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bvieth / powsimR

Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.
https://bvieth.github.io/powsimR/
Artistic License 2.0
103 stars 23 forks source link

installation error #17

Closed Vivianstats closed 6 years ago

Vivianstats commented 6 years ago

Hello,

I got the following error while trying to install powsimR using the source package:

ERROR: dependency ‘DECENT’ is not available for package ‘powsimR’

I could not find DECENT either from CRAN or Bioconductor. Am I missing something here?

Thanks!

bvieth commented 6 years ago

Hello, DECENT is still on github. You can install it using require(devtools) devtools::install_github("cz-ye/DECENT")

Kind regards Beate

Vivianstats commented 6 years ago

Thanks Beate. Finally I was able to install powsimR. I was trying to reproduce the vignette example using the code:

TwoiLIF.params <- estimateParam(countData=kolodziejczk_cnts,
                                batchData = NULL,
                                spikeData = NULL,
                                spikeInfo = NULL,
                                Lengths = NULL,
                                MeanFragLengths = NULL,
                                Distribution = 'ZINB',
                                RNAseq = 'singlecell',
                                normalisation = 'scran',
                                sigma = 1.96,
                                NCores = NULL)

But I received the following error:

Error in scater::calculateQCMetrics(sce, nmads = 3) : 
  object must be an SCESet object.

Do you have any clues on this issue?

bvieth commented 6 years ago

Dear Vivian,

unfortunately I cannot reproduce the error that you have. I have experienced some hiccups before with SIngleCellExperiment R package. I solved it by reinstalling it and its dependencies. Did you try the manual installation description in the README file?

If possible I would try it also once with another example data set, e.g. scrbseq_gene_cnts or one of your own.

For comparison, here is my sessionInfo(): R version 3.4.4 (2018-03-15) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 16.04.4 LTS

Matrix products: default BLAS: /usr/lib/openblas-base/libblas.so.3 LAPACK: /usr/lib/libopenblasp-r0.2.18.so

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

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

other attached packages: [1] bindrcpp_0.2.2 BiocStyle_2.6.1 powsimR_1.1.1 gamlss.dist_5.0-4 [5] MASS_7.3-49

