Hi, I did an analysis using DiffBind in June 2022 with no errors. I restarted the project last week after updating R and DiffBind and now the normalization process does not work when the blacklist argument = TRUE.

1) My command with an error message is: peaks.400 <- dba.analyze(peaks.400, method=DBA_ALL_METHODS_BLOCK)

2) Commands performed just before:

peaks <- dba(sampleSheet = sample.table, minOverlap=1, config=data.frame(RunParallel=FALSE, reportInit="DBA", DataType=DBA_DATA_GRANGES, AnalysisMethod=DBA_DESEQ2,fragmentSize=160, bCorPlot=FALSE, th=0.1, bUsePval=FALSE))
peaks.400 <- dba.count(peaks, summits = 200)
peaks.400 <- dba.normalize(peaks.400, offsets = TRUE)
peaks.400 <- dba.contrast(peaks.400, design = FALSE, categories = DBA_TREATMENT, block = DBA_REPLICATE, minMembers = 2)
`

The error returned was:

Applying Blacklist/Greylists...
Genome detected: Mmusculus.UCSC.mm10
Applying blacklist...
Removed: 944 of 38060 intervals.
Re-normalizing...
Blacklist error: Error: Invalid normalization
Unable to apply Blacklist/Greylist.

3) I tried to remove the blacklist: peaks.400B <- dba.analyze(peaks.400, method=DBA_ALL_METHODS_BLOCK, bBlacklist = FALSE)

And then the problem disappeared:

Normalize edgeR with defaults...
Analyzing...
edgeR multi-factor analysis.
edgeR multi-factor analysis.
edgeR multi-factor analysis.
converting counts to integer mode
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
converting counts to integer mode
DESeq2 multi-factor analysis
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
converting counts to integer mode
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
converting counts to integer mode
DESeq2 multi-factor analysis
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
converting counts to integer mode
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
converting counts to integer mode
DESeq2 multi-factor analysis
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates

4) Finally, I tried:

peaks.400 <- dba.blacklist(peaks.400, blacklist=DBA_BLACKLIST_MM10, greylist= FALSE)

But got the following error message:

Genome detected: Mmusculus.UCSC.mm10
Applying blacklist...
Removed: 944 of 38060 intervals.
Re-normalizing...
Error: Invalid normalization

5) Like I mentioned above, with an earlier R version (R version 4.1.2 (2021-11-01) -- "Bird Hippie") and DiffBind version (not sure which one) on exactly the same BAM files with the same code I did not have this problem.

However, I would like to compare with and without blacklist applied to see the validity of my results. Any idea what the problem could be?

Thanks a lot for your help.

sessionInfo( )

R version 4.2.2 (2022-10-31)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.3.1

Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib

locale:
[1] en_CA.UTF-8/en_CA.UTF-8/en_CA.UTF-8/C/en_CA.UTF-8/en_CA.UTF-8

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

other attached packages:
 [1] GreyListChIP_1.30.0                BSgenome.Mmusculus.UCSC.mm10_1.4.3 BSgenome_1.66.1                   
 [4] BiocManager_1.30.19                csaw_1.32.0                        rtracklayer_1.58.0                
 [7] DiffBind_3.8.0                     minfi_1.44.0                       bumphunter_1.40.0                 
[10] locfit_1.5-9.6                     iterators_1.0.14                   foreach_1.5.2                     
[13] Biostrings_2.66.0                  XVector_0.38.0                     SummarizedExperiment_1.28.0       
[16] Biobase_2.58.0                     MatrixGenerics_1.10.0              matrixStats_0.62.0                
[19] GenomicRanges_1.50.1               GenomeInfoDb_1.34.3                IRanges_2.32.0                    
[22] S4Vectors_0.36.0                   BiocGenerics_0.44.0               

