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R toolkit for single cell genomics
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Error with ReadH5AD in .subset2 #2060

Closed mcfefa closed 5 years ago

mcfefa commented 5 years ago

I downloaded a publicly available 10X scRNAseq, which had the data saved as a .h5ad file. Following along with the Conversion Vignette, I installed the scater & loomR packages, however, when I used the ReadH5AD() function, I got an error that said Error in .subset2(x, i, exact = exact) : subscript out of bounds. Below is how I implemented ReadH5AD with the output:

R version 3.6.0 (2019-04-26) -- "Planting of a Tree"
Copyright (C) 2019 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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[Previously saved workspace restored]

> library(Seurat)
Registered S3 method overwritten by 'R.oo':
  method        from       
  throw.default R.methodsS3
> library(scater)
Loading required package: SingleCellExperiment
Loading required package: SummarizedExperiment
Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    anyDuplicated, append, as.data.frame, basename, cbind, colnames,
    dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
    grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
    rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:base':

    expand.grid

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: DelayedArray
Loading required package: matrixStats

Attaching package: 'matrixStats'

The following objects are masked from 'package:Biobase':

    anyMissing, rowMedians

Loading required package: BiocParallel

Attaching package: 'DelayedArray'

The following objects are masked from 'package:matrixStats':

    colMaxs, colMins, colRanges, rowMaxs, rowMins, rowRanges

The following objects are masked from 'package:base':

    aperm, apply, rowsum

Loading required package: ggplot2

Attaching package: 'scater'

The following object is masked from 'package:S4Vectors':

    rename

The following object is masked from 'package:stats':

    filter

> library(loomR)
Loading required package: R6
Loading required package: hdf5r

Attaching package: 'hdf5r'

The following object is masked from 'package:SummarizedExperiment':

    values

The following object is masked from 'package:GenomicRanges':

    values

The following object is masked from 'package:IRanges':

    values

The following object is masked from 'package:S4Vectors':

    values

Attaching package: 'loomR'

The following object is masked from 'package:Biobase':

    combine

The following object is masked from 'package:BiocGenerics':

    combine

> setwd("/share/lab_padron/Meghan/scRNAseq/Setty-normalCD34/")
> SettyPt1 <- ReadH5AD(file = "./human_cd34_bm_rep1.h5ad", assay = "RNA", verbose = TRUE) 
Pulling expression matrices and metadata
Data is scaled
Merging feature-level metadata dataframes
Creating assay object
Storing X as scale.data and raw as data
Warning: Feature names cannot have underscores ('_'), replacing with dashes ('-')
Warning: Feature names cannot have underscores ('_'), replacing with dashes ('-')
Error in .subset2(x, i, exact = exact) : subscript out of bounds

The sessionInfo() for R is below: 

> sessionInfo()
R version 3.6.0 (2019-04-26)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS release 6.10 (Final)

Matrix products: default
BLAS:   /share/apps/R-3.6.0/lib64/R/lib/libRblas.so
LAPACK: /share/apps/R-3.6.0/lib64/R/lib/libRlapack.so

Random number generation:
 RNG:     Mersenne-Twister 
 Normal:  Inversion 
 Sample:  Rounding 

locale:
 [1] LC_CTYPE=en_US.iso885915       LC_NUMERIC=C                  
 [3] LC_TIME=en_US.iso885915        LC_COLLATE=en_US.iso885915    
 [5] LC_MONETARY=en_US.iso885915    LC_MESSAGES=en_US.iso885915   
 [7] LC_PAPER=en_US.iso885915       LC_NAME=C                     
 [9] LC_ADDRESS=C                   LC_TELEPHONE=C                
[11] LC_MEASUREMENT=en_US.iso885915 LC_IDENTIFICATION=C           

