newSCESet(countData=all.counts) function not working
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Entering edit mode
bk11 • 0
@bk11-19547
Last seen 3.0 years ago

Hi I am running through this tutorial https://f1000research.com/articles/5-2122/v1. But I got this error. I m new to single cell experiment. Why newSCESet(countData=all.counts) function not working? I will appreciate your help. Thanks. I have used these codes:

library(R.utils)
gunzip("GSE61533_HTSEQ_count_results.xls.gz", remove=FALSE, overwrite=TRUE)
library(gdata)
all.counts <- read.xls(’GSE61533_HTSEQ_count_results.xls’, sheet=1, header=TRUE, row.names=1)
library(scater)
sce <- newSCESet(countData=all.counts)

It gave me error:

Error in newSCESet(countData = all.counts) : 
  could not find function "newSCESet"


sessionInfo()

R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
 [1] simpleSingleCell_1.4.1                 TENxBrainData_1.2.0                    HDF5Array_1.10.1                      
 [4] rhdf5_2.26.2                           BiocNeighbors_1.0.0                    BiocFileCache_1.6.0                   
 [7] dbplyr_1.3.0                           DropletUtils_1.2.2                     scRNAseq_1.8.0                        
[10] TxDb.Mmusculus.UCSC.mm10.ensGene_3.4.0 GenomicFeatures_1.34.1                 edgeR_3.24.3                          
[13] cluster_2.0.7-1                        dynamicTreeCut_1.63-1                  pheatmap_1.0.12                       
[16] limma_3.38.3                           scran_1.10.2                           org.Mm.eg.db_3.7.0                    
[19] AnnotationDbi_1.44.0                   readxl_1.2.0                           destiny_2.12.0                        
[22] mvoutlier_2.0.9                        sgeostat_1.0-27                        Rtsne_0.15                            
[25] knitr_1.21                             BiocStyle_2.10.0                       scater_1.10.1                         
[28] ggplot2_3.1.0                          SingleCellExperiment_1.4.1             SummarizedExperiment_1.12.0           
[31] DelayedArray_0.8.0                     BiocParallel_1.16.5                    matrixStats_0.54.0                    
[34] Biobase_2.42.0                         GenomicRanges_1.34.0                   GenomeInfoDb_1.18.1                   
[37] IRanges_2.16.0                         S4Vectors_0.20.1                       BiocGenerics_0.28.0                   
[40] gdata_2.18.0                           R.utils_2.7.0                          R.oo_1.22.0                           
[43] R.methodsS3_1.7.1                      updateR_0.1                            magrittr_1.5                          
[46] stringr_1.3.1                          rvest_0.3.2                            xml2_1.2.0                            
[49] dplyr_0.7.8                            usethis_1.4.0                          devtools_2.0.1                        