loaded via a namespace (and not attached):
  [1] BiocFileCache_2.6.0       plyr_1.8.7                splines_4.2.2             BiocParallel_1.32.1      
  [5] ggplot2_3.4.0             amap_0.8-19               digest_0.6.30             invgamma_1.1             
  [9] htmltools_0.5.3           SQUAREM_2021.1            fansi_1.0.3               magrittr_2.0.3           
 [13] memoise_2.0.1             tzdb_0.3.0                limma_3.54.0              readr_2.1.3              
 [17] annotate_1.76.0           systemPipeR_2.4.0         bdsmatrix_1.3-6           askpass_1.1              
 [21] siggenes_1.72.0           prettyunits_1.1.1         jpeg_0.1-9                colorspace_2.0-3         
 [25] apeglm_1.20.0             ggrepel_0.9.2             blob_1.2.3                rappdirs_0.3.3           
 [29] dplyr_1.0.10              crayon_1.5.2              RCurl_1.98-1.9            genefilter_1.80.0        
 [33] GEOquery_2.66.0           survival_3.4-0            glue_1.6.2                gtable_0.3.1             
 [37] zlibbioc_1.44.0           DelayedArray_0.24.0       Rhdf5lib_1.20.0           HDF5Array_1.26.0         
 [41] scales_1.2.1              mvtnorm_1.1-3             edgeR_3.40.0              DBI_1.1.3                
 [45] rngtools_1.5.2            Rcpp_1.0.9                emdbook_1.3.12            xtable_1.8-4             
 [49] progress_1.2.2            bit_4.0.4                 mclust_6.0.0              preprocessCore_1.60.0    
 [53] truncnorm_1.0-8           metapod_1.6.0             htmlwidgets_1.5.4         httr_1.4.4               
 [57] gplots_3.1.3              RColorBrewer_1.1-3        ellipsis_0.3.2            pkgconfig_2.0.3          
 [61] reshape_0.8.9             XML_3.99-0.12             deldir_1.0-6              dbplyr_2.2.1             
 [65] utf8_1.2.2                tidyselect_1.2.0          rlang_1.0.6               AnnotationDbi_1.60.0     
 [69] munsell_0.5.0             tools_4.2.2               cachem_1.0.6              cli_3.4.1                
 [73] generics_0.1.3            RSQLite_2.2.18            stringr_1.4.1             fastmap_1.1.0            
 [77] yaml_2.3.6                bit64_4.0.5               beanplot_1.3.1            caTools_1.18.2           
 [81] scrime_1.3.5              purrr_0.3.5               KEGGREST_1.38.0           nlme_3.1-160             
 [85] doRNG_1.8.2               sparseMatrixStats_1.10.0  nor1mix_1.3-0             xml2_1.3.3               
 [89] biomaRt_2.54.0            compiler_4.2.2            rstudioapi_0.14           filelock_1.0.2           
 [93] curl_4.3.3                png_0.1-7                 geneplotter_1.76.0        tibble_3.1.8             
 [97] stringi_1.7.8             GenomicFeatures_1.50.2    lattice_0.20-45           Matrix_1.5-1             
[101] multtest_2.54.0           vctrs_0.5.0               pillar_1.8.1              lifecycle_1.0.3          
[105] rhdf5filters_1.10.0       irlba_2.3.5.1             data.table_1.14.4         bitops_1.0-7             
[109] R6_2.5.1                  BiocIO_1.8.0              latticeExtra_0.6-30       hwriter_1.3.2.1          
[113] ShortRead_1.56.0          KernSmooth_2.23-20        codetools_0.2-18          MASS_7.3-58.1            
[117] gtools_3.9.3              assertthat_0.2.1          rhdf5_2.42.0              DESeq2_1.38.0            
[121] openssl_2.0.4             rjson_0.2.21              GenomicAlignments_1.34.0  Rsamtools_2.14.0         
[125] GenomeInfoDbData_1.2.9    hms_1.1.2                 quadprog_1.5-8            grid_4.2.2               
[129] coda_0.19-4               tidyr_1.2.1               base64_2.0.1              DelayedMatrixStats_1.20.0
[133] ashr_2.2-54               illuminaio_0.40.0         mixsqp_0.3-43             bbmle_1.0.25             
[137] numDeriv_2016.8-1.1       interp_1.1-3              restfulr_0.0.15

I am checking in a fix for this now. It will be available as DiffBind_3.8.1.