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

other attached packages:
 [1] loomR_0.2.1.9000            hdf5r_1.2.0                
 [3] R6_2.4.0                    scater_1.12.2              
 [5] ggplot2_3.2.0               SingleCellExperiment_1.6.0 
 [7] SummarizedExperiment_1.14.1 DelayedArray_0.10.0        
 [9] BiocParallel_1.18.1         matrixStats_0.54.0         
[11] Biobase_2.44.0              GenomicRanges_1.36.0       
[13] GenomeInfoDb_1.20.0         IRanges_2.18.1             
[15] S4Vectors_0.22.0            BiocGenerics_0.30.0        
[17] Seurat_3.0.2               

loaded via a namespace (and not attached):
 [1] Rtsne_0.15               ggbeeswarm_0.6.0         colorspace_1.4-1        
 [4] ggridges_0.5.1           XVector_0.24.0           BiocNeighbors_1.2.0     
 [7] listenv_0.7.0            npsurv_0.4-0             ggrepel_0.8.1           
[10] bit64_0.9-7              codetools_0.2-16         splines_3.6.0           
[13] R.methodsS3_1.7.1        lsei_1.2-0               jsonlite_1.6            
[16] ica_1.0-2                cluster_2.1.0            png_0.1-7               
[19] R.oo_1.22.0              sctransform_0.2.0        compiler_3.6.0          
[22] httr_1.4.0               assertthat_0.2.1         Matrix_1.2-17           
[25] lazyeval_0.2.2           BiocSingular_1.0.0       htmltools_0.3.6         
[28] tools_3.6.0              rsvd_1.0.2               igraph_1.2.4.1          
[31] gtable_0.3.0             glue_1.3.1               GenomeInfoDbData_1.2.1  
[34] RANN_2.6.1               reshape2_1.4.3           dplyr_0.8.3             
[37] Rcpp_1.0.2               gdata_2.18.0             ape_5.3                 
[40] nlme_3.1-141             DelayedMatrixStats_1.6.0 gbRd_0.4-11             
[43] lmtest_0.9-37            stringr_1.4.0            globals_0.12.4          
[46] irlba_2.3.3              gtools_3.8.1             future_1.14.0           
[49] MASS_7.3-51.4            zlibbioc_1.30.0          zoo_1.8-6               
[52] scales_1.0.0             RColorBrewer_1.1-2       reticulate_1.13         
[55] pbapply_1.4-1            gridExtra_2.3            stringi_1.4.3           
[58] caTools_1.17.1.2         bibtex_0.4.2             Rdpack_0.11-0           
[61] SDMTools_1.1-221.1       rlang_0.4.0              pkgconfig_2.0.2         
[64] bitops_1.0-6             lattice_0.20-38          ROCR_1.0-7              
[67] purrr_0.3.2              htmlwidgets_1.3          cowplot_1.0.0           
[70] bit_1.1-14               tidyselect_0.2.5         plyr_1.8.4              
[73] magrittr_1.5             gplots_3.0.1.1           pillar_1.4.2            
[76] withr_2.1.2              fitdistrplus_1.0-14      survival_2.44-1.1       
[79] RCurl_1.95-4.12          tibble_2.1.3             future.apply_1.3.0      
[82] tsne_0.1-3               crayon_1.3.4             KernSmooth_2.23-15      
[85] plotly_4.9.0             viridis_0.5.1            grid_3.6.0              
[88] data.table_1.12.2        metap_1.1                digest_0.6.20           
[91] tidyr_0.8.3              R.utils_2.9.0            munsell_0.5.0           
[94] beeswarm_0.2.3           viridisLite_0.3.0        vipor_0.4.5

Please advise on what I should do to correct this error or if this is an issue with the dataset.

mcfefa commented 5 years ago

This issue persists when upgrading to Seurat v3.1.0.

const-ae commented 5 years ago

I get the same error with the another dataset: svensson_chromium_control.h5ad from https://figshare.com/projects/Zero_inflation_in_negative_control_data/61292

mojaveazure commented 5 years ago

This should be fixed in the development version of Seurat. To install the development version of Seurat, please see the instructions here.