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A tool for the unsupervised clustering of cells from single cell RNA-Seq experiments

Home Page: http://bioconductor.org/packages/SC3

License: GNU General Public License v3.0

R 95.51% C++ 4.49%
bioconductor-package human-cell-atlas single-cell-rna-seq

sc3's Introduction

Q: What is this?
A: SC3 is a tool for the unsupervised clustering of cells from single cell RNA-Seq experiments. SC3 main page is on BioConductor.

Q: How to install/run SC3?
A: Please follow the SC3 manual from its BioConductor page.

If you would like to install the latest development version of SC3 please install it from the GitHub repository:

install.packages("devtools")
devtools::install_github("hemberg-lab/SC3")

Q: Where can I report bugs, comments, issues or suggestions?
A: Please use this page.

Q: Where can I ask questions about SC3?
A: Please use this page.

Q: Is SC3 published?
A: Yes, SC3 is published in Nature Methods.

Q: What is SC3 licence?
A: GPL-3

sc3's People

Contributors

dtenenba avatar hpages avatar kayla-morrell avatar nh3 avatar nturaga avatar pati-ni avatar shians avatar tallulandrews avatar vobencha avatar wikiselev avatar

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sc3's Issues

'sc3' is not a slot in class "SCESet"

Hello,

Here's what happens when I follow your tutorial with my data:

library(scater)
library(sc3)

sce <- newSCESet(
  countData = counts,
  phenoData = new("AnnotatedDataFrame", data = meta)
)

sce <- calculateQCMetrics(sce)

sce <- sc3(
  object  = sce,
  ks      = 5:16,
  biology = TRUE,
  n_cores = 20,
  svm_max = 1e4
)
Setting SC3 parameters...
Error in (function (cl, name, valueClass)  :
‘sc3’ is not a slot in class “SCESet”
In addition: Warning message:
Removed 6774 rows containing non-finite values (stat_density).
class(sce)
[1] "SCESet"
attr(,"package")
[1] "scater"

Session info

> sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux Server release 6.5 (Santiago)

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] stats4    grid      parallel  stats     graphics  grDevices utils
 [8] datasets  methods   base

other attached packages:
 [1] SC3_1.3.15            scater_1.0.4          WGCNA_1.51
 [4] dynamicTreeCut_1.63-1 viridis_0.3.4         stringr_1.2.0
 [7] sitools_1.4           scde_1.99.4           flexmix_2.3-13
[10] lattice_0.20-34       scales_0.4.1          Rtsne_0.11
[13] reshape2_1.4.2        readr_1.0.0           RColorBrewer_1.1-2
[16] pheatmap_1.0.8        org.Hs.eg.db_3.3.0    MASS_7.3-45
[19] limma_3.28.21         liger_0.1             largeVis_0.1.10.2
[22] Matrix_1.2-7.1        GO.db_3.3.0           AnnotationDbi_1.34.4
[25] IRanges_2.6.1         S4Vectors_0.10.3      Biobase_2.32.0
[28] BiocGenerics_0.18.0   gridExtra_2.2.1       ggrepel_0.6.5
[31] ggplot2_2.2.1         fastcluster_1.1.22    dplyr_0.5.0
[34] doMC_1.3.4            iterators_1.0.8       foreach_1.4.3
[37] dendsort_0.3.3        data.table_1.10.4     BiocParallel_1.6.6

loaded via a namespace (and not attached):
 [1] minqa_1.2.4               colorspace_1.3-1
 [3] rjson_0.2.15              class_7.3-14
 [5] modeltools_0.2-21         htmlTable_1.7
 [7] RcppArmadillo_0.7.700.0.0 MatrixModels_0.4-1
 [9] mvtnorm_1.0-6             codetools_0.2-15
[11] splines_3.3.2             extRemes_2.0-8
[13] Lmoments_1.2-3            tximport_1.0.3
[15] doParallel_1.0.10         robustbase_0.92-7
[17] impute_1.46.0             knitr_1.15.1
[19] Formula_1.2-1             nloptr_1.0.4
[21] Cairo_1.5-9               pbkrtest_0.4-6
[23] cluster_2.0.5             shinydashboard_0.5.3
[25] shiny_1.0.1               rrcov_1.4-3
[27] assertthat_0.1            lazyeval_0.2.0
[29] acepack_1.4.1             htmltools_0.3.5
[31] quantreg_5.29             tools_3.3.2
[33] gtable_0.2.0              doRNG_1.6
[35] Rcpp_0.12.10              gdata_2.17.0
[37] preprocessCore_1.34.0     nlme_3.1-128
[39] lme4_1.1-12               mime_0.5
[41] pacman_0.4.1              rngtools_1.2.4
[43] WriteXLS_4.0.0            gtools_3.5.0
[45] XML_3.98-1.5              distillery_1.0-2
[47] DEoptimR_1.0-8            edgeR_3.14.0
[49] zlibbioc_1.18.0           pcaMethods_1.64.0
[51] rhdf5_2.16.0              SparseM_1.74
[53] memoise_1.0.0             pkgmaker_0.22
[55] biomaRt_2.28.0            rpart_4.1-10
[57] latticeExtra_0.6-28       stringi_1.1.2
[59] RSQLite_1.1               highr_0.6
[61] Rook_1.1-1                pcaPP_1.9-61
[63] e1071_1.6-8               caTools_1.17.1
[65] matrixStats_0.51.0        bitops_1.0-6
[67] RMTstat_0.3               ROCR_1.0-7
[69] labeling_0.3              plyr_1.8.4
[71] magrittr_1.5              R6_2.2.0
[73] gplots_3.0.1              Hmisc_4.0-0
[75] DBI_0.5-1                 whisker_0.3-2
[77] foreign_0.8-67            mgcv_1.8-16
[79] survival_2.40-1           RCurl_1.95-4.8
[81] nnet_7.3-12               tibble_1.2
[83] janitor_0.2.1             car_2.1-4
[85] KernSmooth_2.23-15        digest_0.6.12
[87] xtable_1.8-2              httpuv_1.3.3
[89] dbscan_0.9-8              brew_1.0-6
[91] munsell_0.4.3             registry_0.3

