Hi,

I'm working with diffbind R package to perform differential analysis on h3k27ac peak data, however, in my case I have to generate a new DBA object containing custom read count across a number of patient samples. Following diffbind instructions, I tried to generate the DBA object starting from the 'dba' command using a Datasheet with all the required meta data (sampleID, Condition, Treatment ...), where the column 'Counts' refers to the path of tab-delimited file formatted as 'chrom', 'start','end','count' for each sample. However, when I try to create the dba...

```newdba <- dba(sampleSheet=datasheet.temp)```

The following error message come out:

"Error in peaks[, 1:3] : incorrect number of dimensions"

It seems to be due to something in the data.frame format but starting from this message it's really hard for me to understand what's wrong.

This is my 'datasheet.temp' object:

ls.str(datasheet.temp)
bamControl :  chr [1:79] "/datasets/MDS_five_patients_ReseqTo20Mn_22_10_07/alignments/Input.bam"| __truncated__ ... 
bamReads :  chr [1:79] "/datasets/MDS_five_patients_ReseqTo20Mn_22_10_07/alignments/hlu1171.bam"| __truncated__ ...
Condition :  chr [1:79] "AML" "LR" "AML" "AML" "AML" "AML" "LR" "LR" "LR" "LR" "LR" ...
ControlID :  chr [1:79] "CD34_control_PE" "CD34_control_PE" "CD34_control_PE" ...
Counts :  chr [1:79] "/analysis_of_h3k27ac_peaks/diffbind/hlu1171.counts.tsv" ...
Factor :  chr [1:79] "h3k27ac" "h3k27ac" "h3k27ac" "h3k27ac" "h3k27ac" "h3k27ac" ...
PeakCaller :  chr [1:79] "bed" "bed" "bed" "bed" "bed" "bed" "bed" "bed" "bed" "bed" ...
Peaks :  chr [1:79] "/datasets/MDS_five_patients_ReseqTo20Mn_22_10_07/peak_calling/hlu1171.cleanedPeaks.bed"| __truncated__ ...
Replicate :  chr [1:79] "1" "1" "1" "1" "1" "1" "1" "1" "1" "1" "1" "1" "1" "1" "1" "1" ...
SampleID :  chr [1:79] "hlu1171" "hlu1455" "hlu1520" "hlu642" "hlu685" "hlu719" ...
Tissue :  chr [1:79] "Human Bone Marrow CD34+" "Human Bone Marrow CD34+" ...
Treatment :  chr [1:79] "five" "five" "five" "five" "five" "five" "eight" "eight" ...

Whilst a single 'tab-delimited count file (as indicated in the 'Counts' column) is:

chr1    825646  828042  71
chr1    843236  844972  18
chr1    869535  870364  16
chr1    902147  933503  351
chr1    935089  946583  140
chr1    950841  969118  293
chr1    970366  980728  119

sessionInfo( )
R version 4.1.3 (2022-03-10)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)


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] stats4    stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] sva_3.42.0                  BiocParallel_1.28.3        
 [3] genefilter_1.76.0           mgcv_1.8-41                
 [5] nlme_3.1-160                writexl_1.4.1              
 [7] ggplot2_3.3.6               RColorBrewer_1.1-3         
 [9] gplots_3.1.3                DiffBind_3.4.11            
[11] SummarizedExperiment_1.24.0 Biobase_2.54.0             
[13] MatrixGenerics_1.6.0        matrixStats_0.62.0         
[15] GenomicRanges_1.46.1        GenomeInfoDb_1.30.1        
[17] IRanges_2.28.0              S4Vectors_0.32.4           
[19] BiocGenerics_0.40.0        

loaded via a namespace (and not attached):
 [1] bitops_1.0-7             bit64_4.0.5              httr_1.4.4              
 [4] numDeriv_2016.8-1.1      tools_4.1.3              utf8_1.2.2              
 [7] R6_2.5.1                 irlba_2.3.5.1            KernSmooth_2.23-20      
[10] DBI_1.1.3                colorspace_2.0-3         apeglm_1.16.0           
[13] withr_2.5.0              tidyselect_1.2.0         bit_4.0.4               
[16] compiler_4.1.3           cli_3.4.1                DelayedArray_0.20.0     
[19] rtracklayer_1.54.0       caTools_1.18.2           scales_1.2.1            
[22] SQUAREM_2021.1           mvtnorm_1.1-3            mixsqp_0.3-43           
[25] stringr_1.4.1            digest_0.6.30            Rsamtools_2.10.0        
[28] XVector_0.34.0           jpeg_0.1-9               pkgconfig_2.0.3         
[31] htmltools_0.5.3          fastmap_1.1.0            invgamma_1.1            
[34] bbmle_1.0.25             limma_3.50.3             BSgenome_1.62.0         
[37] htmlwidgets_1.5.4        rlang_1.0.6              RSQLite_2.2.18          
[40] BiocIO_1.4.0             generics_0.1.3           hwriter_1.3.2.1         
[43] gtools_3.9.3             dplyr_1.0.10             RCurl_1.98-1.9          
[46] magrittr_2.0.3           GenomeInfoDbData_1.2.7   interp_1.1-3            
[49] Matrix_1.5-1             Rcpp_1.0.9               munsell_0.5.0           
[52] fansi_1.0.3              lifecycle_1.0.3          edgeR_3.36.0            
[55] stringi_1.7.8            yaml_2.3.6               MASS_7.3-58.1           
[58] zlibbioc_1.40.0          plyr_1.8.7               blob_1.2.3              
[61] grid_4.1.3               parallel_4.1.3           ggrepel_0.9.1           
[64] bdsmatrix_1.3-6          crayon_1.5.2             deldir_1.0-6            
[67] lattice_0.20-45          splines_4.1.3            Biostrings_2.62.0       
[70] annotate_1.72.0          KEGGREST_1.34.0          locfit_1.5-9.6          
[73] pillar_1.8.1             rjson_0.2.21             systemPipeR_2.0.0       
[76] XML_3.99-0.12            glue_1.6.2               ShortRead_1.52.0        
[79] GreyListChIP_1.26.0      latticeExtra_0.6-30      png_0.1-7               
[82] vctrs_0.5.0              gtable_0.3.1             amap_0.8-19             
[85] assertthat_0.2.1         cachem_1.0.6             ashr_2.2-54             
[88] emdbook_1.3.12           xtable_1.8-4             restfulr_0.0.15         
[91] coda_0.19-4              survival_3.4-0           truncnorm_1.0-8         
[94] tibble_3.1.8             memoise_2.0.1            AnnotationDbi_1.56.2    
[97] GenomicAlignments_1.30.0

Thanks a lot in advance if somebody can help me.

Cheers,

Francesco

This should be fixed in the current version (DiffBind_3.8.3).

Ok, thanks a lot Rory. Francesco

Hi Rory,

After a try with the new DiffBind version (3.8.0 and 3.8.3) , the error still appears. I guess something was wrong in the dba object structure imported from the datasheet. Indeed, I tried to launch the same dba command but using a datasheet without the (last) 'Counts' column and the function works. Now I'm checking the format of the counts.tsv files , if I understood correctly, these are tab-delimited files with chromosome, start, end and counts right? Actually I followed that format. Regions are also sorted by chromosome and position. Do you know if there is something else to consider in creating these count files? Thanks a lot. Francesco