Hi Rory,

I have just recently starting using DiffBind and was hoping you could help me clarify something.

Regarding filtering peaks with few counts, i was wondering if there is a way to plot the distribution of peak counts. I'd like to do this so as to decide what peaks to filter out.

Many thanks,

Maria

Figured it out, sorry for bothering, it was quite straight forward.

Hi Rory,

Yes, many thanks for replying anyway. I have however ran into another problem. If I have two samples for which I do not have controls. When I try to run the dba. count function with the score as TMM in CPM <test=dba.count(test,minOverlap=2,score=DBA_SCORE_TMM_READS_FULL_CPM)>

I get this error:

<Error in pv.get_reads(pv, g1, bSubControl = bSubControl) : object 'bMinus' not found>

I was wondering if it is possible to get the read count in cpm for the peaks in the samples with no control. I double checked that the sorted bams and their indexes are in the same location, and removed the 'Control' column from sample sheet

Many thanks!

Maria

PS: output of sessionInfo()

> sessionInfo()
R version 3.1.1 (2014-07-10)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_GB.UTF-8        LC_COLLATE=en_GB.UTF-8    
 [5] LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_GB.UTF-8   
 [7] LC_PAPER=en_GB.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] DESeq2_1.6.2            RcppArmadillo_0.4.500.0
 [3] Rcpp_0.11.3             DESeq_1.18.0           
 [5] lattice_0.20-29         locfit_1.5-9.1         
 [7] Biobase_2.26.0          DiffBind_1.12.3        
 [9] GenomicAlignments_1.2.1 Rsamtools_1.18.2       
[11] Biostrings_2.34.1       XVector_0.6.0          
[13] limma_3.22.1            GenomicRanges_1.18.3   
[15] GenomeInfoDb_1.2.5      IRanges_2.0.1          
[17] S4Vectors_0.4.0         BiocGenerics_0.12.1    

loaded via a namespace (and not attached):
 [1] acepack_1.3-3.3      amap_0.8-12          annotate_1.44.0     
 [4] AnnotationDbi_1.28.1 base64enc_0.1-2      BatchJobs_1.5       
 [7] BBmisc_1.8           BiocParallel_1.0.0   bitops_1.0-6        
[10] brew_1.0-6           caTools_1.17.1       checkmate_1.5.1     
[13] cluster_1.15.3       codetools_0.2-9      colorspace_1.2-4    
[16] DBI_0.3.1            digest_0.6.6         edgeR_3.8.5         
[19] fail_1.2             foreach_1.4.2        foreign_0.8-61      
[22] Formula_1.1-2        gdata_2.13.3         genefilter_1.48.1   
[25] geneplotter_1.44.0   ggplot2_1.0.0        gplots_2.15.0       
[28] grid_3.1.1           gtable_0.1.2         gtools_3.4.1        
[31] Hmisc_3.14-6         iterators_1.0.7      KernSmooth_2.23-13  
[34] latticeExtra_0.6-26  MASS_7.3-35          munsell_0.4.2       
[37] nnet_7.3-8           plyr_1.8.1           proto_0.3-10        
[40] RColorBrewer_1.1-2   reshape2_1.4.1       rpart_4.1-8         
[43] RSQLite_1.0.0        scales_0.2.4         sendmailR_1.2-1     
[46] splines_3.1.1        stringr_0.6.2        survival_2.37-7     
[49] tools_3.1.1          XML_3.98-1.1         xtable_1.7-4        
[52] zlibbioc_1.12.0 

Hi Maria-

You have discovered a bug. I have checked in a fix. It will appear in DiffBind 1.14.4 in the next day or two. To get this fix, you'll need to be on Bioconductor 3.1, which runs on R 3.2.0.

-Rory