sc3_plot_de_genes does not work

Hi,
I would like to run sc3_plot_de_genes but it threw an error

> sc3_result<- sc3(sce, ks = 5:25, biology = TRUE, K_estimator = TRUE)
> sc3_plot_de_genes(sc3_result, k = 7)
Error in seq.int(rx[1L], rx[2L], length.out = nb) :
  'to' must be a finite number
> sessionInfo()
R version 3.4.0 (2017-04-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] SC3_1.4.2

loaded via a namespace (and not attached):
 [1] bitops_1.0-6         matrixStats_0.52.2   bit64_0.9-7
 [4] doParallel_1.0.10    RColorBrewer_1.1-2   tools_3.4.0
 [7] doRNG_1.6.6          R6_2.2.2             KernSmooth_2.23-15
[10] vipor_0.4.5          DBI_0.7              lazyeval_0.2.0
[13] BiocGenerics_0.22.0  colorspace_1.3-2     gridExtra_2.2.1
[16] bit_1.1-12           compiler_3.4.0       Biobase_2.36.2
[19] pkgmaker_0.22        caTools_1.17.1       scales_0.4.1
[22] DEoptimR_1.0-8       mvtnorm_1.0-6        robustbase_0.92-7
[25] stringr_1.2.0        digest_0.6.12        rrcov_1.4-3
[28] scater_1.4.0         pkgconfig_2.0.1      htmltools_0.3.6
[31] WriteXLS_4.0.0       limma_3.32.2         rlang_0.1.1
[34] RSQLite_2.0          shiny_1.0.3          bindr_0.1
[37] gtools_3.5.0         dplyr_0.7.1          RCurl_1.95-4.8
[40] magrittr_1.5         Matrix_1.2-10        Rcpp_0.12.11
[43] ggbeeswarm_0.5.3     munsell_0.4.3        S4Vectors_0.14.3
[46] viridis_0.4.0        stringi_1.1.5        edgeR_3.18.1
[49] zlibbioc_1.22.0      rhdf5_2.20.0         gplots_3.0.1
[52] plyr_1.8.4           grid_3.4.0           blob_1.1.0
[55] parallel_3.4.0       gdata_2.18.0         shinydashboard_0.6.1
[58] lattice_0.20-35      locfit_1.5-9.1       rjson_0.2.15
[61] rngtools_1.2.4       reshape2_1.4.2       codetools_0.2-15
[64] biomaRt_2.32.1       stats4_3.4.0         XML_3.98-1.9
[67] glue_1.1.1           data.table_1.10.4    httpuv_1.3.3
[70] foreach_1.4.3        gtable_0.2.0         assertthat_0.2.0
[73] ggplot2_2.2.1        mime_0.5             xtable_1.8-2
[76] e1071_1.6-8          class_7.3-14         pcaPP_1.9-72
[79] viridisLite_0.2.0    tibble_1.3.3         pheatmap_1.0.8
[82] iterators_1.0.8      AnnotationDbi_1.38.1 registry_0.3
[85] beeswarm_0.2.3       memoise_1.1.0        IRanges_2.10.2
[88] tximport_1.4.0       bindrcpp_0.2         cluster_2.0.6
[91] ROCR_1.0-7

Other plot functions (sc3_plot_markers, sc3_plot_expression etc.) seem to work.
Could you please give me some advice?

Thanks in advance,

column annotations and list of genes

Hi, I have two feature requests: adding an option to include sample/column labels to the SC3 plots, and also having a separate method to visualize a list of genes of interest. I think I can implement this, would you accept a PR?

[suggestion]maybe it could be better just using the SingleCellExperiment class

Hi Vladimir, I have used your SC3 in several projects and it is great. I have a question regarding your SC3class. I look at the code and it just adds a sc3 slot in the object. Have you think about just using the SingleCellExperiment class directly instead of creating a new class. You can put the sc3 slot into the int_metadata and access it through sce@int_metadata@sc3. This is what I did for my scPipe package. I think the SingleCellExperiment also put package information into int_metadata.

Another thing that confuses me is the feature_symbol column in the rowData. I did not have that column at first and it gives me an error when I plot marker genes. The error message is not obvious so it took me some time to figure out I don't have this column. I think it could be better to add a check when you use the feature_symbol and use rowname as default when it didn't exist.

sc3_plot_de_genes duplicate row names

Maybe I am doing something wrong, but for some values of k I am getting the following error when calling sc3_plot_de_genes:

Warning message:
“non-unique value when setting 'row.names': ‘Lilrb4a’”
Error in `row.names<-.data.frame`(`*tmp*`, value = value): duplicate 'row.names' are not allowed
Traceback:

1. sc3_plot_de_genes(sce_named, k = k)
2. sc3_plot_de_genes(sce_named, k = k)
3. `rownames<-`(`*tmp*`, value = names(de_genes))
4. `row.names<-`(`*tmp*`, value = value)
5. `row.names<-.data.frame`(`*tmp*`, value = value)
6. stop("duplicate 'row.names' are not allowed")

Is it possible that there is a bug somewhere, maybe if a gene is called as differentially expressed for multiple clusters somehow?

sc3_plot_silhouette generate an empty plot

Hi,
I am applying SC3 on a big single cell RNAseq data set with about 3,000 cells and 27,000 genes.

Running sc3 itself is OK.

SC3 <- sc3(my_data, ks = 2:20, biology = TRUE, k_estimator = FALSE, pct_dropout_max = 95, gene_filter = TRUE, pct_dropout_min = 5)

However, I encounter several issues while generating the report.
First, the sc3_plot_silhouette(SC3, k=5) returned me an empty plot
image

The plot is still 'informative' since the silhouette width of each cluster and the average silhouette width are still visible. If sc3_plot_silhouette can not handle the large data set, is there an easy way to get rid of the blank silhouette?

