error with ATACCalculateGenescore

[hoondy]

Hi, I am trying to use the RP model to generate the gene activity score to 10x scATAC data. I installed MAESTRO R version as well as python version and setup reticulate. Yet, it is still throwing errors as follows. Do you have a suggestion?

# python related
library(reticulate)
use_python("/path/to/python", required = TRUE)

obj.gene <- ATACCalculateGenescore(obj,
                                   organism = "GRCh38",
                                   decaydistance = 10000,
                                   model = "Enhanced")

output

Error in as.integer(as_r_value(x$indices)): cannot coerce type 'environment' to vector of type 'integer'
Traceback:

1. ATACCalculateGenescore(obj, organism = "GRCh38", decaydistance = 10000, 
 .     model = "Enhanced")
2. calculate_RP_score(cell_peaks = inputMat, peaks_list = peaks_list, 
 .     gene_bed_df = refgenes.genescore, genes_list = NULL, decay = decaydistance, 
 .     model = model)
3. py_to_r(result)
4. py_to_r.python.builtin.tuple(result)
5. lapply(converted, function(object) {
 .     if (inherits(object, "python.builtin.object")) 
 .         py_to_r(object)
 .     else object
 . })
6. FUN(X[[i]], ...)
7. py_to_r(object)
8. py_to_r.scipy.sparse.csc.csc_matrix(object)
9. new("dgCMatrix", i = as.integer(as_r_value(x$indices)), p = as.integer(as_r_value(x$indptr)), 
 .     x = as.vector(as_r_value(x$data)), Dim = as.integer(dim(x)))
10. initialize(value, ...)
11. initialize(value, ...)
12. callNextMethod()
13. .nextMethod(.Object = .Object, ... = ...)

session info

R version 4.0.3 (2020-10-10)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS:   ***/conda/envs/r403/lib/libblas.so.3.8.0
LAPACK: ***/conda/envs/r403/lib/libmkl_rt.so

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] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] reticulate_1.18 Seurat_3.2.3    MAESTRO_1.3.1  

