search

quadbio / scMultiome_analysis_vignette

Tutorial of single-cell RNA-ATAC multiomic sequencing data analysis
43 stars 13 forks source link

'Error in density.default(x = query.feature[[featmatch]], kernel = "gaussian", : 'x' contains missing values' while running JASPAR2020 for motif enrichment analyses: #5

Open yojetsharma opened 7 months ago

yojetsharma commented 7 months ago

While everything else ran smoothly, there is an issue while running JASPAR. Also in the script earlier (shown here below):

> library(TFBSTools)
> library(JASPAR2020)
> 
> pfm <- getMatrixSet(
+     x = JASPAR2020,
+     opts = list(collection = "CORE", tax_group = 'vertebrates', all_versions = FALSE)
+ )
> df_pfm <- data.frame(t(sapply(pfm, function(x)
+     c(id=x@ID, name=x@name, symbol=ifelse(!is.null(x@tags$symbol),x@tags$symbol,NA)))))
> 
> seurat <- AddMotifs(seurat, genome = BSgenome.Hsapiens.UCSC.hg38, pfm = pfm)
Building motif matrix
Warning in CreateMotifMatrix(features = object, pwm = pfm, genome = genome,  :
  Not all seqlevels present in supplied genome
Finding motif positions
Creating Motif object
Warning in RegionStats.default(object = regions, genome = genome, verbose = verbose,  :
  Not all seqlevels present in supplied genome
Warning messages:
1: In .merge_two_Seqinfo_objects(x, y) :
  Each of the 2 combined objects has sequence levels not in the other:
  - in 'x': chrM, chr1_GL383518v1_alt, chr1_GL383519v1_alt, chr1_GL383520v2_alt, chr1_KI270759v1_alt, chr1_KI270760v1_alt, chr1_KI270761v1_alt, chr1_KI270762v1_alt, chr1_KI270763v1_alt, chr1_KI270764v1_alt, chr1_KI270765v1_alt, chr1_KI270766v1_alt, chr1_KI270892v1_alt, chr2_GL383521v1_alt, chr2_GL383522v1_alt, chr2_GL582966v2_alt, chr2_KI270767v1_alt, chr2_KI270768v1_alt, chr2_KI270769v1_alt, chr2_KI270770v1_alt, chr2_KI270771v1_alt, chr2_KI270772v1_alt, chr2_KI270773v1_alt, chr2_KI270774v1_alt, chr2_KI270775v1_alt, chr2_KI270776v1_alt, chr2_KI270893v1_alt, chr2_KI270894v1_alt, chr3_GL383526v1_alt, chr3_JH636055v2_alt, chr3_KI270777v1_alt, chr3_KI270778v1_alt, chr3_KI270779v1_alt, chr3_KI270780v1_alt, chr3_KI270781v1_alt, chr3_KI270782v1_alt, chr3_KI270783v1_alt, chr3_KI270784v1_alt, chr3_KI270895v1_alt, chr3_KI270924v1_alt, chr3_KI270934v1_alt, chr3_KI270935v1_alt, chr3_KI270936v1_alt, chr3_KI270937v1_alt, chr4_GL000 [... truncated]
2: In .merge_two_Seqinfo_objects(x, y) :
  Each of the 2 combined objects has sequence levels not in the other:
  - in 'x': chrM, chr1_GL383518v1_alt, chr1_GL383519v1_alt, chr1_GL383520v2_alt, chr1_KI270759v1_alt, chr1_KI270760v1_alt, chr1_KI270761v1_alt, chr1_KI270762v1_alt, chr1_KI270763v1_alt, chr1_KI270764v1_alt, chr1_KI270765v1_alt, chr1_KI270766v1_alt, chr1_KI270892v1_alt, chr2_GL383521v1_alt, chr2_GL383522v1_alt, chr2_GL582966v2_alt, chr2_KI270767v1_alt, chr2_KI270768v1_alt, chr2_KI270769v1_alt, chr2_KI270770v1_alt, chr2_KI270771v1_alt, chr2_KI270772v1_alt, chr2_KI270773v1_alt, chr2_KI270774v1_alt, chr2_KI270775v1_alt, chr2_KI270776v1_alt, chr2_KI270893v1_alt, chr2_KI270894v1_alt, chr3_GL383526v1_alt, chr3_JH636055v2_alt, chr3_KI270777v1_alt, chr3_KI270778v1_alt, chr3_KI270779v1_alt, chr3_KI270780v1_alt, chr3_KI270781v1_alt, chr3_KI270782v1_alt, chr3_KI270783v1_alt, chr3_KI270784v1_alt, chr3_KI270895v1_alt, chr3_KI270924v1_alt, chr3_KI270934v1_alt, chr3_KI270935v1_alt, chr3_KI270936v1_alt, chr3_KI270937v1_alt, chr4_GL000 [... truncated]
> open_peaks <- AccessiblePeaks(seurat)
> peaks_matched <- MatchRegionStats(meta.feature = seurat[['ATAC']]@meta.features[open_peaks, ],
+                                   query.feature = seurat[['ATAC']]@meta.features[top_peaks_ct$feature, ],
+                                   n = 50000)
Matching GC.percent distribution
Error in density.default(x = query.feature[[featmatch]], kernel = "gaussian",  : 
  'x' contains missing values
> sessionInfo()
R version 4.2.1 (2022-06-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.5 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3

