Hello,
I am openning this issue because, I wanted to sum up some scores by running map_result_to_celltypes() on the deconvolute() output with the ConsensusTME method.
However, using "other cell" to sum up the "Endothelial cell" and "Cancer associated fibroblast" scores, map_result_to_celltypes() returns NAs.
I am guessing it has to do with @grst response to issue #120, with "other cell" needing all children cell-type to return a value, is it the expected behavior?
Secondly, it seems the Plasma_cells from Consensus_TME cell type is missing from cell_type_map, and subsequently doesn't appear when running deconvolute(), but does with deconvolute_consensus_tme.
#issue1#
test <- immunedeconv::deconvolute(immunedeconv::dataset_racle$expr_mat, "consensus_tme", indications = rep("skcm", 4))
test2 <- map_result_to_celltypes(res_consensusTME, c("other cell"))
#issue2#
test <- immunedeconv::deconvolute(immunedeconv::dataset_racle$expr_mat, "consensus_tme", indications = rep("skcm", 4))
test2 <- immunedeconv::deconvolute_consensus_tme(immunedeconv::dataset_racle$expr_mat, indications = rep("skcm", 4))
Versions
Details
R version 4.3.0 (2023-04-21 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)
Matrix products: default
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] org.Hs.eg.db_3.17.0 readxl_1.4.3 rjson_0.2.21 TCGAbiolinks_2.28.4 prismatic_1.1.1
[6] biomaRt_2.56.1 RColorBrewer_1.1-3 gplots_3.1.3 viridis_0.6.4 viridisLite_0.4.2
[11] hrbrthemes_0.8.0 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 purrr_1.0.2
[16] readr_2.1.4 tibble_3.2.1 tidyverse_2.0.0 tidyr_1.3.0 dplyr_1.1.4
[21] Cairo_1.6-1 pheatmap_1.0.12 writexl_1.4.2 GO.db_3.17.0 org.Mm.eg.db_3.17.0
[26] AnnotationDbi_1.62.2 IRanges_2.34.1 S4Vectors_0.38.2 Biobase_2.60.0 BiocGenerics_0.46.0
[31] statmod_1.5.0 EnhancedVolcano_1.18.0 ggrepel_0.9.4 ggplot2_3.4.4 immunedeconv_2.1.0
[36] EPIC_1.1.6 data.table_1.14.8 BiocManager_1.30.22 edgeR_3.42.4 limma_3.56.2
loaded via a namespace (and not attached):
[1] splines_4.3.0 later_1.3.1 bitops_1.0-7 filelock_1.0.2
[5] cellranger_1.1.0 preprocessCore_1.62.1 graph_1.78.0 XML_3.99-0.15
[9] lifecycle_1.0.4 lattice_0.22-5 MASS_7.3-60 magrittr_2.0.3
[13] rmarkdown_2.25 remotes_2.4.2.1 ConsensusTME_0.0.1.9000 httpuv_1.6.12
[17] DBI_1.1.3 abind_1.4-5 zlibbioc_1.46.0 rvest_1.0.3
[21] GenomicRanges_1.52.1 RCurl_1.98-1.13 rappdirs_0.3.3 sva_3.48.0
[25] gdtools_0.3.4 GenomeInfoDbData_1.2.10 data.tree_1.1.0 irlba_2.3.5.1
[29] crul_1.4.0 genefilter_1.82.1 GSVA_1.48.3 annotate_1.78.0
[33] DelayedMatrixStats_1.22.6 codetools_0.2-19 DelayedArray_0.26.7 xml2_1.3.5
[37] tidyselect_1.2.0 httpcode_0.3.0 farver_2.1.1 ScaledMatrix_1.8.1
