I would like to use ChIPQC to assess the quality of reads, without regard for peak calling. Accordingly, I would like to provide experiment and control BAMs, but no peak file. I was hoping to get all output that is not dependent upon the actual peak calls. Is there any way for me to accomplish this?

My attempt to do this by setting Peaks to NA failed, as shown below.

QCexperiment.csv:

SampleID        Tissue  Factor  bamReads        ControlID       bamControl      Peaks   PeakCaller
ATF3-WT_KO      macrophage-C57BL/6J     ATF3    ATF3-WT.bam     ATF3-KO ATF3-KO.bam     NA      raw

R code:

> library("ChIPQC")

> samples <- read.csv("QCexperiment.csv", sep="\t", stringsAsFactors=FALSE)

> experiment <- ChIPQC(samples, annotation="mm9")

ATF3-WT_KO macrophage-C57BL/6J ATF3   NA raw
Error in `rownames<-`(`*tmp*`, value = c(1L, 0L)) : 
  length of 'dimnames' [1] not equal to array extent
In addition: Warning message:
In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL'


> traceback()
6: `rownames<-`(`*tmp*`, value = c(1L, 0L))
5: `rownames<-`(`*tmp*`, value = c(1L, 0L))
4: pv.vectors(model, mask = mask, minOverlap = minOverlap, bKeepAll = bKeepAll, 
       bAnalysis = bAnalysis, attributes = attributes)
3: pv.model(DBA, mask = mask, minOverlap = minOverlap, samplesheet = sampleSheet, 
       config = config, caller = peakCaller, format = peakFormat, 
       scorecol = scoreCol, bLowerBetter = bLowerScoreBetter, skipLines = skipLines, 
       bAddCallerConsensus = bAddCallerConsensus, bRemoveM = bRemoveM, 
       bRemoveRandom = bRemoveRandom, bKeepAll = TRUE, bAnalysis = TRUE, 
       filter = filter, attributes = attributes)
2: dba(sampleSheet = experiment, bCorPlot = FALSE, peakCaller = "bed")
1: ChIPQC(samples, annotation = "mm9")


> sessionInfo()
R version 3.2.2 (2015-08-14)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS release 6.5 (Final)

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    parallel  stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] ChIPQC_1.6.1            DiffBind_1.14.6         RSQLite_1.0.0          
 [4] DBI_0.3.1               locfit_1.5-9.1          GenomicAlignments_1.4.2
 [7] Rsamtools_1.20.5        Biostrings_2.38.4       XVector_0.10.0         
[10] limma_3.24.15           GenomicRanges_1.22.4    GenomeInfoDb_1.6.3     
[13] IRanges_2.4.8           S4Vectors_0.8.11        BiocGenerics_0.16.1    
[16] ggplot2_2.1.0          

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.4            lattice_0.20-33        GO.db_3.1.2           
 [4] gtools_3.5.0           digest_0.6.9           Nozzle.R1_1.1-1       
 [7] plyr_1.8.3             futile.options_1.0.0   BatchJobs_1.6         
[10] ShortRead_1.26.0       gplots_2.17.0          zlibbioc_1.14.0       
[13] annotate_1.46.1        gdata_2.17.0           Matrix_1.2-2          
[16] checkmate_1.6.2        systemPipeR_1.2.23     GOstats_2.34.0        
[19] splines_3.2.2          BiocParallel_1.2.22    chipseq_1.18.0        
[22] stringr_1.0.0          RCurl_1.95-4.8         pheatmap_1.0.7        
[25] munsell_0.4.3          rtracklayer_1.28.10    sendmailR_1.2-1       
[28] base64enc_0.1-3        BBmisc_1.9             fail_1.3              
[31] edgeR_3.10.4           XML_3.98-1.3           AnnotationForge_1.10.1
[34] bitops_1.0-6           grid_3.2.2             RBGL_1.44.0           
[37] xtable_1.7-4           GSEABase_1.30.2        gtable_0.2.0          
[40] magrittr_1.5           scales_0.4.0           graph_1.46.0          
[43] KernSmooth_2.23-15     amap_0.8-14            stringi_1.0-1         
[46] reshape2_1.4.1         hwriter_1.3.2          genefilter_1.50.0     
[49] latticeExtra_0.6-26    futile.logger_1.4.1    brew_1.0-6            
[52] rjson_0.2.15           lambda.r_1.1.7         RColorBrewer_1.1-2    
[55] tools_3.2.2            BSgenome_1.36.3        Biobase_2.28.0        
[58] Category_2.34.2        survival_2.38-3        AnnotationDbi_1.30.1  
[61] colorspace_1.2-6       caTools_1.17.1