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rikenbit / scTensor

R package for detection of cell-cell interaction using Non-negative Tensor Decomposition
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File figures/Receptor/207.png not found in resource path #4

Closed danshu closed 5 years ago

danshu commented 5 years ago

Hi,

My scTensor fun failed at the step converting Rmd files to html files. The "207.png" was not found in the folder. ... ligand.Rmd is created... receptor.Rmd is created... ligand_all.Rmd is created... receptor_all.Rmd is created... ligand.Rmd is compiled to ligand.html... File figures/Receptor/207.png not found in resource path Error: pandoc document conversion failed with error 99 Execution halted

Best, Danshu

danshu commented 5 years ago

I tried the following codes and successfully converted to html files. require(knitr) # required for knitting from rmd to md require(markdown) # required for md to html knit('test.rmd', 'test.md') # creates md file markdownToHTML('test.md', 'test.html') # creates html file

kokitsuyuzaki commented 5 years ago

Could you show me the result of sessionInfo()? Also, send me the source code to reproduce the error. My e-mail is k.t.the-answer[at]hotmail.co.jp

danshu commented 5 years ago

R version 3.6.0 (2019-04-26) Platform: x86_64-conda_cos6-linux-gnu (64-bit) Running under: CentOS Linux 7 (Core)

Matrix products: default BLAS/LAPACK: /tools/anaconda3/envs/renv/lib/R/lib/libRblas.so

locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages: [1] stats4 parallel stats graphics grDevices utils datasets [8] methods base

other attached packages: [1] AnnotationHub_2.16.0 [2] BiocFileCache_1.8.0 [3] dbplyr_1.4.2 [4] Mus.musculus_1.3.1 [5] TxDb.Mmusculus.UCSC.mm10.knownGene_3.4.7 [6] org.Mm.eg.db_3.8.2 [7] Homo.sapiens_1.3.1 [8] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 [9] org.Hs.eg.db_3.8.2 [10] GO.db_3.8.2 [11] OrganismDbi_1.26.0 [12] GenomicFeatures_1.36.4 [13] AnnotationDbi_1.46.0 [14] Seurat_3.0.2 [15] SingleCellExperiment_1.6.0 [16] SummarizedExperiment_1.14.0 [17] DelayedArray_0.10.0 [18] BiocParallel_1.18.0 [19] matrixStats_0.54.0 [20] Biobase_2.44.0 [21] GenomicRanges_1.36.0 [22] GenomeInfoDb_1.20.0 [23] IRanges_2.18.1 [24] S4Vectors_0.22.0 [25] MeSH.Mmu.eg.db_1.12.0 [26] MeSH.Hsa.eg.db_1.12.0 [27] MeSHDbi_1.20.0 [28] BiocGenerics_0.30.0 [29] LRBase.Mmu.eg.db_1.1.0 [30] LRBase.Hsa.eg.db_1.1.0 [31] LRBaseDbi_1.2.0 [32] scTensor_1.0.7