Thanks in advance.

session info

  • R version 3.4.2
  • Bioconductor 3.6
  • scater_1.6.0
  • SC3_1.6.0

first error: Error in transf[, 1:hash.table$n_dim[i]] : incorrect number of dimensions

I tried SC3 on a dataset and it worked without giving any error. However, when I used it on this dataset specifically, it's throwing the error. Can I know what does it mean? The only obvious difference is that this dataset has very little number of cells (<20)

sce <- sc3(sce, ks = 2:4, biology = TRUE,gene_filter=F)

Setting SC3 parameters...
Calculating distances between the cells...
Performing transformations and calculating eigenvectors...
Performing k-means clustering...
Error in checkForRemoteErrors(val) :
36 nodes produced errors; first error: Error in transf[, 1:hash.table$n_dim[i]] : incorrect number of dimensions

sessionInfo()
R version 3.4.0 (2017-04-21)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252

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

other attached packages:
[1] scran_1.6.7 BiocParallel_1.12.0 scater_1.6.2 SingleCellExperiment_1.0.0
[5] SummarizedExperiment_1.8.1 DelayedArray_0.4.1 matrixStats_0.53.0 GenomicRanges_1.30.1
[9] GenomeInfoDb_1.14.0 IRanges_2.12.0 S4Vectors_0.16.0 ggplot2_2.2.1
[13] tidyr_0.8.0 SC3_1.7.7 Biobase_2.38.0 BiocGenerics_0.24.0

loaded via a namespace (and not attached):
[1] ggbeeswarm_0.6.0 colorspace_1.3-2 rjson_0.2.15 class_7.3-14 dynamicTreeCut_1.63-1
[6] XVector_0.18.0 DT_0.4 bit64_0.9-7 AnnotationDbi_1.40.0 mvtnorm_1.0-7
[11] codetools_0.2-15 tximport_1.6.0 doParallel_1.0.11 robustbase_0.92-8 cluster_2.0.6
[16] pheatmap_1.0.8 shinydashboard_0.6.1 shiny_1.0.5 rrcov_1.4-3 compiler_3.4.0
[21] httr_1.3.1 assertthat_0.2.0 Matrix_1.2-9 lazyeval_0.2.1 limma_3.34.6
[26] htmltools_0.3.6 prettyunits_1.0.2 tools_3.4.0 bindrcpp_0.2 igraph_1.1.2
[31] gtable_0.2.0 glue_1.2.0 GenomeInfoDbData_1.0.0 reshape2_1.4.3 dplyr_0.7.4
[36] doRNG_1.6.6 Rcpp_0.12.15 gdata_2.18.0 iterators_1.0.9 stringr_1.2.0
[41] mime_0.5 rngtools_1.2.4 gtools_3.5.0 WriteXLS_4.0.0 statmod_1.4.30
[46] XML_3.98-1.9 edgeR_3.20.7 DEoptimR_1.0-8 zlibbioc_1.24.0 zoo_1.8-1
[51] scales_0.5.0 rhdf5_2.22.0 RColorBrewer_1.1-2 memoise_1.1.0 gridExtra_2.3
[56] pkgmaker_0.22 biomaRt_2.34.2 stringi_1.1.6 RSQLite_2.0 pcaPP_1.9-73
[61] foreach_1.4.4 e1071_1.6-8 caTools_1.17.1 rlang_0.1.6 pkgconfig_2.0.1
[66] bitops_1.0-6 lattice_0.20-35 ROCR_1.0-7 purrr_0.2.4 bindr_0.1
[71] labeling_0.3 htmlwidgets_1.0 cowplot_0.9.2 bit_1.1-12 tidyselect_0.2.3
[76] plyr_1.8.4 magrittr_1.5 R6_2.2.2 gplots_3.0.1 DBI_0.7
[81] pillar_1.1.0 RCurl_1.95-4.10 tibble_1.4.2 KernSmooth_2.23-15 viridis_0.4.1
[86] progress_1.1.2 locfit_1.5-9.1 grid_3.4.0 data.table_1.10.4-3 blob_1.1.0
[91] FNN_1.1 digest_0.6.15 xtable_1.8-2 httpuv_1.3.5 munsell_0.4.3
[96] registry_0.5 beeswarm_0.2.3 viridisLite_0.3.0 vipor_0.4.5

Thanks in advance!
Y

Update the vignette

At the moment there is no description of SC3 functionality. The vignette should have complete
instructions (along with screenshots) for using the GUI.

Some specific things:

add description of RSelenium

Update Docs

Make sure the docs are updated for sc3() and sc3_interactive() functions.

compute time

Hi, I ran 500 cells scRNA-seq data (gene_filter = TRUE, and ks = 5:15) on my local computer (MacBook Pro (2016), OS Sierra 10.12.5 with 2.5 GHz Intel Core i7 processor, 16 GB 1600 MHz DDR3 of RAM). It took 3hrs to finish the run. Could you share with me the command or parameters you used to achieve sc3 clustering 5k cells in 20min as mentioned in the paper?

Thanks!

'x' must be an array of at least two dimensions

Hi Vlad,

Hope you're doing well.

I'm running SC3 on a dataset (first time using SingleCellExperiments with it) and get the following rather opaque error:

sce_cnv_no_X_use <- sc3(sce_cnv_no_X_use, ks = 2:3, biology = TRUE, n_cores = 2, gene_filter = FALSE)
> Setting SC3 parameters...
> Error in rowSums(dataset == 0) : 
 > 'x' must be an array of at least two dimensions

any idea what might be causing this? The traceback looks like

> traceback()
6: stop("'x' must be an array of at least two dimensions")
5: rowSums(dataset == 0)
4: sc3_prepare(object, gene_filter, pct_dropout_min, pct_dropout_max, 
       d_region_min, d_region_max, svm_num_cells, svm_train_inds, 
       svm_max, n_cores, kmeans_nstart, kmeans_iter_max, rand_seed)
3: sc3_prepare(object, gene_filter, pct_dropout_min, pct_dropout_max, 
       d_region_min, d_region_max, svm_num_cells, svm_train_inds, 
       svm_max, n_cores, kmeans_nstart, kmeans_iter_max, rand_seed)
2: sc3(sce_cnv_no_X_use, ks = 2:3, biology = TRUE, n_cores = 2, 
       gene_filter = FALSE)
1: sc3(sce_cnv_no_X_use, ks = 2:3, biology = TRUE, n_cores = 2, 
       gene_filter = FALSE)

and my sessioninfo looks like

R version 3.4.2 (2017-09-28)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

