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scde issue #88

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mark0237 opened this issue May 27, 2021 · 4 comments
Open

scde issue #88

mark0237 opened this issue May 27, 2021 · 4 comments

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@mark0237
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I keep getting this error when trying to run scde.error.models() or knn on the data from the scde tutorial.

Error in checkSlotAssignment(object, name, value) :
assignment of an object of class “expression” is not valid for slot ‘defineComponent’ in an object of class “FLXMRglmC”; is(value, "expressionOrfunction") is not TRUE

I have already tried to downgrade to the flexmix_2.3-13 version. I also reinstalled the latest version of SCDE several time. Unfortunately I cannot downgrade SCDE because my mac does not allow to do it from the Terminal.

Literally, I have been with SCDe issues for hours. Please, help.

@mark0237
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It is a pity I cannot get to use this package with my data as well. I found it perfect for what I would like to analyze since I am not really an expert on scRNA seq data.

@mark0237
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Hi there!

I CANT BELIEVE I COULD FINALLY SOLVE THIS PROBLEM!

I HAVE (RE)-INSTALLED THE FOLLOWING VERSIONS

gfortran 10.2 for Catalina (macOS 10.15)
https://github.com/fxcoudert/gfortran-for-macOS/releases/tag/10.2

RCCARMADILLO OLDER VERSION
install.packages("https://cran.r-project.org/src/contrib/Archive/RcppArmadillo/RcppArmadillo_0.9.900.3.0.tar.gz", repos=NULL, type="source")

SCDE VERSION 1.99.1 AND FLEXMIX 2.3-13 OLD
require(devtools)
devtools::install_version('flexmix', '2.3-13')
devtools::install_github('hms-dbmi/scde', build_vignettes = FALSE)

I HOPE THIS WILL BE OF A HELP FOR SOMEONE WHO HAVE BEEN STRUGGLING FOR HOURS AS ME

@oyshilin
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I'm facing this problem as well, is this method useful for windows user?

@Zhihao-Huang
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I got errors when I run scde.error.models using the R package from BiocManager.

o.ifm <- scde.error.models(counts = cd, groups = sg, n.cores = 1, threshold.segmentation = TRUE, save.crossfit.plots = FALSE, save.model.plots = FALSE, verbose = 1)

Error in components[[i]]@logLik :
no applicable method for @ applied to an object of class "function"

Downgrading RcppArmadillo to version 0.9.900.3.0 and using the developing version of scde really solved my problem. Thanks! @mark0237

install.packages("https://cran.r-project.org/src/contrib/Archive/RcppArmadillo/RcppArmadillo_0.9.900.3.0.tar.gz", repos=NULL, type="source") require(devtools) devtools::install_version('flexmix', '2.3-13') devtools::install_github('hms-dbmi/scde', build_vignettes = FALSE)

o.ifm <- scde.error.models(counts = cd, groups = sg, n.cores = 1, threshold.segmentation = TRUE, save.crossfit.plots = FALSE, save.model.plots = FALSE, verbose = 1)
cross-fitting cells.
number of pairs: 190
number of pairs: 190
total number of pairs: 380
cross-fitting 380 pairs:
building individual error models.
adjusting library size based on 2000 entries
fitting ESC models:
1 : ESC_10
Classification: weighted
1 Log-likelihood : -18286.7108
2 Log-likelihood : -18218.8464
3 Log-likelihood : -18158.4491
4 Log-likelihood : -18142.6904
5 Log-likelihood : -18142.2715
...

sessionInfo()

Details

R version 4.3.1 (2023-06-16)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.6 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3; LAPACK version 3.9.0

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

time zone: Asia/Shanghai
tzcode source: system (glibc)

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

other attached packages:
[1] scde_2.27.1 flexmix_2.3-13 lattice_0.22-4

loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 RcppArmadillo_0.9.900.3.0 rstudioapi_0.15.0
[4] jsonlite_1.8.7 magrittr_2.0.3 spatstat.utils_3.0-5
[7] modeltools_0.2-23 vctrs_0.6.4 ROCR_1.0-11
[10] Cairo_1.6-1 spatstat.explore_3.2-5 htmltools_0.5.6.1
[13] sctransform_0.4.1 parallelly_1.37.1 KernSmooth_2.23-22
[16] htmlwidgets_1.6.2 ica_1.0-3 plyr_1.8.9
[19] plotly_4.10.3 zoo_1.8-12 igraph_1.5.1
[22] mime_0.12 lifecycle_1.0.4 pkgconfig_2.0.3
[25] Matrix_1.6-4 R6_2.5.1 fastmap_1.1.1
[28] fitdistrplus_1.1-11 future_1.33.2 shiny_1.7.5.1
[31] digest_0.6.36 pcaMethods_1.92.0 colorspace_2.1-0
[34] patchwork_1.2.0.9000 Seurat_5.0.1 tensor_1.5
[37] RSpectra_0.16-1 irlba_2.3.5.1 progressr_0.14.0
[40] extRemes_2.1-4 fansi_1.0.5 spatstat.sparse_3.0-2
[43] httr_1.4.7 polyclip_1.10-6 RMTstat_0.3.1
[46] abind_1.4-5 mgcv_1.9-0 compiler_4.3.1
[49] brew_1.0-8 BiocParallel_1.34.2 fastDummies_1.7.3
[52] MASS_7.3-60 quantreg_5.97 rjson_0.2.21
[55] tools_4.3.1 lmtest_0.9-40 httpuv_1.6.11
[58] future.apply_1.11.2 nnet_7.3-19 goftest_1.2-3
[61] glue_1.7.0 nlme_3.1-163 promises_1.2.1
[64] grid_4.3.1 Rtsne_0.16 cluster_2.1.4
[67] reshape2_1.4.4 generics_0.1.3 gtable_0.3.4
[70] spatstat.data_3.0-1 tidyr_1.3.0 data.table_1.14.8
[73] sp_2.1-4 utf8_1.2.4 BiocGenerics_0.46.0
[76] spatstat.geom_3.2-7 RcppAnnoy_0.0.21 ggrepel_0.9.4
[79] RANN_2.6.1 pillar_1.9.0 stringr_1.5.0
[82] Lmoments_1.3-1 spam_2.10-0 RcppHNSW_0.5.0
[85] limma_3.56.2 later_1.3.1 splines_4.3.1
[88] dplyr_1.1.3 Rook_1.2 survival_3.5-7
[91] deldir_1.0-9 SparseM_1.81 tidyselect_1.2.0
[94] locfit_1.5-9.8 miniUI_0.1.1.1 pbapply_1.7-2
[97] gridExtra_2.3 edgeR_3.42.4 scattermore_1.2
[100] stats4_4.3.1 Biobase_2.60.0 matrixStats_1.0.0
[103] stringi_1.7.12 lazyeval_0.2.2 codetools_0.2-19
[106] tibble_3.2.1 cli_3.6.3 uwot_0.1.16
[109] xtable_1.8-4 reticulate_1.34.0 munsell_0.5.0
[112] Rcpp_1.0.13 globals_0.16.3 spatstat.random_3.2-1
[115] png_0.1-8 parallel_4.3.1 MatrixModels_0.5-2
[118] ellipsis_0.3.2 ggplot2_3.4.4 dotCall64_1.1-1
[121] listenv_0.9.1 viridisLite_0.4.2 scales_1.3.0
[124] ggridges_0.5.4 SeuratObject_5.0.1 leiden_0.4.3
[127] purrr_1.0.2 distillery_1.2-1 rlang_1.1.4
[130] cowplot_1.1.1

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