loaded via a namespace (and not attached): [1] genefilter_1.60.0 tximport_1.6.0
[3] spam_2.1-4 locfit_1.5-9.1
[5] slam_0.1-42 ZIM_1.0.3
[7] ggthemes_3.4.2 lattice_0.20-35
[9] doSNOW_1.0.16 EDASeq_2.12.0
[11] stats4_3.4.4 blob_1.1.1
[13] R.oo_1.21.0 withr_2.1.2
[15] foreign_0.8-69 registry_0.5
[17] readxl_1.0.0 matrixStats_0.53.1
[19] pkgmaker_0.22 stringr_1.3.0
[21] cellranger_1.1.0 munsell_0.4.3
[23] SCnorm_1.0.0 DESeq2_1.18.1
[25] codetools_0.2-15 SparseM_1.77
[27] ADGofTest_0.3 caret_6.0-79
[29] diffusionMap_1.1-0 lmtest_0.9-36
[31] tclust_1.3-1 RMTstat_0.3
[33] limma_3.34.9 densityClust_0.3
[35] annotate_1.56.2 apcluster_1.4.5
[37] brew_1.0-6 ellipse_0.4.1
[39] Rtsne_0.13 DESeq_1.30.0
[41] stringi_1.1.7 RcppRoll_0.2.2
[43] qlcMatrix_0.9.5 distillery_1.0-4
[45] grid_3.4.4 sandwich_2.4-0
[47] cluster_2.0.7-1 blockmodeling_0.3.0
[49] pbivnorm_0.6.0 ape_5.1
[51] pkgconfig_2.0.1 pheatmap_1.0.8
[53] prettyunits_1.0.2 data.table_1.10.4-3
[55] lubridate_1.7.4 ggridges_0.5.0
[57] energy_1.7-2 httr_1.3.1
[59] igraph_1.2.1 progress_1.1.2
[61] fastcluster_1.1.24 scone_1.2.0
[63] modeltools_0.2-21 haven_1.1.1
[65] amap_0.8-14 htmltools_0.3.6
[67] miniUI_0.1.1 viridisLite_0.3.0
[69] snow_0.4-2 fastICA_1.2-1
[71] yaml_2.1.18 baySeq_2.12.0
[73] prodlim_1.6.1 pillar_1.2.1
[75] hexbin_1.27.2 fitdistrplus_1.0-9
[77] glue_1.2.0 DBI_0.8
[79] BiocParallel_1.12.0 doRNG_1.6.6
[81] plyr_1.8.4 foreach_1.4.4
[83] bindr_0.1.1 outliers_0.14
[85] robustbase_0.92-8 dotCall64_0.9-5.2
[87] gtable_0.2.0 pcaMethods_1.70.0
[89] caTools_1.17.1 nonnest2_0.5-1
[91] latticeExtra_0.6-28 Biobase_2.38.0
[93] magic_1.5-8 crosstalk_1.0.0
[95] AnnotationDbi_1.40.0 broom_0.4.4
[97] rARPACK_0.11-0 SAVER_0.4.0
[99] arm_1.10-1 checkmate_1.8.5
[101] S4Vectors_0.16.0 IHW_1.6.0
[103] lpsymphony_1.7.1 FNN_1.1
[105] mnormt_1.5-5 png_0.1-7
[107] cidr_0.1.5 stabledist_0.7-1
[109] lazyeval_0.2.1 Formula_1.2-2
[111] crayon_1.3.4 bayesm_3.1-0.1
[113] RUVSeq_1.12.0 boot_1.3-20
[115] softImpute_1.4 xfun_0.1
[117] tidyselect_0.2.4 kernlab_0.9-25
[119] purrr_0.2.4 splines_3.4.4
[121] pcaPP_1.9-73 survival_2.41-3
[123] penalized_0.9-50 bit64_0.9-7
[125] segmented_0.5-3.0 rngtools_1.2.4
[127] extRemes_2.0-8 scde_2.6.0
[129] ROTS_1.6.0 fields_9.6
[131] MatrixModels_0.4-1 combinat_0.0-8
[133] R.methodsS3_1.7.1 SDMTools_1.1-221
[135] VGAM_1.0-5 UpSetR_1.3.3
[137] permute_0.9-4 pscl_1.5.2
[139] GenomeInfoDb_1.14.0 MBESS_4.4.3
[141] quantreg_5.35 fdrtool_1.2.15
[143] htmlTable_1.11.2 BPSC_0.99.1
[145] trimcluster_0.1-2 xtable_1.8-2
[147] DT_0.4 DelayedArray_0.4.1
[149] DDRTree_0.1.5 gdata_2.18.0
[151] ipred_0.9-6 vegan_2.5-1
[153] abind_1.4-5 ShortRead_1.36.1
[155] mime_0.5 tensorA_0.36
[157] rjson_0.2.15 ggplot2_2.2.1
[159] RMySQL_0.10.14 ggrepel_0.7.0
[161] numDeriv_2016.8-1 ade4_1.7-11
[163] tools_3.4.4 quadprog_1.5-5
[165] magrittr_1.5 rgl_0.99.16
[167] proxy_0.4-22 tibble_1.4.2
[169] dynamicTreeCut_1.63-1 drc_3.0-1
[171] Matrix_1.2-14 shinyBS_0.61
[173] DEDS_1.52.0 ggbeeswarm_0.6.0