loaded via a namespace (and not attached):
  [1] tidyselect_1.1.0            RSQLite_2.2.2              
  [3] AnnotationDbi_1.52.0        htmlwidgets_1.5.3          
  [5] grid_4.0.3                  Rtsne_0.15                 
  [7] devtools_2.3.2              munsell_0.5.0              
  [9] codetools_0.2-18            ica_1.0-2                  
 [11] pbdZMQ_0.3-4                future_1.21.0              
 [13] miniUI_0.1.1.1              withr_2.3.0                
 [15] colorspace_2.0-0            Biobase_2.50.0             
 [17] knitr_1.30                  uuid_0.1-4                 
 [19] rstudioapi_0.13             stats4_4.0.3               
 [21] ROCR_1.0-11                 tensor_1.5                 
 [23] listenv_0.8.0               MatrixGenerics_1.2.0       
 [25] repr_1.1.0                  GenomeInfoDbData_1.2.4     
 [27] polyclip_1.10-0             bit64_4.0.5                
 [29] rprojroot_2.0.2             parallelly_1.23.0          
 [31] vctrs_0.3.6                 generics_0.1.0             
 [33] xfun_0.20                   BiocFileCache_1.14.0       
 [35] R6_2.5.0                    GenomeInfoDb_1.26.2        
 [37] rsvd_1.0.3                  hdf5r_1.3.3                
 [39] bitops_1.0-6                spatstat.utils_1.20-2      
 [41] DelayedArray_0.16.0         assertthat_0.2.1           
 [43] promises_1.1.1              scales_1.1.1               
 [45] nnet_7.3-14                 gtable_0.3.0               
 [47] globals_0.14.0              processx_3.4.5             
 [49] goftest_1.2-2               rlang_0.4.10               
 [51] splines_4.0.3               lazyeval_0.2.2             
 [53] checkmate_2.0.0             yaml_2.2.1                 
 [55] reshape2_1.4.4              abind_1.4-5                
 [57] backports_1.2.1             httpuv_1.5.4               
 [59] Hmisc_4.4-2                 tools_4.0.3                
 [61] usethis_2.0.0               ggplot2_3.3.3              
 [63] ellipsis_0.3.1              gplots_3.1.1               
 [65] RColorBrewer_1.1-2          BiocGenerics_0.36.0        
 [67] sessioninfo_1.1.1           ggridges_0.5.3             
 [69] Rcpp_1.0.5                  plyr_1.8.6                 
 [71] base64enc_0.1-3             progress_1.2.2             
 [73] zlibbioc_1.36.0             purrr_0.3.4                
 [75] RCurl_1.98-1.2              ps_1.5.0                   
 [77] prettyunits_1.1.1           rpart_4.1-15               
 [79] openssl_1.4.3               deldir_0.2-3               
 [81] pbapply_1.4-3               cowplot_1.1.1              
 [83] S4Vectors_0.28.1            zoo_1.8-8                  
 [85] SummarizedExperiment_1.20.0 ggrepel_0.9.0              
 [87] cluster_2.1.0               fs_1.5.0                   
 [89] magrittr_2.0.1              data.table_1.13.6          
 [91] scattermore_0.7             forestplot_1.10.1          
 [93] lmtest_0.9-38               RANN_2.6.1                 
 [95] fitdistrplus_1.1-3          matrixStats_0.57.0         
 [97] pkgload_1.1.0               hms_0.5.3                  
 [99] patchwork_1.1.1             mime_0.9                   
[101] evaluate_0.14               xtable_1.8-4               
[103] XML_3.99-0.5                jpeg_0.1-8.1               
[105] IRanges_2.24.1              gridExtra_2.3              
[107] Gmisc_1.11.0                testthat_3.0.1             
[109] compiler_4.0.3              biomaRt_2.46.0             
[111] tibble_3.0.4                KernSmooth_2.23-18         
[113] crayon_1.3.4                htmltools_0.5.1            
[115] mgcv_1.8-33                 later_1.1.0.1              
[117] Formula_1.2-4               tidyr_1.1.2                
[119] lubridate_1.7.9.2           DBI_1.1.0                  
[121] dbplyr_2.0.0                MASS_7.3-53                
[123] rappdirs_0.3.1              Matrix_1.3-2               
[125] cli_2.2.0                   parallel_4.0.3             
[127] igraph_1.2.6                GenomicRanges_1.42.0       
[129] pkgconfig_2.0.3             foreign_0.8-81             
[131] IRdisplay_0.7.0             plotly_4.9.3               
[133] xml2_1.3.2                  XVector_0.30.0             
[135] stringr_1.4.0               callr_3.5.1                
[137] digest_0.6.27               sctransform_0.3.2          
[139] RcppAnnoy_0.0.18            spatstat.data_1.7-0        
[141] rmarkdown_2.6               leiden_0.3.6               
[143] htmlTable_2.1.0             uwot_0.1.10                
[145] curl_4.3                    shiny_1.5.0                
[147] gtools_3.8.2                lifecycle_0.2.0            
[149] nlme_3.1-151                jsonlite_1.7.2             
[151] desc_1.2.0                  viridisLite_0.3.0          
[153] askpass_1.1                 fansi_0.4.1                
[155] pillar_1.4.7                lattice_0.20-41            
[157] fastmap_1.0.1               httr_1.4.2                 
[159] pkgbuild_1.2.0              survival_3.2-7             
[161] glue_1.4.2                  remotes_2.2.0              
[163] spatstat_1.64-1             png_0.1-7                  
[165] bit_4.0.4                   presto_1.0.0               
[167] stringi_1.5.3               blob_1.2.1                 
[169] latticeExtra_0.6-29         caTools_1.18.1             
[171] memoise_1.1.0               IRkernel_1.1.1             
[173] dplyr_1.0.2                 irlba_2.3.3                
[175] future.apply_1.7.0         

[crazyhottommy]

Have you tried the command-line version?

MAESTRO scatac-genescore -h

[crazyhottommy]

can you try the latest version and see if it still errors out?