Entering edit mode
                    Hi,
I'm having some troubles trying to filter a SingleCellLoomExperiment object by its colData. I made a subset with 100 columns , an I want to filter by the variable Tissue in colData to be equal than "DRG".
Does anyone know what I'm doing wrong? Many thanks!
> scle.all
class: SingleCellLoomExperiment 
dim: 27998 100 
metadata(0):
assays(2): matrix logcounts
rownames(27998): Cbln2 Ptchd2 ... Med27 Psmc6
rowData names(7): Accession Gene ... X_Total X_Valid
colnames(100): Enteric neurons Enteric neurons ... Enteric neurons
  Enteric neurons
colData names(127): Age AnalysisPool ... cDNA_Lib_Ok ngperul_cDNA
reducedDimNames(0):
spikeNames(0):
altExpNames(0):
rowGraphs(0): NULL
colGraphs(2): KNN MKNN
> table(colData(scle.all.drg)$Tissue)
DRG  XX 
 50  50 
> scle.all.drg <- scle.all[,colData(scle.all)$Tissue == "DRG"]
Error in validObject(.Object) : invalid class ?SelfHits? object: 1: 
    'from(x)' must contain non-NA values >= 1 and <= 'nLnode(x)'
invalid class ?SelfHits? object: 2: 
    'to(x)' must contain non-NA values >= 1 and <= 'nRnode(x)'
sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-conda_cos6-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
Random number generation:
 RNG:     Mersenne-Twister 
 Normal:  Inversion 
 Sample:  Rounding 
locale:
[1] en_US.UTF-8
attached base packages:
 [1] grid      parallel  stats4    stats     graphics  grDevices utils    
 [8] datasets  methods   base     
other attached packages:
 [1] rmarkdown_2.1               DESeq2_1.26.0              
 [3] LoomExperiment_1.4.0        rtracklayer_1.46.0         
 [5] rhdf5_2.30.0                SingleR_1.0.5              
 [7] pheatmap_1.0.12             xlsx_0.6.3                 
 [9] AUCell_1.8.0                GSEABase_1.48.0            
[11] graph_1.64.0                annotate_1.64.0            
[13] XML_3.99-0.3                AnnotationDbi_1.48.0       
[15] gridExtra_2.3               edgeR_3.28.0               
[17] limma_3.42.0                Rtsne_0.15                 
[19] scran_1.14.1                scater_1.14.0              
[21] ggplot2_3.3.0               SingleCellExperiment_1.8.0 
[23] SummarizedExperiment_1.16.1 DelayedArray_0.12.2        
[25] BiocParallel_1.20.1         matrixStats_0.56.0         
[27] Biobase_2.46.0              GenomicRanges_1.38.0       
[29] GenomeInfoDb_1.22.0         IRanges_2.20.2             
[31] S4Vectors_0.24.3            BiocGenerics_0.32.0        
loaded via a namespace (and not attached):
  [1] backports_1.1.5               Hmisc_4.4-0                  
  [3] AnnotationHub_2.18.0          BiocFileCache_1.10.2         
  [5] igraph_1.2.4.2                splines_3.6.1                
  [7] digest_0.6.25                 htmltools_0.4.0              
  [9] viridis_0.5.1                 magrittr_1.5                 
 [11] checkmate_2.0.0               memoise_1.1.0                
 [13] cluster_2.1.0                 Biostrings_2.54.0            
 [15] R.utils_2.9.2                 jpeg_0.1-8.1                 
 [17] colorspace_1.4-1              blob_1.2.1                   
 [19] rappdirs_0.3.1                xfun_0.12                    
 [21] dplyr_0.8.5                   crayon_1.3.4                 
 [23] RCurl_1.98-1.1                genefilter_1.68.0            
 [25] survival_3.1-11               glue_1.3.2                   
 [27] gtable_0.3.0                  zlibbioc_1.32.0              
 [29] XVector_0.26.0                BiocSingular_1.2.0           
 [31] Rhdf5lib_1.8.0                HDF5Array_1.14.0             
 [33] scales_1.1.0                  DBI_1.1.0                    
 [35] Rcpp_1.0.4                    viridisLite_0.3.0            
 [37] xtable_1.8-4                  htmlTable_1.13.3             
 [39] dqrng_0.2.1                   foreign_0.8-76               
 [41] bit_1.1-15.2                  rsvd_1.0.3                   
 [43] Formula_1.2-3                 htmlwidgets_1.5.1            
 [45] httr_1.4.1                    RColorBrewer_1.1-2           
 [47] acepack_1.4.1                 farver_2.0.3                 
 [49] pkgconfig_2.0.3               rJava_0.9-11                 
 [51] R.methodsS3_1.8.0             nnet_7.3-13                  
 [53] dbplyr_1.4.2                  locfit_1.5-9.1               
 [55] tidyselect_1.0.0              rlang_0.4.5                  
 [57] later_1.0.0                   munsell_0.5.0                
 [59] BiocVersion_3.10.1            tools_3.6.1                  
 [61] RSQLite_2.2.0                 ExperimentHub_1.12.0         
 [63] evaluate_0.14                 stringr_1.4.0                
 [65] fastmap_1.0.1                 yaml_2.2.1                   
 [67] knitr_1.28                    bit64_0.9-7                  
 [69] purrr_0.3.3                   mime_0.9                     
 [71] R.oo_1.23.0                   compiler_3.6.1               
 [73] rstudioapi_0.11               beeswarm_0.2.3               
 [75] curl_4.3                      png_0.1-7                    
 [77] interactiveDisplayBase_1.24.0 geneplotter_1.64.0           
 [79] tibble_2.1.3                  statmod_1.4.34               
 [81] stringi_1.4.6                 lattice_0.20-40              
 [83] Matrix_1.2-18                 vctrs_0.2.4                  
 [85] pillar_1.4.3                  lifecycle_0.2.0              
 [87] BiocManager_1.30.10           BiocNeighbors_1.4.0          
 [89] data.table_1.12.8             bitops_1.0-6                 
 [91] irlba_2.3.3                   httpuv_1.5.2                 
 [93] R6_2.4.1                      latticeExtra_0.6-29          
 [95] promises_1.1.0                vipor_0.4.5                  
 [97] assertthat_0.2.1              xlsxjars_0.6.1               
 [99] withr_2.1.2                   GenomicAlignments_1.22.1     
[101] Rsamtools_2.2.3               GenomeInfoDbData_1.2.2       
[103] rpart_4.1-15                  DelayedMatrixStats_1.8.0     
[105] shiny_1.4.0.2                 base64enc_0.1-3              
[107] ggbeeswarm_0.6.0      
                    
                
                
This can be made reproducible with
So this looks like a (serious) bug in LoomExperiment
Thanks Martin,
I don't know how to report a bug through Bioconductor, sorry.