[175] roxygen2_6.0.1 assertthat_0.2.0
[177] qvalue_2.10.0 mixtools_1.1.0
[179] clusterCrit_1.2.7 ica_1.0-1
[181] pbapply_1.3-4 NBPSeq_0.3.0
[183] rtracklayer_1.38.3 mgcv_1.8-23
[185] R.utils_2.6.0 metap_0.8
[187] BiocGenerics_0.24.0 HSMMSingleCell_0.112.0
[189] multcomp_1.4-8 zlibbioc_1.24.0
[191] commonmark_1.4 hwriter_1.3.2
[193] monocle_2.6.4 devtools_1.13.5
[195] rio_0.5.10 biomaRt_2.34.2
[197] geneplotter_1.56.0 TH.data_1.0-8
[199] ROCR_1.0-7 KernSmooth_2.23-15
[201] backports_1.1.2 scatterplot3d_0.3-41
[203] XVector_0.18.0 bit_1.1-12
[205] ggExtra_0.8 Rsamtools_1.30.0
[207] gplots_3.0.1 RANN_2.5.1
[209] ranger_0.9.0 openxlsx_4.0.17
[211] zingeR_0.1.0 shiny_1.0.5
[213] dtw_1.18-1 GenomicRanges_1.30.3
[215] maps_3.3.0 glmnet_2.0-16
[217] Seurat_2.3.0 viridis_0.5.1
[219] rstudioapi_0.7 minqa_1.2.4
[221] iterators_1.0.9 nlme_3.1-137
[223] sfsmisc_1.1-2 SummarizedExperiment_1.8.1 [225] lavaan_0.5-23.1097 gtools_3.5.0
[227] beeswarm_0.2.3 RcppNumerical_0.3-2
[229] Rook_1.1-1 reshape2_1.4.3
[231] rhdf5_2.22.0 colorspace_1.3-2
[233] compositions_1.40-1 base64enc_0.1-3
[235] GenomicFeatures_1.30.3 cobs_1.3-3
[237] XML_3.98-1.10 DrImpute_1.0
[239] ModelMetrics_1.1.0 sn_1.5-1
[241] NbClust_3.0 aroma.light_3.8.0
[243] RColorBrewer_1.1-2 Linnorm_2.2.0
[245] GenomeInfoDbData_1.0.0 dimRed_0.1.0
[247] Biostrings_2.46.0 timeDate_3043.102
[249] moments_0.14 evaluate_0.10.1
[251] memoise_1.1.0 iCOBRA_1.6.0
[253] coda_0.19-1 knitr_1.20
[255] IRanges_2.12.0 doParallel_1.0.11
[257] vipor_0.4.5 httpuv_1.3.6.2
[259] class_7.3-14 irlba_2.3.2
[261] lars_1.2 Rcpp_0.12.16
[263] acepack_1.4.1 formatR_1.5
[265] diptest_0.75-7 jsonlite_1.5
[267] Hmisc_4.1-1 RSpectra_0.12-0
[269] msir_1.3.1 digest_0.6.15
[271] gmodels_2.16.2 bookdown_0.7
[273] dplyr_0.7.4 ddalpha_1.3.2
[275] CompQuadForm_1.4.3 scDD_1.2.0
[277] rprojroot_1.3-2 gsl_1.9-10.3
[279] cowplot_0.9.2 Lmoments_1.2-3
[281] bitops_1.0-6 RSQLite_2.1.0
[283] tsne_0.1-3 EBSeq_1.18.0
[285] NOISeq_2.22.1 rmarkdown_1.9
[287] compiler_3.4.4 nnet_7.3-12
[289] statmod_1.4.30 RcppEigen_0.3.3.4.0
[291] scran_1.6.9 zoo_1.8-1
[293] minpack.lm_1.2-1 carData_3.0-1
[295] testthat_2.0.0 geometry_0.3-6
[297] rlang_0.2.0 manipulateWidget_0.9.0
[299] nloptr_1.0.4 prabclus_2.2-6
[301] SingleCellExperiment_1.0.0 fpc_2.1-11
[303] lava_1.6.1 pspline_1.0-18
[305] recipes_0.1.2 mvtnorm_1.0-7
[307] htmlwidgets_1.0 psych_1.8.3.3
[309] labeling_0.3 RcppArmadillo_0.8.400.0.0 [311] forcats_0.3.0 Cairo_1.5-9
[313] copula_0.999-18 flexmix_2.3-14
[315] curl_3.2 scater_1.6.3
[317] parallel_3.4.4 highr_0.6
[319] DEoptimR_1.0-8 edgeR_3.20.9
[321] scales_0.5.0 plotrix_3.7
[323] desc_1.1.1 RcppParallel_4.4.0
[325] CVST_0.2-1 lme4_1.1-17
[327] gridExtra_2.3 DECENT_0.2.0
[329] bbmle_1.0.20 RCurl_1.95-4.10
[331] ggdendro_0.1-20 DRR_0.0.3
[333] car_3.0-0 tidyr_0.8.0
[335] MAST_1.4.1 xml2_1.2.0
[337] shinydashboard_0.7.0 gower_0.1.2
[339] rpart_4.1-13 R6_2.2.2
[341] mclust_5.4 zinbwave_1.0.0
[343] GenomicAlignments_1.14.2