loaded via a namespace (and not attached): [1] rsvd_1.0.1 Hmisc_4.2-0 [3] ica_1.0-2 Rsamtools_2.0.0 [5] foreach_1.4.4 lmtest_0.9-37 [7] crayon_1.3.4 MASS_7.3-51.4 [9] nlme_3.1-140 backports_1.1.4 [11] GOSemSim_2.10.0 rlang_0.4.0 [13] XVector_0.24.0 ROCR_1.0-7 [15] irlba_2.3.3 nnTensor_0.99.4 [17] GOstats_2.50.0 tagcloud_0.6 [19] bit64_0.9-7 glue_1.3.1 [21] sctransform_0.2.0 UpSetR_1.4.0 [23] dotCall64_1.0-0 DOSE_3.10.2 [25] tidyselect_0.2.5 fitdistrplus_1.0-14 [27] XML_3.98-1.16 tidyr_0.8.3 [29] zoo_1.8-6 GenomicAlignments_1.20.1 [31] xtable_1.8-4 magrittr_1.5 [33] evaluate_0.14 bibtex_0.4.2 [35] ggplot2_3.2.0 Rdpack_0.11-0 [37] zlibbioc_1.30.0 rstudioapi_0.10 [39] rpart_4.1-15 fastmatch_1.1-0 [41] BiocStyle_2.12.0 ensembldb_2.8.0 [43] maps_3.3.0 fields_9.8-3 [45] shiny_1.3.2 xfun_0.8 [47] cluster_2.1.0 caTools_1.17.1.2 [49] TSP_1.1-7 tibble_2.1.3 [51] interactiveDisplayBase_1.22.0 ggrepel_0.8.1 [53] biovizBase_1.32.0 ape_5.3 [55] listenv_0.7.0 dendextend_1.12.0 [57] Biostrings_2.52.0 png_0.1-7 [59] future_1.14.0 zeallot_0.1.0 [61] bitops_1.0-6 ggforce_0.2.2 [63] RBGL_1.60.0 plyr_1.8.4 [65] GSEABase_1.46.0 AnnotationFilter_1.8.0 [67] pillar_1.4.2 gplots_3.0.1.1 [69] graphite_1.30.0 europepmc_0.3 [71] vctrs_0.2.0 plot3D_1.1.1 [73] urltools_1.7.3 MeSH.Aca.eg.db_1.12.0 [75] metap_1.1 outliers_0.14 [77] tools_3.6.0 foreign_0.8-71 [79] munsell_0.5.0 tweenr_1.0.1 [81] fgsea_1.10.0 compiler_3.6.0 [83] abind_1.4-5 httpuv_1.5.1 [85] rtracklayer_1.44.0 Gviz_1.28.0 [87] plotly_4.9.0 GenomeInfoDbData_1.2.1 [89] gridExtra_2.3 lattice_0.20-38 [91] AnnotationForge_1.26.0 later_0.8.0 [93] dplyr_0.8.3 jsonlite_1.6 [95] scales_1.0.0 graph_1.62.0 [97] pbapply_1.4-1 genefilter_1.66.0 [99] lazyeval_0.2.2 promises_1.0.1 [101] MeSH.db_1.12.0 latticeExtra_0.6-28 [103] R.utils_2.9.0 reticulate_1.12 [105] checkmate_1.9.4 rmarkdown_1.14 [107] cowplot_1.0.0 MeSH.Syn.eg.db_1.12.0 [109] webshot_0.5.1 Rtsne_0.15 [111] dichromat_2.0-0 BSgenome_1.52.0 [113] igraph_1.2.4.1 gclus_1.3.2 [115] survival_2.44-1.1 yaml_2.2.0 [117] plotrix_3.7-6 htmltools_0.3.6 [119] memoise_1.1.0 VariantAnnotation_1.30.1 [121] rTensor_1.4 seriation_1.2-7 [123] viridisLite_0.3.0 digest_0.6.20 [125] assertthat_0.2.1 ReactomePA_1.28.0 [127] mime_0.7 rappdirs_0.3.1 [129] registry_0.5-1 npsurv_0.4-0 [131] spam_2.2-2 RSQLite_2.1.1 [133] future.apply_1.3.0 lsei_1.2-0 [135] misc3d_0.8-4 data.table_1.12.2 [137] blob_1.2.0 R.oo_1.22.0 [139] cummeRbund_2.26.0 splines_3.6.0 [141] Formula_1.2-3 ProtGenerics_1.16.0 [143] RCurl_1.95-4.12 hms_0.5.0 [145] colorspace_1.4-1 base64enc_0.1-3 [147] BiocManager_1.30.4 SDMTools_1.1-221.1 [149] nnet_7.3-12 Rcpp_1.0.1 [151] RANN_2.6.1 MeSH.PCR.db_1.12.0 [153] enrichplot_1.4.0 R6_2.4.0 [155] grid_3.6.0 ggridges_0.5.1 [157] acepack_1.4.1 curl_3.3 [159] MeSH.Bsu.168.eg.db_1.12.0 gdata_2.18.0 [161] MeSH.AOR.db_1.12.0 meshr_1.20.0 [163] DO.db_2.9 Matrix_1.2-17 [165] qvalue_2.16.0 RColorBrewer_1.1-2 [167] iterators_1.0.10 stringr_1.4.0 [169] htmlwidgets_1.3 polyclip_1.10-0 [171] triebeard_0.3.0 biomaRt_2.40.1 [173] purrr_0.3.2 gridGraphics_0.4-1 [175] reactome.db_1.68.0 globals_0.12.4 [177] htmlTable_1.13.1 codetools_0.2-16 [179] gtools_3.8.1 prettyunits_1.0.2 [181] R.methodsS3_1.7.1 gtable_0.3.0 [183] tsne_0.1-3 DBI_1.0.0 [185] httr_1.4.0 KernSmooth_2.23-15 [187] stringi_1.4.3 progress_1.2.2 [189] reshape2_1.4.3 farver_1.1.0 [191] heatmaply_0.16.0 annotate_1.62.0 [193] viridis_0.5.1 fdrtool_1.2.15 [195] Rgraphviz_2.28.0 xml2_1.2.0 [197] rvcheck_0.1.3 ggplotify_0.0.3 [199] Category_2.50.0 bit_1.1-14 [201] ggraph_1.0.2 pkgconfig_2.0.2 [203] gbRd_0.4-11 knitr_1.23

danshu commented 5 years ago

I don't know how to reproduce the error, so I dig into your codes a little bit.

con = dbConnect(SQLite(), metadata(sce)$lrbase) LR <- dbGetQuery(con, "SELECT * FROM DATA")[, c("GENEID_L", "GENEID_R", "SOURCEID")] LR <- unique(LR) LR$GENEID_R should be all the receptor ids with a png plotted. However, "207" is not in this list. Actually I was runnning scTensor on a list of samples, and all of them failed at this step reporting that "207.png/945.png/5530.png" was not found. I can found "207/945/5530“ in ligand.Rmd files: "[945]" "(https://www.ncbi.nlm.nih.gov/gene/945)" The strange thing about these genes is that they do not have their gene symbols in the file as other genes do. For example, "[CDC42]" "(https://www.ncbi.nlm.nih.gov/gene/998)"

kokitsuyuzaki commented 5 years ago

Please send me your source code of scTensor and your data. Otherwise, I cannot correctly modify this error in my environment.

If you hesitate to send your original experimental data, I recommend replacing the column names of the matrix such as X1, X2, Y1, Y2. It does not affect the reproducibility of the error.

danshu commented 5 years ago

Thank! I can finish scTensor when I rerun my codes. I guess this error was due to the R environment since I'm updating lots of R packages recently.