Hi!
I have been trying to run diffbind with count tables I generated for each replicate. I also normalized the read counts by subtracting the counts from the respective input files. The count table is as follows: chr10 100005027 100010617 345 chr10 100043137 100045010 112 chr10 100183611 100183844 0 chr10 100184335 100187340 223
dba.contrast and dba.analyze run fine, but I get an error when running dba.report. Error in .Call2("solveuserSEW0", start, end, width, PACKAGE = "IRanges") : solving row 82: negative widths are not allowed I checked and there are no negative widths.
Also, when looking at the generated csv file from dba.report, I get completely different chromosome ranges than what I had in my input files. This is how it looks like: Chr Start End Conc ConcTreatment ConcVeh. Fold p-value FDR chr22 19542 19543 8.91 9.66 7.22 2.44 3.58E-23 4.12E-20 chr15 36604 36607 6.99 7.87 4.26 3.61 3.75E-23 4.20E-20 chr8 35313 35315 9.09 9.71 7.99 1.71 4.77E-23 5.20E-20 chr1 27014 27014 7.22 8.09 4.73 3.36 5.22E-23 5.55E-20 chr6 2000 1999 8.43 7.08 9.11 -2.03 6.91E-23 7.17E-20 chr19 18308 18313 7.54 8.33 5.71 2.62 8.00E-23 7.99E-20 chr2 30458 30460 6.93 7.83 4.07 3.76 8.09E-23 7.99E-20 chr6 1680 1681 8.16 8.95 6.28 2.66 1.08E-22 1.05E-19 chr16 23757 23770 6.92 7.81 4.22 3.58 1.30E-22 1.23E-19 chr2 2609 2608 7.72 8.53 5.72 2.81 1.90E-22 1.75E-19 chr2 23069 23074 8.07 8.79 6.58 2.21 2.47E-22 2.23E-19
Am I missing any information in my counts file? Why are my ranges off?
Here is also my session information, in case it helps! R version 3.6.1 (2019-07-05) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows >= 8 x64 (build 9200)
Matrix products: default
locale:
[1] LCCOLLATE=EnglishUnited States.1252 LCCTYPE=EnglishUnited States.1252
[3] LCMONETARY=EnglishUnited States.1252 LCNUMERIC=C
[5] LCTIME=English_United States.1252
attached base packages: [1] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] DiffBind2.12.0 SummarizedExperiment1.14.1 DelayedArray0.10.0
[4] BiocParallel1.17.18 matrixStats0.54.0 Biobase2.44.0
[7] GenomicRanges1.36.0 GenomeInfoDb1.20.0 IRanges2.18.1
[10] S4Vectors0.22.0 BiocGenerics_0.30.0
loaded via a namespace (and not attached):
[1] amap0.8-17 colorspace1.4-1 rjson0.2.20
[4] hwriter1.3.2 htmlTable1.13.1 XVector0.24.0
[7] base64enc0.1-3 rstudioapi0.10 ggrepel0.8.1
[10] bit640.9-7 AnnotationDbi1.46.0 splines3.6.1
[13] geneplotter1.62.0 knitr1.23 zeallot0.1.0
[16] Formula1.2-3 Rsamtools2.0.0 annotate1.62.0
[19] cluster2.1.0 GO.db3.8.2 pheatmap1.0.12
[22] graph1.62.0 BiocManager1.30.4 compiler3.6.1
[25] httr1.4.1 GOstats2.50.0 backports1.1.4
[28] assertthat0.2.1 Matrix1.2-17 lazyeval0.2.2
[31] limma3.40.6 htmltools0.3.6 acepack1.4.1
[34] prettyunits1.0.2 tools3.6.1 gtable0.3.0
[37] glue1.3.1 GenomeInfoDbData1.2.1 Category2.50.0
[40] systemPipeR1.18.2 dplyr0.8.3 batchtools0.9.11
[43] rappdirs0.3.1 ShortRead1.42.0 Rcpp1.0.2
[46] vctrs0.2.0 Biostrings2.52.0 gdata2.18.0
[49] rtracklayer1.44.2 xfun0.8 stringr1.4.0
[52] gtools3.8.1 XML3.98-1.20 edgeR3.26.6
[55] zlibbioc1.30.0 scales1.0.0 BSgenome1.52.0
[58] VariantAnnotation1.30.1 hms0.5.0 RBGL1.60.0
[61] RColorBrewer1.1-2 yaml2.2.0 gridExtra2.3
[64] memoise1.1.0 ggplot23.2.0 rpart4.1-15
[67] biomaRt2.40.3 latticeExtra0.6-28 stringi1.4.3
[70] RSQLite2.1.2 genefilter1.66.0 checkmate1.9.4
[73] GenomicFeatures1.36.4 caTools1.17.1.2 rlang0.4.0
[76] pkgconfig2.0.2 bitops1.0-6 lattice0.20-38
[79] purrr0.3.2 htmlwidgets1.3 GenomicAlignments1.20.1
[82] bit1.1-14 tidyselect0.2.5 GSEABase1.46.0
[85] AnnotationForge1.26.0 magrittr1.5 DESeq21.24.0
[88] R62.4.0 gplots3.0.1.1 Hmisc4.2-0
[91] base64url1.4 DBI1.0.0 pillar1.4.2
[94] foreign0.8-71 withr2.1.2 nnet7.3-12
[97] survival2.44-1.1 RCurl1.95-4.12 tibble2.1.3
[100] crayon1.3.4 KernSmooth2.23-15 progress1.2.2
[103] locfit1.5-9.1 grid3.6.1 data.table1.12.2
[106] blob1.2.0 Rgraphviz2.28.0 digest0.6.20
[109] xtable1.8-4 brew1.0-6 munsell_0.5.0
Thank you very much! Best, Ana