Vivianstats commented 6 years ago

Hello Beate,

Thank you very much for your information. I reinstalled SingleCellExperiment and tested the two example datasets, but I got a different error this time:

> TwoiLIF.params <- estimateParam(countData = kolodziejczk_cnts,
+                                 batchData = NULL,
+                                 spikeData = NULL,
+                                 spikeInfo = NULL,
+                                 Lengths = NULL,
+                                 MeanFragLengths = NULL,
+                                 Distribution = 'ZINB',
+                                 RNAseq = 'singlecell',
+                                 normalisation = 'scran',
+                                 sigma = 1.96,
+                                 NCores = NULL)

Using computeSumFactors, i.e. deconvolution over all cells!
Error in (function (classes, fdef, mtable)  : 
  unable to find an inherited method for function ‘computeSumFactors’ for signature ‘"SingleCellExperiment"’

I checked the version of SingleCellExperiment and we are both using 1.0.0. Any other thoughts on the reasons behind this issue? I'm also attaching my output of sessionInfo().

> sessionInfo()
R version 3.4.2 (2017-09-28)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.5 LTS

Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.0
LAPACK: /usr/lib/lapack/liblapack.so.3.0

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

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

other attached packages:
[1] powsimR_1.1.0       Biobase_2.36.2      BiocGenerics_0.22.1
[4] gamlss.dist_5.0-4   MASS_7.3-49        

