Hi I am using DiffBind's dba.plotHeatmap() or just plot() to plot a correlation matrix between the peak calls.

For my correlation matrix I don't want to have the axis labels and thus used the given command

plot(DBdata,labRow = NULL, labCol = NULL)

but getting the following error:

Error in heatmap.3(domap, labCol = collab, col = cols, trace = "none",  : 
  formal argument "labRow" matched by multiple actual arguments

For details you can visit this page for DiffBind [source core.R][1] which also incorporated heatmap.3().

Can anyone help me in this regard? Thanks in advance.

Also have a look of my sessionInfo().

sessionInfo()
R version 3.6.0 (2019-04-26)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /usr/local/intel/compilers_and_libraries_2019.1.144/linux/mkl/lib/intel64_lin/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] parallel  stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] ggplot2_3.2.1               DiffBind_2.13.0            
 [3] SummarizedExperiment_1.15.3 DelayedArray_0.11.2        
 [5] BiocParallel_1.19.0         matrixStats_0.54.0         
 [7] Biobase_2.45.0              GenomicRanges_1.37.12      
 [9] GenomeInfoDb_1.21.1         IRanges_2.19.10            
[11] S4Vectors_0.23.13           BiocGenerics_0.31.4        

loaded via a namespace (and not attached):
 [1] Category_2.51.0          bitops_1.0-6             bit64_0.9-7             
 [4] RColorBrewer_1.1-2       progress_1.2.2           httr_1.4.0              
 [7] Rgraphviz_2.29.0         tools_3.6.0              backports_1.1.4         
[10] R6_2.4.0                 KernSmooth_2.23-15       DBI_1.0.0               
[13] lazyeval_0.2.2           colorspace_1.4-1         withr_2.1.2             
[16] tidyselect_0.2.5         prettyunits_1.0.2        bit_1.1-14              
[19] curl_3.3                 compiler_3.6.0           graph_1.63.0            
[22] rtracklayer_1.45.1       checkmate_1.9.3          caTools_1.17.1.2        
[25] scales_1.0.0             genefilter_1.67.1        RBGL_1.61.0             
[28] askpass_1.1              rappdirs_0.3.1           stringr_1.4.0           
[31] digest_0.6.20            Rsamtools_2.1.2          AnnotationForge_1.27.0  
[34] XVector_0.25.0           pkgconfig_2.0.2          BSgenome_1.53.0         
[37] dbplyr_1.4.2             limma_3.41.5             rlang_0.4.0             
[40] RSQLite_2.1.1            GOstats_2.51.0           hwriter_1.3.2           
[43] gtools_3.8.1             dplyr_0.8.3              VariantAnnotation_1.31.3
[46] RCurl_1.95-4.12          magrittr_1.5             GO.db_3.8.2             
[49] GenomeInfoDbData_1.2.1   Matrix_1.2-17            Rcpp_1.0.2              
[52] munsell_0.5.0            yaml_2.2.0               stringi_1.4.3           
[55] edgeR_3.27.5             debugme_1.1.0            zlibbioc_1.31.0         
[58] gplots_3.0.1.1           BiocFileCache_1.9.1      grid_3.6.0              
[61] blob_1.2.0               ggrepel_0.8.1            gdata_2.18.0            
[64] crayon_1.3.4             lattice_0.20-38          splines_3.6.0           
[67] Biostrings_2.53.0        GenomicFeatures_1.37.1   annotate_1.63.0         
[70] hms_0.5.0                batchtools_0.9.11        locfit_1.5-9.1          
[73] zeallot_0.1.0            pillar_1.4.2             rjson_0.2.20            
[76] systemPipeR_1.19.1       base64url_1.4            biomaRt_2.41.7          
[79] XML_3.98-1.20            glue_1.3.1               ShortRead_1.43.0        
[82] latticeExtra_0.6-28      data.table_1.12.2        vctrs_0.2.0             
[85] gtable_0.3.0             openssl_1.4              purrr_0.3.2             
[88] amap_0.8-17              assertthat_0.2.1         xtable_1.8-4            
[91] survival_2.44-1.1        pheatmap_1.0.12          tibble_2.1.3            
[94] GenomicAlignments_1.21.2 AnnotationDbi_1.47.0     memoise_1.1.0           
[97] brew_1.0-6               GSEABase_1.47.0

As you say, DiffBind does indeed support plot(), which dispatches dba.plotHeatmap(), which internally invokes heatmap.3().

However dba.plotHeatmap() doesn't directly support plotting without row and column labels. There are two workarounds you may try.

One is to retrieve the correlation matrix and plot it yourself (using, for example, gplots::heatmap.2()). You can get the correlaiton heatmap as follows:

cor.matrix <- plot(DBdata)
heatmap.2(cor.matrix,labCol="",labRow="")

Alternatively, you can remove the labels from the DBA object and use the regular dba.plotHeatmap() function. You are advised do this using a separate copy of the object, as other plotting functions may not work properly without the labels:

temp.DB <- DBdata
temp.DB$class[DBA_ID,]="" 
plot(DBdata,ColAttributes=NULL)