Hello,

Using DiffBind, I would like to get the peaks in common between the edgeR approach and the DESeq2 approach. With the edgeR approach, I'm getting 135 peaks (with significant differences between two conditions). With the DESeq2 approach, I'm getting 192 peaks. The result of dba.plotVenn() tells me that there are 70 peaks in common between the two approaches. When I run:

dba.report(dbObj, method=DBA_ALL_METHODS, contrast=1, th=0.05)

Instead of getting 70 peaks, I get 135 peaks as if I had run:

dba.report(dbObj, method=DBA_EDGER, contrast=1, th=0.05)

which, as expected, gives me 135 peaks. Is there anything I can do on my side?

Here is the result of my sessionInfo():

R version 4.1.0 (2021-05-18)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.2 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        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] forcats_0.5.1               stringr_1.4.0               dplyr_1.0.7                
 [4] purrr_0.3.4                 readr_1.4.0                 tidyr_1.1.3                
 [7] tibble_3.1.2                tidyverse_1.3.1             ChIPQC_1.28.0              
[10] DiffBind_3.2.3              SummarizedExperiment_1.22.0 MatrixGenerics_1.4.0       
[13] matrixStats_0.59.0          ggplot2_3.3.5               ensembldb_2.16.0           
[16] AnnotationFilter_1.16.0     GenomicFeatures_1.44.0      AnnotationDbi_1.54.1       
[19] Biobase_2.52.0              GenomicRanges_1.44.0        GenomeInfoDb_1.28.0        
[22] IRanges_2.26.0              S4Vectors_0.30.0            AnnotationHub_3.0.1        
[25] BiocFileCache_2.0.0         dbplyr_2.1.1                BiocGenerics_0.38.0        