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

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

other attached packages:
 [1] SC3_1.7.2                  BiocInstaller_1.28.0       bindrcpp_0.2              
 [4] clonealign_0.99.0          goseq_1.30.0               geneLenDataBase_1.14.0    
 [7] BiasedUrn_1.07             ggforce_0.1.1              ggbeeswarm_0.6.0          
[10] ggmcmc_1.1                 edgeR_3.20.1               limma_3.34.0              
[13] ggrepel_0.7.0              cowplot_0.9.2              glue_1.2.0                
[16] tidyr_0.7.2                dplyr_0.7.4                readr_1.1.1               
[19] scran_1.6.2                BiocParallel_1.12.0        scater_1.6.0              
[22] SingleCellExperiment_1.0.0 SummarizedExperiment_1.8.1 DelayedArray_0.4.1        
[25] matrixStats_0.52.2         GenomicRanges_1.30.1       GenomeInfoDb_1.14.0       
[28] IRanges_2.12.0             S4Vectors_0.16.0           ggplot2_2.2.1             
[31] Biobase_2.38.0             BiocGenerics_0.24.0       

loaded via a namespace (and not attached):
  [1] plyr_1.8.4               igraph_1.1.2             lazyeval_0.2.1          
  [4] shinydashboard_0.6.1     splines_3.4.2            digest_0.6.13           
  [7] foreach_1.4.4            htmltools_0.3.6          viridis_0.4.0           
 [10] GO.db_3.5.0              gdata_2.18.0             magrittr_1.5            
 [13] memoise_1.1.0            cluster_2.0.6            doParallel_1.0.11       
 [16] ROCR_1.0-7               Biostrings_2.46.0        prettyunits_1.0.2       
 [19] colorspace_1.3-2         rrcov_1.4-3              blob_1.1.0              
 [22] WriteXLS_4.0.0           crayon_1.3.4             RCurl_1.95-4.8          
 [25] tximport_1.6.0           roxygen2_6.0.1           bindr_0.1               
 [28] zoo_1.8-0                iterators_1.0.9          registry_0.5            
 [31] gtable_0.2.0             zlibbioc_1.24.0          XVector_0.18.0          
 [34] DEoptimR_1.0-8           scales_0.5.0.9000        mvtnorm_1.0-6           
 [37] pheatmap_1.0.8           rngtools_1.2.4           DBI_0.7                 
 [40] GGally_1.3.2             Rcpp_0.12.14             viridisLite_0.2.0       
 [43] xtable_1.8-2             progress_1.1.2           units_0.4-6             
 [46] bit_1.1-12               DT_0.2                   htmlwidgets_0.9         
 [49] httr_1.3.1               FNN_1.1                  gplots_3.0.1            
 [52] RColorBrewer_1.1-2       pkgconfig_2.0.1          reshape_0.8.7           
 [55] XML_3.98-1.9             locfit_1.5-9.1           dynamicTreeCut_1.63-1   
 [58] tidyselect_0.2.3         labeling_0.3             rlang_0.1.4             
 [61] reshape2_1.4.2           AnnotationDbi_1.40.0     munsell_0.4.3           
 [64] tools_3.4.2              RSQLite_2.0              devtools_1.13.4         
 [67] stringr_1.2.0            yaml_2.1.16              knitr_1.17              
 [70] bit64_0.9-7              robustbase_0.92-8        caTools_1.17.1          
 [73] purrr_0.2.4              doRNG_1.6.6              nlme_3.1-131            
 [76] mime_0.5                 xml2_1.1.1               biomaRt_2.34.1          
 [79] compiler_3.4.2           rstudioapi_0.7           curl_3.0                
 [82] beeswarm_0.2.3           e1071_1.6-8              testthat_2.0.0          
 [85] tibble_1.3.4             statmod_1.4.30           tweenr_0.1.5            
 [88] pcaPP_1.9-72             stringi_1.1.5            GenomicFeatures_1.30.0  
 [91] lattice_0.20-35          Matrix_1.2-11            commonmark_1.4          
 [94] data.table_1.10.4-3      bitops_1.0-6             httpuv_1.3.5            
 [97] rtracklayer_1.38.0       R6_2.2.2                 RMySQL_0.10.13          
[100] KernSmooth_2.23-15       gridExtra_2.3            vipor_0.4.5             
[103] codetools_0.2-15         MASS_7.3-47              gtools_3.5.0            
[106] assertthat_0.2.0         rhdf5_2.22.0             pkgmaker_0.22           
[109] rjson_0.2.15             withr_2.1.1.9000         GenomicAlignments_1.14.0
[112] Rsamtools_1.30.0         GenomeInfoDbData_0.99.1  mgcv_1.8-20             
[115] hms_0.3                  udunits2_0.13            grid_3.4.2              
[118] class_7.3-14             git2r_0.19.0             shiny_1.0.5    

Many thanks,

Kieran

Check random seed

Looks like the seed is changed somewhere in the code, so sometimes results cannot be reproduced...

Loading SC3 in R 3.4.1

Hello

I used SC3 previously and I recently update R from 3.3 to 3.4 and I am having problem with loading SC3.

When I try to load SC3 after scater, i get following error:

`> library(scater)

library(SC3)
Error: package or namespace load failed for ‘SC3’:
object ‘fData<-’ is not exported by 'namespace:scater`

Any idea how to fix this?

Thank you

Harry

Add and explain non-interactive analysis

  1. Integrate with SCESet class of Bioconductor
  2. Update vignettes and explain how to perform the analysis without interactive session
  3. Add more names and description to the object returned by sc3(interactivity = FALSE)

Error in !isSpike(object) : invalid argument type

Hi,

I guess this is somehow related with #53 or 10X data. I tried to run sc3 on a 10x data set. Based on #53 , I manually convert both counts slot and logcounts slot to a standard/regular matrix. However, I am getting another error

Setting SC3 parameters...
Error in !isSpike(object) : invalid argument type

It seems the issue came from gene_filter. Set gene_filter = FALSE will make the code work. 10X data most likely will have no Spike-in. For my data set, isSpike(mySingleCellExperiment) will return NULL, which is the expected behavior.