loaded via a namespace (and not attached):
  [1] mixtools_1.1.0             softImpute_1.4            
  [3] minpack.lm_1.2-1           pbapply_1.3-4             
  [5] lattice_0.20-35            haven_1.1.1               
  [7] fastICA_1.2-1              mgcv_1.8-22               
  [9] penalized_0.9-50           blob_1.1.1                
 [11] survival_2.41-3            prodlim_1.6.1             
 [13] nloptr_1.0.4               DBI_0.8                   
 [15] R.utils_2.6.0              SingleCellExperiment_1.0.0
 [17] Linnorm_2.0.8              bindr_0.1.1               
 [19] zlibbioc_1.22.0            MatrixModels_0.4-1        
 [21] pspline_1.0-18             pcaMethods_1.68.0         
 [23] SDMTools_1.1-221           htmlwidgets_1.0           
 [25] mvtnorm_1.0-7              tclust_1.3-1              
 [27] scater_1.6.3               irlba_2.3.2               
 [29] DEoptimR_1.0-8             lars_1.2                  
 [31] Rcpp_0.12.16               KernSmooth_2.23-15        
 [33] DT_0.4                     gdata_2.18.0              
 [35] DDRTree_0.1.5              DelayedArray_0.2.7        
 [37] limma_3.34.9               vegan_2.5-1               
 [39] CVST_0.2-1                 RcppParallel_4.4.0        
 [41] Hmisc_4.1-1                ShortRead_1.34.2          
 [43] apcluster_1.4.5            RSpectra_0.12-0           
 [45] msir_1.3.1                 mnormt_1.5-5              
 [47] ranger_0.9.0               digest_0.6.15             
 [49] png_0.1-7                  qlcMatrix_0.9.5           
 [51] cidr_0.1.5                 cowplot_0.9.2             
 [53] glmnet_2.0-16              pkgconfig_2.0.1           
 [55] gridBase_0.4-7             gower_0.1.2               
 [57] ggbeeswarm_0.6.0           iterators_1.0.9           
 [59] minqa_1.2.4                lavaan_0.5-23.1097        
 [61] SummarizedExperiment_1.6.5 spam_2.1-4                
 [63] beeswarm_0.2.3             modeltools_0.2-21         
 [65] RcppNumerical_0.3-2        zoo_1.8-1                 
 [67] tidyselect_0.2.4           clusterCrit_1.2.7         
 [69] ZIM_1.0.3                  reshape2_1.4.3            
 [71] purrr_0.2.4                kernlab_0.9-25            
 [73] ica_1.0-1                  pcaPP_1.9-73              
 [75] EDASeq_2.10.0              viridisLite_0.3.0         
 [77] snow_0.4-2                 rtracklayer_1.36.6        
 [79] rlang_0.2.0                hexbin_1.27.2             
 [81] NbClust_3.0                glue_1.2.0                
 [83] metap_0.8                  RColorBrewer_1.1-2        
 [85] registry_0.5               fpc_2.1-11                
 [87] matrixStats_0.53.1         stringr_1.3.0             
 [89] pkgmaker_0.22              lava_1.6.1                
 [91] fields_9.6                 DESeq2_1.16.1             
 [93] recipes_0.1.2              SparseM_1.77              
 [95] httpuv_1.3.6.2             class_7.3-14              
 [97] BPSC_0.99.1                RMTstat_0.3               
 [99] annotate_1.54.0            jsonlite_1.5              
[101] XVector_0.16.0             bit_1.1-12                
[103] mime_0.5                   gridExtra_2.3             
[105] gplots_3.0.1               Rsamtools_1.28.0          
[107] zingeR_0.1.0               stringi_1.1.7             
[109] gmodels_2.16.2             RcppRoll_0.2.2            
[111] gsl_1.9-10.3               quadprog_1.5-5            
[113] bitops_1.0-6               maps_3.3.0                
[115] RSQLite_2.1.0              tidyr_0.8.0               
[117] pheatmap_1.0.8             data.table_1.10.4-3       
[119] DEDS_1.50.0                energy_1.7-2              
[121] rstudioapi_0.7             GenomicAlignments_1.12.2  
[123] sfsmisc_1.1-2              nlme_3.1-131              
[125] qvalue_2.8.0               scran_1.4.5               
[127] fastcluster_1.1.24         scone_1.0.0               
[129] locfit_1.5-9.1             miniUI_0.1.1              
[131] cobs_1.3-3                 R.oo_1.21.0               
[133] prabclus_2.2-6             segmented_0.5-3.0         
[135] readxl_1.0.0               dimRed_0.1.0              
[137] timeDate_3043.102          ROTS_1.4.0                
[139] munsell_0.4.3              cellranger_1.1.0          
[141] R.methodsS3_1.7.1          moments_0.14              
[143] hwriter_1.3.2              visNetwork_2.0.3          
[145] caTools_1.17.1             codetools_0.2-15          
[147] coda_0.19-1                magic_1.5-8               
[149] GenomeInfoDb_1.12.3        diffusionMap_1.1-0        
[151] vipor_0.4.5                lmtest_0.9-36             
[153] htmlTable_1.11.2           rARPACK_0.11-0            
[155] xtable_1.8-2               SAVER_0.4.0               
[157] ROCR_1.0-7                 diptest_0.75-7            
[159] scatterplot3d_0.3-41       lpsymphony_1.4.1          
[161] abind_1.4-5                FNN_1.1                   
[163] RANN_2.5.1                 CompQuadForm_1.4.3        
[165] GenomicRanges_1.28.6       rgl_0.96.0                
[167] tibble_1.4.2               ggdendro_0.1-20           