[41] TCGAbiolinksGUI.data_1.20.0 matrixStats_1.1.0 BiocFileCache_2.8.0 jsonlite_1.8.7
[45] ellipsis_0.3.2 survival_3.5-7 systemfonts_1.0.5 tools_4.3.0
[49] progress_1.2.2 Rcpp_1.0.11 glue_1.6.2 gridExtra_2.3
[53] Rttf2pt1_1.3.12 xfun_0.41 mgcv_1.9-0 MatrixGenerics_1.12.3
[57] GenomeInfoDb_1.36.4 HDF5Array_1.28.1 withr_2.5.2 ComICS_1.0.4
[61] fastmap_1.1.1 rhdf5filters_1.12.1 fansi_1.0.5 rsvd_1.0.5
[65] caTools_1.18.2 digest_0.6.33 timechange_0.2.0 R6_2.5.1
[69] mime_0.12 colorspace_2.1-0 gtools_3.9.5 mMCPcounter_1.1.0
[73] RSQLite_2.3.3 utf8_1.2.4 generics_0.1.3 fontLiberation_0.1.0
[77] prettyunits_1.2.0 httr_1.4.7 S4Arrays_1.0.6 pkgconfig_2.0.3
[81] gtable_0.3.4 blob_1.2.4 SingleCellExperiment_1.22.0 XVector_0.40.0
[85] htmltools_0.5.7 fontBitstreamVera_0.1.1 GSEABase_1.62.0 scales_1.3.0
[89] png_0.1-8 knitr_1.45 rstudioapi_0.15.0 tzdb_0.4.0
[93] nlme_3.1-163 curl_5.1.0 rhdf5_2.44.0 cachem_1.0.8
[97] testit_0.13 KernSmooth_2.23-22 parallel_4.3.0 extrafont_0.19
[101] pillar_1.9.0 grid_4.3.0 vctrs_0.6.4 promises_1.2.1
[105] BiocSingular_1.16.0 beachmat_2.16.0 dbplyr_2.4.0 xtable_1.8-4
[109] extrafontdb_1.0 evaluate_0.23 cli_3.6.1 locfit_1.5-9.8
[113] compiler_4.3.0 rlang_1.1.2 crayon_1.5.2 plyr_1.8.9
[117] stringi_1.8.2 BiocParallel_1.34.2 munsell_0.5.0 Biostrings_2.68.1
[121] fontquiver_0.2.1 Matrix_1.6-3 hms_1.1.3 sparseMatrixStats_1.12.2
[125] bit64_4.0.5 Rhdf5lib_1.22.1 gfonts_0.2.0 KEGGREST_1.40.1
[129] shiny_1.8.0 SummarizedExperiment_1.30.2 memoise_2.0.1 bit_4.0.5
[133] downloader_0.4
Hello,
I am openning this issue because, I wanted to sum up some scores by running
map_result_to_celltypes()on thedeconvolute()output with the ConsensusTME method.However, using "other cell" to sum up the "Endothelial cell" and "Cancer associated fibroblast" scores,
map_result_to_celltypes()returns NAs.I am guessing it has to do with @grst response to issue #120, with "other cell" needing all children cell-type to return a value, is it the expected behavior?
Secondly, it seems the Plasma_cells from Consensus_TME cell type is missing from
cell_type_map, and subsequently doesn't appear when runningdeconvolute(), but does withdeconvolute_consensus_tme.Versions
Details
R version 4.3.0 (2023-04-21 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)
Matrix products: default
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] org.Hs.eg.db_3.17.0 readxl_1.4.3 rjson_0.2.21 TCGAbiolinks_2.28.4 prismatic_1.1.1
[6] biomaRt_2.56.1 RColorBrewer_1.1-3 gplots_3.1.3 viridis_0.6.4 viridisLite_0.4.2
[11] hrbrthemes_0.8.0 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 purrr_1.0.2