Here is my session info:

R version 3.4.2 (2017-09-28)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 9 (stretch)

Matrix products: default
BLAS/LAPACK: /usr/lib/libopenblasp-r0.2.19.so

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

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

other attached packages:
 [1] SC3_1.7.2                  Rtsne_0.13                 cowplot_0.9.1              scater_1.6.1              
 [5] SingleCellExperiment_1.0.0 SummarizedExperiment_1.8.0 DelayedArray_0.4.0         matrixStats_0.52.2        
 [9] GenomicRanges_1.30.0       GenomeInfoDb_1.14.0        IRanges_2.12.0             S4Vectors_0.16.0          
[13] ggplot2_2.2.1              Biobase_2.38.0             BiocGenerics_0.24.0        knitr_1.17                

loaded via a namespace (and not attached):
 [1] bitops_1.0-6            bit64_0.9-7             RColorBrewer_1.1-2      doParallel_1.0.11       progress_1.1.2         
 [6] tools_3.4.2             doRNG_1.6.6             R6_2.2.2                KernSmooth_2.23-15      vipor_0.4.5            
[11] DBI_0.7                 lazyeval_0.2.1          colorspace_1.3-2        gridExtra_2.3           prettyunits_1.0.2      
[16] bit_1.1-12              compiler_3.4.2          pkgmaker_0.22           caTools_1.17.1          scales_0.5.0           
[21] mvtnorm_1.0-6           DEoptimR_1.0-8          robustbase_0.92-8       stringr_1.2.0           digest_0.6.12          
[26] XVector_0.18.0          rrcov_1.4-3             pkgconfig_2.0.1         htmltools_0.3.6         WriteXLS_4.0.0         
[31] limma_3.34.4            rlang_0.1.2             RSQLite_2.0             shiny_1.0.5             bindr_0.1              
[36] gtools_3.5.0            dplyr_0.7.4             RCurl_1.95-4.8          magrittr_1.5            GenomeInfoDbData_0.99.1
[41] Matrix_1.2-11           Rcpp_0.12.14            ggbeeswarm_0.6.0        munsell_0.4.3           viridis_0.4.0          
[46] stringi_1.1.5           yaml_2.1.14             edgeR_3.20.1            zlibbioc_1.24.0         rhdf5_2.22.0           
[51] gplots_3.0.1            plyr_1.8.4              grid_3.4.2              blob_1.1.0              gdata_2.18.0           
[56] shinydashboard_0.6.1    lattice_0.20-35         locfit_1.5-9.1          rjson_0.2.15            rngtools_1.2.4         
[61] reshape2_1.4.2          codetools_0.2-15        biomaRt_2.34.0          XML_3.98-1.9            glue_1.2.0             
[66] data.table_1.10.4-3     httpuv_1.3.5            foreach_1.4.4           gtable_0.2.0            assertthat_0.2.0       
[71] mime_0.5                xtable_1.8-2            e1071_1.6-8             pcaPP_1.9-72            class_7.3-14           
[76] viridisLite_0.2.0       pheatmap_1.0.8          tibble_1.3.4            iterators_1.0.9         AnnotationDbi_1.40.0   
[81] registry_0.5            beeswarm_0.2.3          memoise_1.1.0           tximport_1.6.0          bindrcpp_0.2           
[86] cluster_2.0.6           ROCR_1.0-7             

Thanks in advance,
Yi-Chien.

No 'dimnames' attribute for array

Running SC3 on a dataset, post QC and normalisation. The clustering completes, followed by calc_biology, but upon attempting to plot_de_genes or plot_markers, I get the following error:

Error in dataset[names(de_genes), , drop = FALSE] :
no 'dimnames' attribute for array

The fData of the dataset is properly updated with markers_clusts, markers_padj, and de_padj columns, which leads me to believe that it might be a plotting error?

Error in silhouette.default(clusts, diss) : object 'sildist' not found

I see you are trying to address this in some of the commits, but I am getting the following error when running the example vignette. I have tried running this in a number of ways including the Bioconductor and development branches. Any ideas?

Error in silhouette.default(clusts, diss) : object 'sildist' not found
Error in silhouette.default(clusts, diss) : object 'sildist' not found
Error in silhouette.default(clusts, diss) : object 'sildist' not found
Error in checkForRemoteErrors(val) :
3 nodes produced errors; first error: Error in silhouette.default(clusts, diss) : object 'sildist' not found

sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.2 LTS

Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0

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 methods
[8] base

other attached packages:
[1] SC3_1.5.2 scater_1.4.0 ggplot2_2.2.1
[4] Biobase_2.36.2 BiocGenerics_0.22.0 knitr_1.16

loaded via a namespace (and not attached):
[1] bitops_1.0-6 matrixStats_0.52.2 devtools_1.13.3
[4] bit64_0.9-7 doParallel_1.0.10 RColorBrewer_1.1-2
[7] httr_1.2.1 tools_3.4.1 doRNG_1.6.6
[10] R6_2.2.2 KernSmooth_2.23-15 vipor_0.4.5
[13] DBI_0.7 lazyeval_0.2.0 colorspace_1.3-2
[16] withr_2.0.0 gridExtra_2.2.1 bit_1.1-12
[19] curl_2.8.1 compiler_3.4.1 git2r_0.19.0
[22] pkgmaker_0.22 labeling_0.3 caTools_1.17.1
[25] scales_0.4.1 mvtnorm_1.0-6 DEoptimR_1.0-8
[28] robustbase_0.92-7 stringr_1.2.0 digest_0.6.12
[31] rrcov_1.4-3 pkgconfig_2.0.1 htmltools_0.3.6
[34] WriteXLS_4.0.0 limma_3.32.5 rlang_0.1.1
[37] RSQLite_2.0 BiocInstaller_1.26.0 shiny_1.0.3
[40] bindr_0.1 gtools_3.5.0 dplyr_0.7.2
[43] RCurl_1.95-4.8 magrittr_1.5 Matrix_1.2-10
[46] Rcpp_0.12.12 ggbeeswarm_0.6.0 munsell_0.4.3
[49] S4Vectors_0.14.3 viridis_0.4.0 stringi_1.1.5
[52] edgeR_3.18.1 zlibbioc_1.22.0 rhdf5_2.20.0
[55] gplots_3.0.1 plyr_1.8.4 grid_3.4.1
[58] blob_1.1.0 gdata_2.18.0 shinydashboard_0.6.1
[61] lattice_0.20-35 locfit_1.5-9.1 tcltk_3.4.1
[64] rjson_0.2.15 rngtools_1.2.4 reshape2_1.4.2
[67] codetools_0.2-15 biomaRt_2.32.1 stats4_3.4.1
[70] XML_3.98-1.9 glue_1.1.1 data.table_1.10.4
[73] httpuv_1.3.5 foreach_1.4.3 gtable_0.2.0
[76] assertthat_0.2.0 mime_0.5 xtable_1.8-2
[79] e1071_1.6-8 pcaPP_1.9-72 class_7.3-14
[82] viridisLite_0.2.0 tibble_1.3.3 pheatmap_1.0.8
[85] iterators_1.0.8 AnnotationDbi_1.38.2 registry_0.3
[88] beeswarm_0.2.3 memoise_1.1.0 IRanges_2.10.2
[91] tximport_1.4.0 bindrcpp_0.2 cluster_2.0.6
[94] ROCR_1.0-7

