Entering edit mode
Hello,
I've been using DiffBind for my analyses and it's working great, apart from a specific problem I encountered with the output: Sometimes it will record all intervals from one "tissue" having a concentration of 0, but only for 1 chromosome. In the most recent case, it was all intervals from chr9.
I have no idea why this might be happening, as there are definitely reads throughout chr9 for this sample. If anyone has any idea what might be causing this problem, please let me know.
I have attached an image of the first 30 rows of the full dba report output csv file.
![chr9_example1
> STAT5_exp7 <- dba(sampleSheet = "DamID_exp7_HPC_diffbind.csv")
> replicate_consensus <- dba.peakset(STAT5_exp7, consensus = (DBA_TISSUE),
minOverlap = 2)
> replicate_consensus <- dba(replicate_consensus,
mask = replicate_consensus$masks$Consensus,
minOverlap = 1)
> consensus_peakset <- dba.peakset(replicate_consensus, bRetrieve = TRUE)
> STAT5_exp7_reads <- dba.count(STAT5_exp7, peaks = consensus_peakset, summits = FALSE, bSubControl = FALSE, bUseSummarizeOverlaps = FALSE)
KO_WT_rep1 WT 1 narrow
KO_WT_rep2 WT 2 narrow
KO_YF_rep1 YF 1 narrow
KO_YF_rep2 YF 2 narrow
> replicate_consensus <- dba.peakset(STAT5_exp7, consensus = (DBA_TISSUE),
+ minOverlap = 2)
Add consensus: WT
Add consensus: YF
> replicate_consensus <- dba(replicate_consensus,
+ mask = replicate_consensus$masks$Consensus,
+ minOverlap = 1)
> consensus_peakset <- dba.peakset(replicate_consensus, bRetrieve = TRUE)
>
>
> STAT5_exp7_reads <- dba.count(STAT5_exp7, peaks = consensus_peakset, summits = FALSE, bSubControl = FALSE, bUseSummarizeOverlaps = FALSE)
> STAT5_exp7_analysis <- dba.contrast(STAT5_exp7_reads, contrast=c("Tissue","WT","YF"))
Computing results names...
> STAT5_exp7_analysis <- dba.analyze(STAT5_exp7_analysis, bBlacklist=FALSE, bGreylist=FALSE)
Normalize DESeq2 with defaults...
Analyzing...
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
> STAT5KO_full_report <- dba.report(STAT5_exp7_analysis, th=1, bCalled = TRUE, file = "STAT5_exp7_DB_analysis_DBv3.csv")
sessionInfo( )
R version 4.0.3 (2020-10-10)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Scientific Linux 7.9 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /home/mhw46/.conda/envs/bioconductor2/lib/libopenblasp-r0.3.10.so
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] parallel stats4 stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] DiffBind_3.0.15 SummarizedExperiment_1.20.0
[3] Biobase_2.50.0 MatrixGenerics_1.2.1
[5] matrixStats_0.61.0 GenomicRanges_1.42.0
[7] GenomeInfoDb_1.26.7 IRanges_2.24.1
[9] S4Vectors_0.28.1 BiocGenerics_0.36.1
loaded via a namespace (and not attached):
[1] backports_1.4.1 GOstats_2.56.0 BiocFileCache_1.14.0
[4] plyr_1.8.6 GSEABase_1.52.1 splines_4.0.3
[7] BiocParallel_1.24.1 ggplot2_3.3.5 amap_0.8-18
[10] digest_0.6.29 invgamma_1.1 GO.db_3.12.1
[13] SQUAREM_2021.1 fansi_1.0.2 magrittr_2.0.1
[16] checkmate_2.0.0 memoise_2.0.1 BSgenome_1.58.0
[19] base64url_1.4 limma_3.46.0 Biostrings_2.58.0
[22] annotate_1.68.0 systemPipeR_1.24.6 askpass_1.1
[25] bdsmatrix_1.3-4 prettyunits_1.1.1 jpeg_0.1-9
[28] colorspace_2.0-2 blob_1.2.2 rappdirs_0.3.3
[31] apeglm_1.12.0 ggrepel_0.9.1 dplyr_1.0.7
[34] crayon_1.4.2 RCurl_1.98-1.5 jsonlite_1.7.3
[37] graph_1.68.0 genefilter_1.72.1 brew_1.0-6
[40] survival_3.2-13 VariantAnnotation_1.36.0 glue_1.6.0
[43] gtable_0.3.0 zlibbioc_1.36.0 XVector_0.30.0
[46] DelayedArray_0.16.3 V8_4.0.0 Rgraphviz_2.34.0
[49] scales_1.1.1 pheatmap_1.0.12 mvtnorm_1.1-3
[52] DBI_1.1.2 edgeR_3.32.1 Rcpp_1.0.8
[55] xtable_1.8-4 progress_1.2.2 emdbook_1.3.12
[58] bit_4.0.4 rsvg_2.1.2 AnnotationForge_1.32.0
[61] truncnorm_1.0-8 httr_1.4.2 gplots_3.1.1
[64] RColorBrewer_1.1-2 ellipsis_0.3.2 pkgconfig_2.0.3
[67] XML_3.99-0.8 dbplyr_2.1.1 locfit_1.5-9.4
[70] utf8_1.2.2 tidyselect_1.1.1 rlang_0.4.12
[73] AnnotationDbi_1.52.0 munsell_0.5.0 tools_4.0.3
[76] cachem_1.0.6 generics_0.1.1 RSQLite_2.2.9
[79] stringr_1.4.0 fastmap_1.1.0 yaml_2.2.1
[82] bit64_4.0.5 caTools_1.18.2 purrr_0.3.4
[85] RBGL_1.66.0 xml2_1.3.3 biomaRt_2.46.3
[88] compiler_4.0.3 curl_4.3.2 png_0.1-7
[91] geneplotter_1.68.0 tibble_3.1.6 stringi_1.7.6
[94] GenomicFeatures_1.42.3 lattice_0.20-45 Matrix_1.4-0
[97] vctrs_0.3.8 pillar_1.6.4 lifecycle_1.0.1
[100] data.table_1.14.2 bitops_1.0-7 irlba_2.3.5
[103] rtracklayer_1.50.0 R6_2.5.1 latticeExtra_0.6-29
[106] hwriter_1.3.2 ShortRead_1.48.0 KernSmooth_2.23-20
[109] MASS_7.3-55 gtools_3.9.2 assertthat_0.2.1
[112] DESeq2_1.30.1 openssl_1.4.6 Category_2.56.0
[115] rjson_0.2.21 withr_2.4.3 GenomicAlignments_1.26.0
[118] batchtools_0.9.15 Rsamtools_2.6.0 GenomeInfoDbData_1.2.4
[121] hms_1.1.1 grid_4.0.3 DOT_0.1
[124] coda_0.19-4 GreyListChIP_1.22.0 ashr_2.2-47
[127] mixsqp_0.3-43 bbmle_1.0.24 numDeriv_2016.8-1.1
