SofieVG
commented
4 years ago Hi Emma,
Thanks for trying out our tool! I have not yet solved the issue in the code, but I can already explain what is happening. If the parameter plot is TRUE, the tool will also generate an overview figure, with the different CV values for the upper part of the image, but underneath also the different metacluster percentages for each of the files for the number of metaclusters chosen in the model. This can help to investigate in which cluster the variation is happening and about which kind of percentages the issue is about. However, this part of the plot fails if the number of clusters used in the model is not present in the numbers you pass to test. So e.g. c(seq(5, 25, by = 3), 25) will work in your case, or you could adapt the FlowSOM parameters to choose the number of metaclusters as one that you have in this new list (e.g. 20 or 23). If you are just interested in the CV values themselves and not in the plot you could also put plot to FALSE in which case he will not run into the problematic code.
I know this presents just workarounds for now, but I hope this already helps a bit.
All the best, Sofie
On Thu, 25 Jun 2020 at 14:49, Emma notifications@github.com wrote:
Hello, First of all, thank you for putting this together, batch normalisation in CyTOF data has been a large problem in the community for a while now. I have come across some unexpected behaviour when running testCV. It runs for some values of the cluster_values argument but gives an error under different values. For example: cvs <- testCV(fsom, cluster_values = seq(5,25,by=2)) runs fine but not
cvs <- testCV(fsom, cluster_values = seq(5,25,by=3)) Error in array(x, c(length(x), 1L), if (!is.null(names(x))) list(names(x), : 'data' must be of a vector type, was 'NULL'
I was wondering if you have any insight on what could be causing the problem. Many thanks, Emma
R version 3.6.3 (2020-02-29) Platform: x86_64-pc-linux-gnu (64-bit) Running under: CentOS release 6.10 (Final)
Matrix products: default BLAS/LAPACK: /usr/lib64/libopenblas-r0.3.3.so
locale: [1] LC_CTYPE=en_GB.ISO-8859-1 LC_NUMERIC=C LC_TIME=en_GB.ISO-8859-1 LC_COLLATE=en_GB.ISO-8859-1 [5] LC_MONETARY=en_GB.ISO-8859-1 LC_MESSAGES=en_GB.ISO-8859-1 LC_PAPER=en_GB.ISO-8859-1 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_GB.ISO-8859-1 LC_IDENTIFICATION=C
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] flowCore_1.52.1 dplyr_1.0.0 CytoNorm_0.0.5
loaded via a namespace (and not attached): [1] Biobase_2.46.0 splines_3.6.3 jsonlite_1.6.1 ConsensusClusterPlus_1.50.0 R.utils_2.9.2 [6] ellipse_0.4.2 gtools_3.8.2 RcppParallel_5.0.1 stats4_3.6.3 latticeExtra_0.6-29 [11] RBGL_1.62.1 flowWorkspace_3.34.1 yaml_2.2.1 robustbase_0.93-6 pillar_1.4.4 [16] lattice_0.20-41 glue_1.3.2 digest_0.6.25 RColorBrewer_1.1-2 colorspace_1.4-1 [21] ggcyto_1.14.1 Matrix_1.2-18 R.oo_1.23.0 plyr_1.8.6 pcaPP_1.9-73 [26] XML_3.99-0.3 pkgconfig_2.0.3 pheatmap_1.0.12 tsne_0.1-3 fda_5.1.4 [31] zlibbioc_1.32.0 purrr_0.3.4 corpcor_1.6.9 mvtnorm_1.1-1 scales_1.1.1 [36] jpeg_0.1-8.1 openCyto_1.24.0 flowStats_3.44.0 tibble_3.0.1 generics_0.0.2 [41] ggplot2_3.3.1 ellipsis_0.3.1 flowViz_1.50.0 BiocGenerics_0.32.0 hexbin_1.28.1 [46] mnormt_1.5-6 magrittr_1.5 crayon_1.3.4 IDPmisc_1.1.20 mclust_5.4.6 [51] ks_1.11.7 R.methodsS3_1.8.0 MASS_7.3-51.6 graph_1.64.0 tools_3.6.3 [56] data.table_1.12.8 ncdfFlow_2.32.0 flowClust_3.24.0 lifecycle_0.2.0 matrixStats_0.56.0 [61] stringr_1.4.0 munsell_0.5.0 cluster_2.1.0 compiler_3.6.3 rlang_0.4.6 [66] grid_3.6.3 igraph_1.2.5 base64enc_0.1-3 gtable_0.3.0 rrcov_1.5-2 [71] R6_2.4.1 gridExtra_2.3 clue_0.3-57 FlowSOM_1.18.0 CytoML_1.12.1 [76] KernSmooth_2.23-17 Rgraphviz_2.30.0 stringi_1.4.6 parallel_3.6.3 Rcpp_1.0.4.6 [81] vctrs_0.3.0 png_0.1-7 DEoptimR_1.0-8 tidyselect_1.1.0 ```
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emmanuelaaaaa
ghost
Hello, First of all, thank you for putting this together, batch normalisation in CyTOF data has been a large problem in the community for a while now. I have come across some unexpected behaviour when running testCV. It runs for some values of the cluster_values argument but gives an error under different values. For example:
cvs <- testCV(fsom, cluster_values = seq(5,25,by=2))runs fine but notI was wondering if you have any insight on what could be causing the problem. Many thanks, Emma