sc3(s) giving error

Hello,
When I try to run sc3(sceObj, ks = 11, biology = TRUE), it gives the following error

Error in `[<-`(`*tmp*`, , paste0("sc3_", k, "_markers_clusts"), value = c(NA, : 7635 rows in value to replace 1 rows

where I have 7635 genes in the sceObj

Could you please let me know why the error and how to fix it?

Cluster coverage feature

Add a feature that will allow us to identify coverage in each cluster to help identify clusters corresponding to batches with lower/higher coverage.

Installation failed

I was installing the SC3 from github via Rstudio on my Mac, because I want to use the lastest version used in the scRNA.seq.course. However, the installing did not work.

The installation command and the session info are as followings.

> devtools::install_github("hemberg-lab/SC3")
Downloading GitHub repo hemberg-lab/SC3@master
from URL https://api.github.com/repos/hemberg-lab/SC3/zipball/master
Installing SC3
'/Library/Frameworks/R.framework/Resources/bin/R' --no-site-file --no-environ --no-save  \
  --no-restore --quiet CMD INSTALL  \
  '/private/var/folders/z9/zcddb9jx5bz343w2nfzzc3500000gn/T/RtmpRQrrrD/devtools112e0c43ed85/hemberg-lab-SC3-a8216c5'  \
  --library='/Library/Frameworks/R.framework/Versions/3.4/Resources/library' --install-tests 

* installing *source* package ‘SC3’ ...
** libs
clang++ -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG  -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/Rcpp/include" -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/RcppArmadillo/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c RcppExports.cpp -o RcppExports.o
clang++ -I/Library/Frameworks/R.framework/Resources/include -DNDEBUG  -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/Rcpp/include" -I"/Library/Frameworks/R.framework/Versions/3.4/Resources/library/RcppArmadillo/include" -I/usr/local/include   -fPIC  -Wall -g -O2  -c cppFunctions.cpp -o cppFunctions.o
clang++ -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -single_module -multiply_defined suppress -L/Library/Frameworks/R.framework/Resources/lib -L/usr/local/lib -o SC3.so RcppExports.o cppFunctions.o -L/Library/Frameworks/R.framework/Resources/lib -lRlapack -L/Library/Frameworks/R.framework/Resources/lib -lRblas -L/usr/local/gfortran/lib/gcc/x86_64-apple-darwin15/6.1.0 -L/usr/local/gfortran/lib -lgfortran -lquadmath -lm -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
ld: warning: directory not found for option '-L/usr/local/gfortran/lib/gcc/x86_64-apple-darwin15/6.1.0'
ld: warning: directory not found for option '-L/usr/local/gfortran/lib'
ld: library not found for -lgfortran
clang: error: linker command failed with exit code 1 (use -v to see invocation)
make: *** [SC3.so] Error 1
ERROR: compilation failed for package ‘SC3’
* removing ‘/Library/Frameworks/R.framework/Versions/3.4/Resources/library/SC3’
Installation failed: Command failed (1)
> sessionInfo()
R version 3.4.0 (2017-04-21)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.5

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/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] stats4    parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] RUVSeq_1.10.0              EDASeq_2.10.0              ShortRead_1.34.0          
 [4] GenomicAlignments_1.12.1   SummarizedExperiment_1.6.3 DelayedArray_0.2.7        
 [7] matrixStats_0.52.2         Rsamtools_1.28.0           GenomicRanges_1.28.3      
[10] GenomeInfoDb_1.12.1        Biostrings_2.44.1          XVector_0.16.0            
[13] IRanges_2.10.2             S4Vectors_0.14.3           BiocParallel_1.10.1       
[16] edgeR_3.18.1               limma_3.32.2               pheatmap_1.0.8            
[19] scater_1.4.0               ggplot2_2.2.1              Biobase_2.36.2            
[22] BiocGenerics_0.22.0        RColorBrewer_1.1-2         BiocInstaller_1.26.0      

loaded via a namespace (and not attached):
 [1] bitops_1.0-6            devtools_1.13.2         httr_1.2.1              tools_3.4.0            
 [5] R6_2.2.1                vipor_0.4.5             DBI_0.6-1               lazyeval_0.2.0         
 [9] colorspace_1.3-2        withr_1.0.2             gridExtra_2.2.1         curl_2.6               
[13] compiler_3.4.0          git2r_0.18.0            pacman_0.4.6            rtracklayer_1.36.3     
[17] labeling_0.3            scales_0.4.1            genefilter_1.58.1       DESeq_1.28.0           
[21] stringr_1.2.0           digest_0.6.12           R.utils_2.5.0           htmltools_0.3.6        
[25] rlang_0.1.1             RSQLite_1.1-2           shiny_1.0.3             hwriter_1.3.2          
[29] dplyr_0.5.0             R.oo_1.21.0             RCurl_1.95-4.8          magrittr_1.5           
[33] GenomeInfoDbData_0.99.0 Matrix_1.2-10           Rcpp_0.12.11            ggbeeswarm_0.5.3       
[37] munsell_0.4.3           viridis_0.4.0           R.methodsS3_1.7.1       stringi_1.1.5          
[41] MASS_7.3-47             zlibbioc_1.22.0         rhdf5_2.20.0            plyr_1.8.4             
[45] grid_3.4.0              shinydashboard_0.6.0    lattice_0.20-35         splines_3.4.0          
[49] GenomicFeatures_1.28.2  annotate_1.54.0         locfit_1.5-9.1          knitr_1.16             
[53] rjson_0.2.15            geneplotter_1.54.0      reshape2_1.4.2          biomaRt_2.32.0         
[57] XML_3.98-1.7            latticeExtra_0.6-28     data.table_1.10.4       httpuv_1.3.3           
[61] gtable_0.2.0            assertthat_0.2.0        aroma.light_3.6.0       mime_0.5               
[65] xtable_1.8-2            survival_2.41-3         viridisLite_0.2.0       tibble_1.3.3           
[69] AnnotationDbi_1.38.1    beeswarm_0.2.3          memoise_1.1.0           tximport_1.4.0       