loaded via a namespace (and not attached):
  [1] rappdirs_0.3.1                rtracklayer_1.42.1            ggthemes_4.0.1               
  [4] prabclus_2.2-7                GGally_1.4.0                  bit64_0.9-7                  
  [7] data.table_1.12.0             RCurl_1.95-4.11               callr_3.1.1                  
 [10] RSQLite_2.1.1                 proxy_0.4-22                  bit_1.1-14                   
 [13] httpuv_1.4.5.1                assertthat_0.2.0              viridis_0.5.1                
 [16] xfun_0.4                      hms_0.4.2                     promises_1.0.1               
 [19] evaluate_0.12                 DEoptimR_1.0-8                progress_1.2.0               
 [22] igraph_1.2.2                  DBI_1.0.0                     reshape_0.8.8                
 [25] purrr_0.2.5                   selectr_0.4-1                 backports_1.1.3              
 [28] trimcluster_0.1-2.1           sROC_0.1-2                    biomaRt_2.38.0               
 [31] remotes_2.0.2                 TTR_0.23-4                    abind_1.4-5                  
 [34] RcppEigen_0.3.3.5.0           withr_2.1.2                   robustbase_0.93-3            
 [37] vcd_1.4-4                     GenomicAlignments_1.18.1      xts_0.11-2                   
 [40] prettyunits_1.0.2             mclust_5.4.2                  ExperimentHub_1.8.0          
 [43] lazyeval_0.2.1                laeken_0.5.0                  crayon_1.3.4                 
 [46] pkgconfig_2.0.2               zCompositions_1.1.2           vipor_0.4.5                  
 [49] pkgload_1.0.2                 nnet_7.3-12                   bindr_0.1.1                  
 [52] rlang_0.3.1                   diptest_0.75-7                pls_2.7-0                    
 [55] AnnotationHub_2.14.2          cellranger_1.1.0              rprojroot_1.3-2              
 [58] lmtest_0.9-36                 Matrix_1.2-15                 carData_3.0-2                
 [61] Rhdf5lib_1.4.2                boot_1.3-20                   zoo_1.8-4                    
 [64] beeswarm_0.2.3                processx_3.2.1                viridisLite_0.3.0            
 [67] bitops_1.0-6                  Biostrings_2.50.2             blob_1.1.1                   
 [70] DelayedMatrixStats_1.4.0      scales_1.0.0                  memoise_1.1.0                
 [73] plyr_1.8.4                    zlibbioc_1.28.0               compiler_3.5.1               
 [76] RColorBrewer_1.1-2            rrcov_1.4-7                   Rsamtools_1.34.0             
 [79] cli_1.0.1                     XVector_0.22.0                ps_1.3.0                     
 [82] MASS_7.3-51.1                 tidyselect_0.2.5              stringi_1.2.4                
 [85] forcats_0.3.0                 yaml_2.2.0                    locfit_1.5-9.1               
 [88] grid_3.5.1                    tools_3.5.1                   rio_0.5.16                   
 [91] rstudioapi_0.9.0              foreign_0.8-71                gridExtra_2.3                
 [94] smoother_1.1                  scatterplot3d_0.3-41          digest_0.6.18                
 [97] BiocManager_1.30.4            shiny_1.2.0                   fpc_2.1-11.1                 
[100] bindrcpp_0.2.2                Rcpp_1.0.0                    car_3.0-2                    
[103] later_0.7.5                   httr_1.4.0                    kernlab_0.9-27               
[106] colorspace_1.4-0              XML_3.98-1.16                 fs_1.2.6                     
[109] truncnorm_1.0-8               splines_3.5.1                 statmod_1.4.30               
[112] sp_1.3-1                      flexmix_2.3-14                sessioninfo_1.1.1            
[115] xtable_1.8-3                  modeltools_0.2-22             R6_2.3.0                     
[118] NADA_1.6-1                    mime_0.6                      pillar_1.3.1                 
[121] htmltools_0.3.6               glue_1.3.0                    VIM_4.7.0                    
[124] cvTools_0.3.2                 class_7.3-15                  interactiveDisplayBase_1.20.0
[127] pkgbuild_1.0.2                pcaPP_1.9-73                  mvtnorm_1.0-8                
[130] lattice_0.20-38               tibble_2.0.1                  curl_3.3                     
[133] ggbeeswarm_0.6.0              gtools_3.8.1                  zip_1.0.0                    
[136] openxlsx_4.1.0                survival_2.43-3               rmarkdown_1.11               
[139] desc_1.2.0                    munsell_0.5.0                 e1071_1.7-0.1                
[142] GenomeInfoDbData_1.2.0        haven_2.0.0                   reshape2_1.4.3               
[145] gtable_0.2.0                  robCompositions_2.0.9
Single cell experiment Single cell RNAseq • 1.5k views
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Entering edit mode
Aaron Lun ★ 28k
@alun
Last seen 6 hours ago
The city by the bay

Please read the latest version of the workflow at https://bioconductor.org/packages/release/workflows/html/simpleSingleCell.html.

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0
Entering edit mode

I have tried this workflow and still getting the same error

Error in newSCESet(countData = all.counts) : 
  could not find function "newSCESet"
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2
Entering edit mode

You must be following along with an older version of the workflow than the current one (which Aaron linked to). As far as I know, the newSCEset stuff has been completely replaced by using SingleCellExperiment objects.

You should make sure that you are reading the "release" version of these workflows, as well as the current (release) version of the Bioconductor ecosystem (v3.8) -- which you can check using the following R code packageVersion("BiocVersion")[,1:2].

(edit)

I see from you sessionInfo that you are using the release versions of bioc software -- so I'm guessing you are just looking at outdated code somewhere ... again, you should be using the relase version of the simpleSingleCell worfklow (if that's the code you are following along with).

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