Error in scCATCH

[m3lorra]

Hello,

I run findmarkergenes using my Seurat object

clu_markers <- findmarkergenes(mat.so.singlet,
                               species = "Mouse",
                               cluster = 'All',
                               match_CellMatch = FALSE,
                               cancer = NULL,
                               tissue = "Bone-related",
                               cell_min_pct = 0.25,
                               logfc = 0.25,
                               pvalue = 0.05)

It run succesfully for each cluster in my object but then when I do scCATCH I get an error:

clu_ann <- scCATCH(clu_markers$clu_markers, species = 'Mouse', cancer = NULL, tissue = "Bone-related")
Error in scCATCH(clu_markers$clu_markers, species = "Mouse", cancer = NULL,  :
  Bone-related, not matched with the tissue types in CellMatch database! Please select one or more related tissue types.

I think "Mouse" and "Bone-related" should work fine as they are, so I don't get why I get this error.

Can you take a look into that?

> sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Ubuntu 20.04.2 LTS

Matrix products: default
BLAS/LAPACK: /home/steph/miniconda3/envs/r_v4/lib/libopenblasp-r0.3.12.so

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

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

other attached packages:
[1] SeuratObject_4.0.2 Seurat_4.0.3       scCATCH_2.1

loaded via a namespace (and not attached):
  [1] nlme_3.1-152          matrixStats_0.59.0    spatstat.sparse_2.0-0
  [4] progress_1.2.2        RcppAnnoy_0.0.18      RColorBrewer_1.1-2
  [7] httr_1.4.2            sctransform_0.3.2     tools_4.0.3
 [10] utf8_1.2.1            R6_2.5.0              irlba_2.3.3
 [13] rpart_4.1-15          KernSmooth_2.23-20    uwot_0.1.10
 [16] mgcv_1.8-36           lazyeval_0.2.2        colorspace_2.0-2
 [19] prettyunits_1.1.1     tidyselect_1.1.1      gridExtra_2.3
 [22] compiler_4.0.3        plotly_4.9.4.1        scales_1.1.1
 [25] lmtest_0.9-38         spatstat.data_2.1-0   ggridges_0.5.3
 [28] pbapply_1.4-3         goftest_1.2-2         stringr_1.4.0
 [31] digest_0.6.27         spatstat.utils_2.2-0  pkgconfig_2.0.3
 [34] htmltools_0.5.1.1     parallelly_1.27.0     fastmap_1.1.0
 [37] htmlwidgets_1.5.3     rlang_0.4.11          shiny_1.6.0
 [40] generics_0.1.0        zoo_1.8-9             jsonlite_1.7.2
 [43] ica_1.0-2             dplyr_1.0.7           magrittr_2.0.1
 [46] patchwork_1.1.1       Matrix_1.3-4          Rcpp_1.0.7
 [49] munsell_0.5.0         fansi_0.5.0           abind_1.4-5
 [52] reticulate_1.20       lifecycle_1.0.0       stringi_1.7.3
 [55] MASS_7.3-54           Rtsne_0.15            plyr_1.8.6
 [58] grid_4.0.3            parallel_4.0.3        listenv_0.8.0
 [61] promises_1.2.0.1      ggrepel_0.9.1         crayon_1.4.1
 [64] miniUI_0.1.1.1        deldir_0.2-10         lattice_0.20-44
 [67] cowplot_1.1.1         splines_4.0.3         tensor_1.5
 [70] hms_1.1.0             pillar_1.6.1          igraph_1.2.6
 [73] spatstat.geom_2.2-2   future.apply_1.7.0    reshape2_1.4.4
 [76] codetools_0.2-18      leiden_0.3.8          glue_1.4.2
 [79] data.table_1.14.0     png_0.1-7             vctrs_0.3.8
 [82] httpuv_1.6.1          gtable_0.3.0          RANN_2.6.1
 [85] purrr_0.3.4           spatstat.core_2.3-0   polyclip_1.10-0
 [88] tidyr_1.1.3           scattermore_0.7       future_1.21.0
 [91] ggplot2_3.3.5         mime_0.11             xtable_1.8-4
 [94] later_1.2.0           survival_3.2-11       viridisLite_0.4.0
 [97] tibble_3.1.2          cluster_2.1.2         globals_0.14.0
[100] fitdistrplus_1.1-5    ellipsis_0.3.2        ROCR_1.0-11

[xiaocong3333]

You should just use Bone to replace Bone-related