ubuntu 16.04 SC3 1.4.2 or 1.5.1 bugs

when i run SC3 on my PC,it comes up a bugs , can not find 'sildist' object.can you help me?
my error is Error in silhouette.default(clusts, diss) : can not find object 'sildist';

unable to generate sc3_plot_cluster_stability plot in loop

Hi,

I have a script which attempts to generate a pdf file that includes the sc3_plot_cluster_stabilty plot and it appears that if the function is used in a loop, the plot is not able to be generated. However, if the function is used outside of the loop, the plot is able to be generated.

I am currently running the function in a script through the commandline using the sample dataset that was provided.

pdf("fout.pdf")
for(i in num_of_clusters ){
  sc3_plot_cluster_stability(sce, k = i)
  sc3_plot_consensus(sce, k=i )
  sc3_plot_silhouette(sce, k=i)
  sc3_plot_expression(sce, k = i)
}

In the code snippet, the num_of_clusters is a user provided value. This returns a pdf with all of the plots except the cluster stability. Perhaps someone has insight on this?

I would be happy to email/provide the script and my commandline arguments if that would help.

Add column colouring to sc3_plot_markers

It would be really nice to have an additional argument passed to sc3_plot_markers that accepted either an N length vector (for N cells) or a column name of pData(sceset) that added column colouring to the resulting heatmap, so you can compare the consistency of the clustering with a known covariate.

sc3_plot_de_genes and sc3_plot_markers not working

Hi,

Somehow sc3 doesn't like my data set :)
Both sc3_plot_de_genes and sc3_plot_markers are not not working.
The command I used to run sc3 was provided in #45

sc3_plot_de_genes

sc3_plot_de_genes(SC3, k = 5)

Error in seq.default(min(x, na.rm = T), max(x, na.rm = T), length.out = n + : 'from' must be a finite number

8.stop("'from' must be a finite number")
7.seq.default(min(x, na.rm = T), max(x, na.rm = T), length.out = n + 1)
6.seq(min(x, na.rm = T), max(x, na.rm = T), length.out = n + 1)
5.generate_breaks(as.vector(mat), length(color))
4.(function (mat, color = colorRampPalette(rev(brewer.pal(n = 7, name = "RdYlBu")))(100), kmeans_k = NA, breaks = NA, border_color = "grey60", cellwidth = NA, cellheight = NA, scale = "none", cluster_rows = TRUE, cluster_cols = TRUE, clustering_distance_rows = "euclidean", ...
3.do.call(pheatmap::pheatmap, c(list(dataset[names(de_genes), , drop = FALSE], show_colnames = FALSE, cluster_rows = FALSE, cluster_cols = hc, cutree_cols = k, annotation_row = row_ann, cellheight = 10), list(annotation_col = ann)[add_ann_col]))

sc3_plot_markers

sc3_plot_markers(SCExp.filtered.normalized.tSNE.SC3, k = 5)

Error: subscript contains invalid names

10.stop(wmsg(...), call. = FALSE)
9..subscript_error("subscript contains invalid ", what)
8.NSBS(i, x, exact = exact, strict.upper.bound = !allow.append, allow.NAs = allow.NAs)
7.NSBS(i, x, exact = exact, strict.upper.bound = !allow.append, allow.NAs = allow.NAs)
6.normalizeSingleBracketSubscript(j, xstub)
5.rowData(object)[, c(paste0("sc3_", k, "_markers_clusts"), paste0("sc3_", k, "_markers_auroc"), paste0("sc3_", k, "_markers_padj"), "feature_symbol")]
4.rowData(object)[, c(paste0("sc3_", k, "_markers_clusts"), paste0("sc3_", k, "_markers_auroc"), paste0("sc3_", k, "_markers_padj"), "feature_symbol")]
3.organise_marker_genes(object, k, p.val, auroc)

session info

  • R version 3.4.2
  • Bioconductor 3.6
  • scater_1.6.0
  • SC3_1.6.0

Thanks again.

Problems with calculate_distance() and sc3_calc_dists() functions

Hello,

I give a SCESet to sc3_calc_dists() and receive this error:

sce_full <- sc3_calc_dists(sce_full)
Calculating distances between the cells... Error in if (object@sc3$n_cores > length(distances)) { : argument is of length zero

When I try to run sc3() function I have this:

sce_full <- calculateQCMetrics(sce_full)
sce_full <- sc3(sce_full, ks = 8:10, biology = TRUE)
Setting SC3 parameters...
Setting a range of k...
Calculating distances between the cells...
starting worker pid=31908 on localhost:11626 at 15:25:45.606
starting worker pid=31924 on localhost:11626 at 15:25:46.109
starting worker pid=31940 on localhost:11626 at 15:25:46.629
Loading required package: SC3
Loading required package: SC3
Loading required package: SC3
Error: package or namespace load failed for �SC3™ in loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]): there is no package called rhdf5™
Loading required package: rngtools
Loading required package: rngtools
Loading required package: foreach
Loading required package: pkgmaker
Loading required package: pkgmaker
Loading required package: rngtools
Loading required package: registry
Loading required package: registry
Loading required package: pkgmaker
Loading required package: registry
Attaching package: pkgmaker™
Attaching package: �pkgmaker™
The following object is masked from �package:base™: isNamespaceLoaded The following object is masked from package:base™: isNamespaceLoaded
Attaching package: pkgmaker™
The following object is masked from �package:base™: isNamespaceLoaded
Error in calculate_distance(dataset, i) : could not find function "calculate_distance"
Error in calculate_distance(dataset, i) : could not find function "calculate_distance"
Error in calculate_distance(dataset, i) : could not find function "calculate_distance"
Error in checkForRemoteErrors(val) : 3 nodes produced errors; first error: Error in calculate_distance(dataset, i) : could not find function "calculate_distance"

Actually, I have rhdf5 package loaded. It is strange that it cannot read it.
I tried to load calculate_distance() function manually in R but it did not help. Does anyone have an idea how to get calculate_distance function?