loaded via a namespace (and not attached):
  [1] rappdirs_0.3.3                            rtracklayer_1.52.0                       
  [3] AnnotationForge_1.34.0                    coda_0.19-4                              
  [5] bit64_4.0.5                               knitr_1.33                               
  [7] irlba_2.3.3                               DelayedArray_0.18.0                      
  [9] data.table_1.14.0                         hwriter_1.3.2                            
 [11] KEGGREST_1.32.0                           RCurl_1.98-1.3                           
 [13] generics_0.1.0                            cowplot_1.1.1                            
 [15] TxDb.Rnorvegicus.UCSC.rn4.ensGene_3.2.2   RSQLite_2.2.7                            
 [17] shadowtext_0.0.8                          bit_4.0.4                                
 [19] enrichplot_1.12.1                         base64url_1.4                            
 [21] lubridate_1.7.10                          xml2_1.3.2                               
 [23] httpuv_1.6.1                              assertthat_0.2.1                         
 [25] batchtools_0.9.15                         viridis_0.6.1                            
 [27] amap_0.8-18                               apeglm_1.14.0                            
 [29] xfun_0.24                                 hms_1.1.0                                
 [31] evaluate_0.14                             promises_1.2.0.1                         
 [33] fansi_0.5.0                               restfulr_0.0.13                          
 [35] progress_1.2.2                            readxl_1.3.1                             
 [37] caTools_1.18.2                            Rgraphviz_2.36.0                         
 [39] igraph_1.2.6                              DBI_1.1.1                                
 [41] ellipsis_0.3.2                            backports_1.2.1                          
 [43] V8_3.4.2                                  annotate_1.70.0                          
 [45] biomaRt_2.48.1                            vctrs_0.3.8                              
 [47] cachem_1.0.5                              withr_2.4.2                              
 [49] ggforce_0.3.3                             DOT_0.1                                  
 [51] BSgenome_1.60.0                           bdsmatrix_1.3-4                          
 [53] checkmate_2.0.0                           GenomicAlignments_1.28.0                 
 [55] treeio_1.16.1                             prettyunits_1.1.1                        
 [57] TxDb.Mmusculus.UCSC.mm10.knownGene_3.10.0 DOSE_3.18.0                              
 [59] ape_5.5                                   lazyeval_0.2.2                           
 [61] crayon_1.4.1                              genefilter_1.74.0                        
 [63] edgeR_3.34.0                              pkgconfig_2.0.3                          
 [65] tweenr_1.0.2                              nlme_3.1-152                             
 [67] ProtGenerics_1.24.0                       rlang_0.4.11                             
 [69] lifecycle_1.0.0                           filelock_1.0.2                           
 [71] modelr_0.1.8                              GOstats_2.58.0                           
 [73] invgamma_1.1                              cellranger_1.1.0                         
 [75] rsvg_2.1.2                                polyclip_1.10-0                          
 [77] graph_1.70.0                              Matrix_1.3-4                             
 [79] aplot_0.0.6                               ashr_2.2-47                              
 [81] chipseq_1.42.0                            boot_1.3-28                              
 [83] reprex_2.0.0                              pheatmap_1.0.12                          
 [85] png_0.1-7                                 viridisLite_0.4.0                        
 [87] rjson_0.2.20                              bitops_1.0-7                             
 [89] KernSmooth_2.23-20                        Biostrings_2.60.1                        
 [91] blob_1.2.1                                mixsqp_0.3-43                            
 [93] SQUAREM_2021.1                            qvalue_2.24.0                            
 [95] ShortRead_1.50.0                          brew_1.0-6                               
 [97] jpeg_0.1-8.1                              TxDb.Mmusculus.UCSC.mm9.knownGene_3.2.2  
 [99] scales_1.1.1                              memoise_2.0.0                            
[101] GSEABase_1.54.0                           magrittr_2.0.1                           
[103] plyr_1.8.6                                gplots_3.1.1                             
[105] zlibbioc_1.38.0                           compiler_4.1.0                           
[107] scatterpie_0.1.6                          tinytex_0.32                             
[109] BiocIO_1.2.0                              bbmle_1.0.23.1                           
[111] RColorBrewer_1.1-2                        plotrix_3.8-1                            
[113] Rsamtools_2.8.0                           cli_3.0.0                                
[115] systemPipeR_1.26.2                        XVector_0.32.0                           
[117] Category_2.58.0                           patchwork_1.1.1                          
[119] MASS_7.3-54                               tidyselect_1.1.1                         
[121] stringi_1.6.2                             emdbook_1.3.12                           
[123] yaml_2.2.1                                GOSemSim_2.18.0                          
[125] locfit_1.5-9.4                            latticeExtra_0.6-29                      
[127] ggrepel_0.9.1                             grid_4.1.0                               
[129] VariantAnnotation_1.38.0                  fastmatch_1.1-0                          
[131] tools_4.1.0                               rstudioapi_0.13                          
[133] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2   gridExtra_2.3                            
[135] farver_2.1.0                              ggraph_2.0.5                             
[137] digest_0.6.27                             rvcheck_0.1.8                            
[139] BiocManager_1.30.16                       shiny_1.6.0                              
[141] Rcpp_1.0.6                                broom_0.7.8                              
[143] BiocVersion_3.13.1                        later_1.2.0                              
[145] httr_1.4.2                                Nozzle.R1_1.1-1                          
[147] TxDb.Celegans.UCSC.ce6.ensGene_3.2.2      colorspace_2.0-1                         
[149] rvest_1.0.0                               fs_1.5.0                                 
[151] XML_3.99-0.6                              truncnorm_1.0-8                          
[153] splines_4.1.0                             TxDb.Dmelanogaster.UCSC.dm3.ensGene_3.2.2
[155] RBGL_1.68.0                               tidytree_0.3.4                           
[157] graphlayouts_0.7.1                        xtable_1.8-4                             
[159] jsonlite_1.7.2                            ggtree_3.0.2                             
[161] tidygraph_1.2.0                           R6_2.5.0                                 
[163] pillar_1.6.1                              htmltools_0.5.1.1                        
[165] mime_0.11                                 glue_1.4.2                               
[167] fastmap_1.1.0                             BiocParallel_1.26.0                      
[169] interactiveDisplayBase_1.30.0             ChIPseeker_1.28.3                        
[171] fgsea_1.18.0                              GreyListChIP_1.24.0                      
[173] mvtnorm_1.1-2                             utf8_1.2.1                               
[175] lattice_0.20-44                           numDeriv_2016.8-1.1                      
[177] curl_4.3.1                                gtools_3.9.2                             
[179] GO.db_3.13.0                              survival_3.2-11                          
[181] limma_3.48.1                              rmarkdown_2.9                            
[183] munsell_0.5.0                             DO.db_2.9                                
[185] GenomeInfoDbData_1.2.6                    haven_2.4.1                              
[187] reshape2_1.4.4                            gtable_0.3.0                             
[189] TxDb.Hsapiens.UCSC.hg18.knownGene_3.2.2

If you have a look at the help page for dba.report(), DBA_ALL_METHODS is not a valid value for the methods parameter (unless you are generating a report-based DBA object, eg. if bDB=TRUE). As it turns out, dba.report() is using the first method listed in DBA_ALL_METHODS, which is edgeR for historical reasons.

There are a few ways to get a report for only those sites identified as differentially bound by both methods. The most straightforward is probably to retrieve both reports and then take their overlap. Here's an example:

data(tamoxifen_analysis)
tamoxifen <- dba.analyze(tamoxifen, method=DBA_ALL_METHODS)
report.edgeR <- dba.report(tamoxifen,  method=DBA_EDGER)
report.DESeq2 <- dba.report(tamoxifen, method=DBA_DESEQ2)

# overlapping sites annotated with edgeR statistics
report.edgeR[report.edgeR %over% report.DESeq2,]

# overlapping sites annotated with DESeq2 statistics
report.DESeq2[report.DESeq2 %over% report.edgeR,]