[16] readr_2.1.4 tibble_3.2.1 tidyverse_2.0.0 tidyr_1.3.0 dplyr_1.1.4
[21] Cairo_1.6-1 pheatmap_1.0.12 writexl_1.4.2 GO.db_3.17.0 org.Mm.eg.db_3.17.0
[26] AnnotationDbi_1.62.2 IRanges_2.34.1 S4Vectors_0.38.2 Biobase_2.60.0 BiocGenerics_0.46.0
[31] statmod_1.5.0 EnhancedVolcano_1.18.0 ggrepel_0.9.4 ggplot2_3.4.4 immunedeconv_2.1.0
[36] EPIC_1.1.6 data.table_1.14.8 BiocManager_1.30.22 edgeR_3.42.4 limma_3.56.2
loaded via a namespace (and not attached):
[1] splines_4.3.0 later_1.3.1 bitops_1.0-7 filelock_1.0.2
[5] cellranger_1.1.0 preprocessCore_1.62.1 graph_1.78.0 XML_3.99-0.15
[9] lifecycle_1.0.4 lattice_0.22-5 MASS_7.3-60 magrittr_2.0.3
[13] rmarkdown_2.25 remotes_2.4.2.1 ConsensusTME_0.0.1.9000 httpuv_1.6.12
[17] DBI_1.1.3 abind_1.4-5 zlibbioc_1.46.0 rvest_1.0.3
[21] GenomicRanges_1.52.1 RCurl_1.98-1.13 rappdirs_0.3.3 sva_3.48.0
[25] gdtools_0.3.4 GenomeInfoDbData_1.2.10 data.tree_1.1.0 irlba_2.3.5.1
[29] crul_1.4.0 genefilter_1.82.1 GSVA_1.48.3 annotate_1.78.0
[33] DelayedMatrixStats_1.22.6 codetools_0.2-19 DelayedArray_0.26.7 xml2_1.3.5
[37] tidyselect_1.2.0 httpcode_0.3.0 farver_2.1.1 ScaledMatrix_1.8.1
[41] TCGAbiolinksGUI.data_1.20.0 matrixStats_1.1.0 BiocFileCache_2.8.0 jsonlite_1.8.7
[45] ellipsis_0.3.2 survival_3.5-7 systemfonts_1.0.5 tools_4.3.0
[49] progress_1.2.2 Rcpp_1.0.11 glue_1.6.2 gridExtra_2.3
[53] Rttf2pt1_1.3.12 xfun_0.41 mgcv_1.9-0 MatrixGenerics_1.12.3
[57] GenomeInfoDb_1.36.4 HDF5Array_1.28.1 withr_2.5.2 ComICS_1.0.4
[61] fastmap_1.1.1 rhdf5filters_1.12.1 fansi_1.0.5 rsvd_1.0.5
[65] caTools_1.18.2 digest_0.6.33 timechange_0.2.0 R6_2.5.1
[69] mime_0.12 colorspace_2.1-0 gtools_3.9.5 mMCPcounter_1.1.0
[73] RSQLite_2.3.3 utf8_1.2.4 generics_0.1.3 fontLiberation_0.1.0
[77] prettyunits_1.2.0 httr_1.4.7 S4Arrays_1.0.6 pkgconfig_2.0.3
[81] gtable_0.3.4 blob_1.2.4 SingleCellExperiment_1.22.0 XVector_0.40.0
[85] htmltools_0.5.7 fontBitstreamVera_0.1.1 GSEABase_1.62.0 scales_1.3.0
[89] png_0.1-8 knitr_1.45 rstudioapi_0.15.0 tzdb_0.4.0
[93] nlme_3.1-163 curl_5.1.0 rhdf5_2.44.0 cachem_1.0.8
[97] testit_0.13 KernSmooth_2.23-22 parallel_4.3.0 extrafont_0.19
[101] pillar_1.9.0 grid_4.3.0 vctrs_0.6.4 promises_1.2.1
[105] BiocSingular_1.16.0 beachmat_2.16.0 dbplyr_2.4.0 xtable_1.8-4
[109] extrafontdb_1.0 evaluate_0.23 cli_3.6.1 locfit_1.5-9.8
[113] compiler_4.3.0 rlang_1.1.2 crayon_1.5.2 plyr_1.8.9
[117] stringi_1.8.2 BiocParallel_1.34.2 munsell_0.5.0 Biostrings_2.68.1
[121] fontquiver_0.2.1 Matrix_1.6-3 hms_1.1.3 sparseMatrixStats_1.12.2
[125] bit64_4.0.5 Rhdf5lib_1.22.1 gfonts_0.2.0 KEGGREST_1.40.1
[129] shiny_1.8.0 SummarizedExperiment_1.30.2 memoise_2.0.1 bit_4.0.5
[133] downloader_0.4