Session Info

rhdf5_2.20.0
SC3_1.4.2
BiocParallel_1.10.1

All genes were removed after the gene filter! Stopping now...

I ran SC3 a few weeks ago. At that time, it well works and I successfully found clusters.

However, after I update R and reinstalled the SC3, I cannot run SC3 with exactly same code and same data.

I got a message "All genes were removed after the gene filter! Stopping now...".

My R version is 3.4.2 and I install recent version of SC3.

Does anyone know this problem? My script is as follows:


ann <- data.frame(cell_type1 = rep(1,dim(temp2)[2]))
pd <- new("AnnotatedDataFrame", data = ann)

colnames(temp2) <- rownames(ann)
sceset <- newSCESet(countData = temp2, phenoData = pd, logExprsOffset = 1)
is_exprs(sceset) <- exprs(sceset) >0.1
sceset <- calculateQCMetrics(sceset)
sceset <- sc3(sceset, ks = 2:10, biology = TRUE)
p_data <- pData(sceset)

Error running sc3() - Error in unserialize(socklist[[n]]) : error reading from connection

Hello,

I was trying out your package but I get a pretty long error list when I run sc3()
I used the example your provide.

Setting SC3 parameters...
Setting a range of k...
Calculating distances between the cells...
starting worker pid=9833 on localhost:11267 at 21:54:28.710
Loading required package: SC3
loaded SC3 and set parent environment
Loading required package: foreach
Loading required package: rngtools
Loading required package: pkgmaker
Loading required package: registry

Attaching package: ‘pkgmaker’

The following object is masked from ‘package:base’:

    isNamespaceLoaded

Performing transformations and calculating eigenvectors...
starting worker pid=9843 on localhost:11267 at 21:54:33.550
Loading required package: SC3
loaded SC3 and set parent environment

 *** caught segfault ***
address 0xee12000, cause 'memory not mapped'

Traceback:
 1: .Call("SC3_norm_laplacian", PACKAGE = "SC3", A)
 2: norm_laplacian(dists)
 3: transformation(get(hash.table[i, 1], dists), hash.table[i, 2])
 4: doTryCatch(return(expr), name, parentenv, handler)
 5: tryCatchOne(expr, names, parentenv, handlers[[1L]])
 6: tryCatchList(expr, classes, parentenv, handlers)
 7: tryCatch(expr, error = function(e) {    call <- conditionCall(e)    if (!is.null(call)) {        if (identical(call[[1L]], quote(doTryCatch)))             call <- sys.call(-4L)        dcall <- deparse(call)[1L]        prefix <- paste("Error in", dcall, ": ")        LONG <- 75L        msg <- conditionMessage(e)        sm <- strsplit(msg, "\n")[[1L]]        w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w")        if (is.na(w))             w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L],                 type = "b")        if (w > LONG)             prefix <- paste0(prefix, "\n  ")    }    else prefix <- "Error : "    msg <- paste0(prefix, conditionMessage(e), "\n")    .Internal(seterrmessage(msg[1L]))    if (!silent && identical(getOption("show.error.messages"),         TRUE)) {        cat(msg, file = stderr())        .Internal(printDeferredWarnings())    }    invisible(structure(msg, class = "try-error", condition = e))})
 8: try({    tmp <- transformation(get(hash.table[i, 1], dists), hash.table[i,         2])    tmp[, 1:max(n_dim)]})
 9: eval(expr, envir, enclos)
10: eval(.doSnowGlobals$expr, envir = .doSnowGlobals$exportenv)
11: doTryCatch(return(expr), name, parentenv, handler)
12: tryCatchOne(expr, names, parentenv, handlers[[1L]])
13: tryCatchList(expr, classes, parentenv, handlers)
14: tryCatch(eval(.doSnowGlobals$expr, envir = .doSnowGlobals$exportenv),     error = function(e) e)
15: (function (args) {    lapply(names(args), function(n) assign(n, args[[n]], pos = .doSnowGlobals$exportenv))    tryCatch(eval(.doSnowGlobals$expr, envir = .doSnowGlobals$exportenv),         error = function(e) e)})(quote(list(i = 4L)))
16: do.call(msg$data$fun, msg$data$args, quote = TRUE)
17: doTryCatch(return(expr), name, parentenv, handler)
18: tryCatchOne(expr, names, parentenv, handlers[[1L]])
19: tryCatchList(expr, classes, parentenv, handlers)
20: tryCatch(do.call(msg$data$fun, msg$data$args, quote = TRUE),     error = handler)
21: doTryCatch(return(expr), name, parentenv, handler)
22: tryCatchOne(expr, names, parentenv, handlers[[1L]])
23: tryCatchList(expr, classes, parentenv, handlers)
24: tryCatch({    msg <- recvData(master)    if (msg$type == "DONE") {        closeNode(master)        break    }    else if (msg$type == "EXEC") {        success <- TRUE        handler <- function(e) {            success <<- FALSE            structure(conditionMessage(e), class = c("snow-try-error",                 "try-error"))        }        t1 <- proc.time()        value <- tryCatch(do.call(msg$data$fun, msg$data$args,             quote = TRUE), error = handler)        t2 <- proc.time()        value <- list(type = "VALUE", value = value, success = success,             time = t2 - t1, tag = msg$data$tag)        msg <- NULL        sendData(master, value)        value <- NULL    }}, interrupt = function(e) NULL)
25: slaveLoop(makeSOCKmaster(master, port, timeout, useXDR))
26: parallel:::.slaveRSOCK()
An irrecoverable exception occurred. R is aborting now ...
Error in unserialize(socklist[[n]]) : error reading from connection

Any idea?

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