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R toolkit for the analysis of single-cell chromatin data
https://stuartlab.org/signac/
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Question about detecting pseudobulk DACRs with FindMarkers() using DESeq2 #1686

Closed yls2g13 closed 2 months ago

yls2g13 commented 2 months ago

Currently analysing a 10X Multiome dataset. When I run FindMarkers() on an ATAC assay with custom peaks using DESeq2 I get an error back. Appreciate if someone here could teach me how to understand and troubleshoot this.

Code used: 

# https://github.com/satijalab/seurat/discussions/7763
# add 1 so that DESeq2 will run
so@assays$customPeakList$counts <- as.matrix(so@assays$customPeakList$counts+1)

# FindMarkers()
markers <- FindMarkers(so, ident.1 = "Control", ident.2 = "Knockout",
                   group.by = "sampleSource",
                   assay = "customPeakList",
                   test.use = "DESeq2")

Resulting error message:

converting counts to integer mode
gene-wise dispersion estimates
mean-dispersion relationship
Error in lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth,  : 
  newsplit: out of vertex space
In addition: There were 17 warnings (use warnings() to see them)

sessionInfo

R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS:   /usr/lib64/libblas.so.3.4.2
LAPACK: /usr/lib64/liblapack.so.3.4.2

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

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

other attached packages:
 [1] DESeq2_1.38.3                      SummarizedExperiment_1.28.0        MatrixGenerics_1.10.0             
 [4] matrixStats_1.1.0                  SeuratDisk_0.0.0.9020              scCustomize_1.1.1                 
 [7] cowplot_1.1.3                      ggpubr_0.4.0                       xlsx_0.6.5                        
[10] RColorBrewer_1.1-3                 viridisLite_0.4.2                  circlize_0.4.15                   
[13] ComplexHeatmap_2.14.0              patchwork_1.1.3.9000               TFBSTools_1.34.0                  
[16] JASPAR2020_0.99.10                 BSgenome.Mmusculus.UCSC.mm10_1.4.3 BSgenome_1.64.0                   
[19] rtracklayer_1.56.1                 Biostrings_2.66.0                  XVector_0.38.0                    
[22] EnsDb.Mmusculus.v79_2.99.0         ensembldb_2.20.2                   AnnotationFilter_1.20.0           
[25] GenomicFeatures_1.48.4             AnnotationDbi_1.58.0               Biobase_2.58.0                    
[28] GenomicRanges_1.50.2               GenomeInfoDb_1.34.9                IRanges_2.32.0                    
[31] S4Vectors_0.36.2                   BiocGenerics_0.44.0                forcats_0.5.1                     
[34] stringr_1.5.1                      dplyr_1.1.4                        purrr_1.0.2                       
[37] readr_2.1.2                        tidyr_1.3.0                        tibble_3.2.1                      
[40] ggplot2_3.4.4                      tidyverse_1.3.1                    Signac_1.12.0                     
[43] Seurat_5.0.0                       SeuratObject_5.0.1                 sp_2.1-1                          