[169] cluster_2.0.6              Seurat_2.3.0              
[171] Matrix_1.2-14              lubridate_1.7.4           
[173] ggridges_0.5.0             NOISeq_2.20.0             
[175] shinydashboard_0.7.0       mclust_5.4                
[177] igraph_1.2.1               RcppEigen_0.3.3.4.0       
[179] slam_0.1-42                testthat_2.0.0            
[181] doSNOW_1.0.16              geometry_0.3-6            
[183] htmltools_0.3.6            NMF_0.21.0                
[185] yaml_2.1.18                GenomicFeatures_1.28.5    
[187] plotly_4.7.1               XML_3.98-1.9              
[189] ModelMetrics_1.1.0         DrImpute_1.0              
[191] foreign_0.8-69             withr_2.1.2               
[193] fitdistrplus_1.0-9         BiocParallel_1.10.1       
[195] aroma.light_3.6.0          bit64_0.9-7               
[197] rngtools_1.2.4             doRNG_1.6.6               
[199] foreach_1.4.4              robustbase_0.92-8         
[201] outliers_0.14              scde_2.4.1                
[203] Biostrings_2.44.2          combinat_0.0-8            
[205] memoise_1.1.0              VGAM_1.0-5                
[207] nonnest2_0.5-1             forcats_0.3.0             
[209] rio_0.5.10                 geneplotter_1.54.0        
[211] permute_0.9-4              caret_6.0-79              
[213] curl_3.2                   fdrtool_1.2.15            
[215] trimcluster_0.1-2          acepack_1.4.1             
[217] edgeR_3.20.9               checkmate_1.8.5           
[219] tensorA_0.36               DECENT_0.2.0              
[221] ellipse_0.4.1              ggplot2_2.2.1             
[223] rjson_0.2.15               openxlsx_4.0.17           
[225] ggrepel_0.7.0              distillery_1.0-4          
[227] ade4_1.7-11                dtw_1.18-1                
[229] scDD_1.0.0                 stabledist_0.7-1          
[231] Lmoments_1.2-3             tools_3.4.2               
[233] sandwich_2.4-0             magrittr_1.5              
[235] RCurl_1.95-4.10            proxy_0.4-22              
[237] car_3.0-0                  pbivnorm_0.6.0            
[239] ape_5.1                    bayesm_3.1-0.1            
[241] EBSeq_1.16.0               httr_1.3.1                
[243] assertthat_0.2.0           boot_1.3-20               
[245] R6_2.2.2                   nnet_7.3-12               
[247] tximport_1.4.0             genefilter_1.58.1         
[249] gtools_3.5.0               statmod_1.4.30            
[251] Rook_1.1-1                 rhdf5_2.20.0              
[253] splines_3.4.2              carData_3.0-1             
[255] colorspace_1.3-2           amap_0.8-14               
[257] stats4_3.4.2               NBPSeq_0.3.0              
[259] compositions_1.40-1        base64enc_0.1-3           
[261] baySeq_2.10.0              pillar_1.2.1              
[263] sn_1.5-1                   HSMMSingleCell_0.110.0    
[265] bindrcpp_0.2.2             GenomeInfoDbData_0.99.0   
[267] plyr_1.8.4                 extRemes_2.0-8            
[269] dotCall64_0.9-5.2          gtable_0.2.0              
[271] SCnorm_0.99.7              monocle_2.6.1             
[273] psych_1.8.3.3              knitr_1.20                
[275] RcppArmadillo_0.8.400.0.0  latticeExtra_0.6-28       
[277] biomaRt_2.32.1             IRanges_2.10.5            
[279] ADGofTest_0.3              copula_0.999-18           
[281] Cairo_1.5-9                doParallel_1.0.11         
[283] pscl_1.5.2                 flexmix_2.3-13            
[285] quantreg_5.35              AnnotationDbi_1.38.2      
[287] broom_0.4.4                scales_0.5.0              
[289] arm_1.10-1                 backports_1.1.2           
[291] IHW_1.4.0                  S4Vectors_0.14.7          
[293] densityClust_0.3           ipred_0.9-6               
[295] lme4_1.1-17                brew_1.0-6                
[297] DESeq_1.28.0               Rtsne_0.13                
[299] dplyr_0.7.4                shiny_1.0.5               
[301] ddalpha_1.3.2              grid_3.4.2                
[303] numDeriv_2016.8-1          bbmle_1.0.20              
[305] lazyeval_0.2.1             dynamicTreeCut_1.63-1     
[307] Formula_1.2-2              tsne_0.1-3                
[309] blockmodeling_0.3.0        DRR_0.0.3                 
[311] MAST_1.2.1                 RUVSeq_1.10.0             
[313] viridis_0.5.1              rpart_4.1-11              
[315] zinbwave_1.0.0             compiler_3.4.2
bvieth commented 6 years ago

Dear Vivian,

I think I might have found it. Since the error occurred in the call to scran computeSumFactors() and you have version 1.4.5 and I have 1.6.9 and I know that scran made the change to SingleCellExperiment 'quite' recently, my guess is that the error is due to this. My harsh solution would be to install/update the Bioconductor packages.

I am sorry for the inconvenience. Please let me know if that helped, I know how much of a hassle Bioconductor can sometimes be....

Kind regards Beate

bvieth commented 6 years ago

Dear Vivian,

I will close the issue for now. Feel free to reopen if my suggestions did not resolve the issue for you.

Kind regards Beate