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

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

other attached packages:
 [1] BSgenome.Hsapiens.UCSC.hg38_1.4.5 BSgenome_1.66.3                  
 [3] rtracklayer_1.58.0                Biostrings_2.66.0                
 [5] XVector_0.38.0                    GenomicRanges_1.50.2             
 [7] GenomeInfoDb_1.34.9               IRanges_2.32.0                   
 [9] S4Vectors_0.36.2                  BiocGenerics_0.44.0              
[11] JASPAR2020_0.99.10                TFBSTools_1.36.0                 
[13] presto_1.0.0                      data.table_1.15.2                
[15] Rcpp_1.0.12                       simspec_0.0.0.9000               
[17] Matrix_1.6-5                      dplyr_1.1.4                      
[19] Signac_1.12.0                     Seurat_5.0.2                     
[21] SeuratObject_5.0.1                sp_2.1-3                         

loaded via a namespace (and not attached):
  [1] utf8_1.2.4                  R.utils_2.12.3              spatstat.explore_3.2-6     
  [4] reticulate_1.35.0           tidyselect_1.2.0            AnnotationDbi_1.60.2       
  [7] poweRlaw_0.80.0             RSQLite_2.3.5               htmlwidgets_1.6.4          
 [10] grid_4.2.1                  BiocParallel_1.32.6         Rtsne_0.17                 
 [13] munsell_0.5.0               codetools_0.2-18            ica_1.0-3                  
 [16] future_1.33.1               miniUI_0.1.1.1              withr_3.0.0                
 [19] spatstat.random_3.2-3       colorspace_2.1-0            progressr_0.14.0           
 [22] Biobase_2.58.0              rstudioapi_0.15.0           ROCR_1.0-11                
 [25] tensor_1.5                  listenv_0.9.1               MatrixGenerics_1.10.0      
 [28] labeling_0.4.3              GenomeInfoDbData_1.2.9      polyclip_1.10-6            
 [31] bit64_4.0.5                 farver_2.1.1                parallelly_1.37.1          
 [34] vctrs_0.6.5                 generics_0.1.3              R6_2.5.1                   
 [37] bitops_1.0-7                spatstat.utils_3.0-4        cachem_1.0.8               
 [40] DelayedArray_0.24.0         promises_1.2.1              BiocIO_1.8.0               
 [43] scales_1.3.0                gtable_0.3.4                globals_0.16.2             
 [46] goftest_1.2-3               spam_2.10-0                 seqLogo_1.64.0             
 [49] rlang_1.1.3                 RcppRoll_0.3.0              splines_4.2.1              
 [52] lazyeval_0.2.2              spatstat.geom_3.2-9         BiocManager_1.30.22        
 [55] yaml_2.3.8                  reshape2_1.4.4              abind_1.4-5                
 [58] httpuv_1.6.14               tools_4.2.1                 ggplot2_3.5.0              
 [61] ellipsis_0.3.2              RColorBrewer_1.1-3          ggridges_0.5.6             
 [64] plyr_1.8.9                  zlibbioc_1.44.0             purrr_1.0.2                
 [67] RCurl_1.98-1.14             deldir_2.0-4                pbapply_1.7-2              
 [70] cowplot_1.1.3               zoo_1.8-12                  SummarizedExperiment_1.28.0
 [73] ggrepel_0.9.5               cluster_2.1.3               motifmatchr_1.20.0         
 [76] magrittr_2.0.3              RSpectra_0.16-1             scattermore_1.2            
 [79] lmtest_0.9-40               RANN_2.6.1                  fitdistrplus_1.1-11        
 [82] matrixStats_1.2.0           hms_1.1.3                   patchwork_1.2.0            
 [85] mime_0.12                   xtable_1.8-4                XML_3.99-0.16.1            
 [88] fastDummies_1.7.3           gridExtra_2.3               compiler_4.2.1             
 [91] tibble_3.2.1                KernSmooth_2.23-20          crayon_1.5.2               
 [94] R.oo_1.26.0                 htmltools_0.5.7             later_1.3.2                
 [97] tzdb_0.4.0                  tidyr_1.3.1                 DBI_1.2.2                  
[100] MASS_7.3-57                 readr_2.1.5                 cli_3.6.2                  
[103] R.methodsS3_1.8.2           parallel_4.2.1              dotCall64_1.1-1            
[106] igraph_2.0.2                pkgconfig_2.0.3             GenomicAlignments_1.34.1   
[109] TFMPvalue_0.0.9             plotly_4.10.4               spatstat.sparse_3.0-3      
[112] annotate_1.76.0             DirichletMultinomial_1.40.0 stringr_1.5.1              
[115] digest_0.6.34               sctransform_0.4.1           RcppAnnoy_0.0.22           
[118] pracma_2.4.4                CNEr_1.34.0                 spatstat.data_3.0-4        
[121] leiden_0.4.3.1              fastmatch_1.1-4             uwot_0.1.16                
[124] restfulr_0.0.15             shiny_1.8.0                 Rsamtools_2.14.0           
[127] gtools_3.9.5                rjson_0.2.21                lifecycle_1.0.4            
[130] nlme_3.1-157                jsonlite_1.8.8              viridisLite_0.4.2          
[133] fansi_1.0.6                 pillar_1.9.0                lattice_0.20-45            
[136] GO.db_3.16.0                KEGGREST_1.38.0             fastmap_1.1.1              
[139] httr_1.4.7                  survival_3.3-1              glue_1.7.0                 
[142] png_0.1-8                   bit_4.0.5                   stringi_1.8.3              
[145] blob_1.2.4                  RcppHNSW_0.6.0              caTools_1.18.2             
[148] memoise_2.0.1               irlba_2.3.5.1               future.apply_1.11.1