 testthat_2.3.1
[151] R6_2.4.1 TFisher_0.2.0 pillar_1.4.3
[154] htmltools_0.4.0 mime_0.8 glue_1.3.1
[157] fastmap_1.0.1 BiocNeighbors_1.4.1 interactiveDisplayBase_1.24.0
[160] codetools_0.2-16 fgsea_1.12.0 pkgbuild_1.0.6
[163] tsne_0.1-3 mvtnorm_1.0-12 lattice_0.20-38
[166] tibble_2.1.3 numDeriv_2016.8-1.1 ggbeeswarm_0.6.0
[169] curl_4.3 leiden_0.3.1 tfruns_1.4
[172] gtools_3.8.1 GO.db_3.8.2 limma_3.42.0
[175] survival_3.1-8 desc_1.2.0 munsell_0.5.0
[178] DO.db_2.9 GenomeInfoDbData_1.2.2 reshape2_1.4.3
[181] gtable_0.3.0
Looks like 2 problems here. Size factors not being carried over because I suspect sizeFactors(sce) is NULL. You should be able to recompute them by calling
sce <- scran::computeSumFactors(sce)
after creating the object. But more importantly, it looks like tensorflow probability isn't installed properly:
Error in py_module_import(module, convert = convert) :
ModuleNotFoundError: No module named 'tensorflow_probability'
If you run
tensorflow::install_tensorflow(extra_packages='tensorflow-probability', version = "2.1.0")
then call
tensorflow::tf_config()
how does it look?
Sorry for the delay, time difference... Is it possible to work with tensorflow v 2.0.0?
You can try but I think there was a tensorflow probability error last time I did