loaded via a namespace (and not attached):
  [1] rappdirs_0.3.3              ggprism_1.0.4               scattermore_1.2             R.methodsS3_1.8.2          
  [5] bit64_4.0.5                 knitr_1.45                  irlba_2.3.5.1               DelayedArray_0.24.0        
  [9] R.utils_2.12.2              data.table_1.14.8           KEGGREST_1.36.0             RCurl_1.98-1.13            
 [13] doParallel_1.0.17           generics_0.1.3              RSQLite_2.2.14              RANN_2.6.1                 
 [17] future_1.33.0               bit_4.0.4                   tzdb_0.3.0                  spatstat.data_3.0-3        
 [21] xml2_1.3.3                  lubridate_1.8.0             httpuv_1.6.12               DirichletMultinomial_1.38.0
 [25] xfun_0.41                   rJava_1.0-6                 hms_1.1.1                   evaluate_0.23              
 [29] promises_1.2.1              fansi_1.0.6                 restfulr_0.0.15             progress_1.2.2             
 [33] caTools_1.18.2              dbplyr_2.4.0                readxl_1.4.0                geneplotter_1.74.0         
 [37] igraph_1.5.1                DBI_1.1.3                   htmlwidgets_1.6.3           spatstat.geom_3.2-7        
 [41] paletteer_1.5.0             ellipsis_0.3.2              RSpectra_0.16-1             backports_1.4.1            
 [45] annotate_1.74.0             biomaRt_2.52.0              deldir_1.0-9                vctrs_0.6.5                
 [49] ROCR_1.0-11                 abind_1.4-5                 cachem_1.0.6                withr_2.5.0                
 [53] progressr_0.14.0            sctransform_0.4.1           GenomicAlignments_1.34.1    prettyunits_1.2.0          
 [57] goftest_1.2-3               cluster_2.1.3               dotCall64_1.1-0             lazyeval_0.2.2             
 [61] seqLogo_1.62.0              crayon_1.5.2                hdf5r_1.3.5                 spatstat.explore_3.2-5     
 [65] pkgconfig_2.0.3             vipor_0.4.5                 nlme_3.1-157                ProtGenerics_1.28.0        
 [69] rlang_1.1.3                 globals_0.16.2              lifecycle_1.0.4             miniUI_0.1.1.1             
 [73] filelock_1.0.2              fastDummies_1.7.3           BiocFileCache_2.6.1         modelr_0.1.8               
 [77] ggrastr_1.0.1               cellranger_1.1.0            polyclip_1.10-6             RcppHNSW_0.5.0             
 [81] lmtest_0.9-40               Matrix_1.6-3                carData_3.0-5               zoo_1.8-12                 
 [85] beeswarm_0.4.0              reprex_2.0.1                ggridges_0.5.4              GlobalOptions_0.1.2        
 [89] png_0.1-8                   rjson_0.2.21                bitops_1.0-7                R.oo_1.25.0                
 [93] KernSmooth_2.23-20          spam_2.10-0                 blob_1.2.3                  shape_1.4.6                
 [97] parallelly_1.36.0           spatstat.random_3.2-1       rstatix_0.7.0               ggsignif_0.6.3             
[101] CNEr_1.32.0                 scales_1.3.0                memoise_2.0.1               magrittr_2.0.3             
[105] plyr_1.8.9                  ica_1.0-3                   zlibbioc_1.44.0             compiler_4.2.0             
[109] BiocIO_1.6.0                clue_0.3-64                 fitdistrplus_1.1-11         snakecase_0.11.0           
[113] Rsamtools_2.14.0            cli_3.6.2                   listenv_0.9.0               pbapply_1.7-2              
[117] MASS_7.3-57                 tidyselect_1.2.0            stringi_1.8.1               yaml_2.3.7                 
[121] locfit_1.5-9.7              ggrepel_0.9.4               fastmatch_1.1-3             tools_4.2.0                
[125] future.apply_1.11.0         parallel_4.2.0              rstudioapi_0.15.0           TFMPvalue_0.0.8            
[129] foreach_1.5.2               janitor_2.2.0               gridExtra_2.3               Rtsne_0.16                 
[133] digest_0.6.33               shiny_1.8.0                 pracma_2.4.2                Rcpp_1.0.12                
[137] car_3.0-13                  broom_0.8.0                 later_1.3.1                 RcppAnnoy_0.0.21           
[141] httr_1.4.7                  colorspace_2.1-0            rvest_1.0.2                 XML_3.99-0.15              
[145] fs_1.5.2                    tensor_1.5                  reticulate_1.35.0           splines_4.2.0              
[149] uwot_0.1.16                 RcppRoll_0.3.0              rematch2_2.1.2              spatstat.utils_3.0-4       
[153] xlsxjars_0.6.1              plotly_4.10.3               xtable_1.8-4                jsonlite_1.8.7             
[157] poweRlaw_0.70.6             R6_2.5.1                    pillar_1.9.0                htmltools_0.5.7            
[161] mime_0.12                   glue_1.7.0                  fastmap_1.1.1               BiocParallel_1.32.6        
[165] codetools_0.2-18            utf8_1.2.4                  lattice_0.20-45             spatstat.sparse_3.0-3      
[169] ggbeeswarm_0.6.0            curl_5.1.0                  leiden_0.4.3.1              gtools_3.9.5               
[173] GO.db_3.15.0                survival_3.5-7              rmarkdown_2.25              munsell_0.5.0              
[177] GetoptLong_1.0.5            GenomeInfoDbData_1.2.9      iterators_1.0.14            haven_2.5.0                
[181] reshape2_1.4.4              gtable_0.3.4
timoast commented 2 months ago

Hi, please open an issue in the Seurat repo as the FindMarkers() function is part of Seurat: https://github.com/satijalab/seurat