Entering edit mode
3.8 years ago
loveleaves102
•
0
Hello,
I'm using DiffBind to identify differential binding affinity of histone marks H3k27ac between two conditions. I set the summits
parameter in dba.count()
, but the resulting peaks still have different widths. For example:
seqname start end width
6 29330809 29331809 1001
9 43674228 43675228 1001
1 84561539 84563500 1962
Can you guys help explain this to me? Thank you a lot! The following is my code:
enhancer <- dba(sampleSheet = sample, peakFormat = "narrow", scoreCol = 9)
enhancer <- dba.count(enhancer, minOverlap = 4, summits = 500, score=DBA_SCORE_TMM_MINUS_FULL)
enhancer <- dba.contrast(enhancer, enhancer$masks$cond1, enhancer$masks$cond2, "cond1", "con2")
enhancer <- dba.analyze(enhancer, method=DBA_ALL_METHODS, bSubControl = FALSE, bFullLibrarySize = FALSE, bTagwise = TRUE)
enhancer.DB <- dba.report(enhancer, method=DBA_EDGER)
This is my session info:
> sessionInfo()
R version 3.6.0 (2019-04-26)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux
Matrix products: default
BLAS/LAPACK: /path/to/lib/libopenblas_haswell-r0.3.4.so
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] parallel stats4 stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] DiffBind_2.14.0 SummarizedExperiment_1.16.1
[3] DelayedArray_0.12.3 BiocParallel_1.20.1
[5] matrixStats_0.56.0 Biobase_2.46.0
[7] GenomicRanges_1.38.0 GenomeInfoDb_1.22.1
[9] IRanges_2.20.2 S4Vectors_0.24.4
[11] BiocGenerics_0.32.0
loaded via a namespace (and not attached):
[1] Category_2.52.1 bitops_1.0-6 bit64_0.9-7
[4] RColorBrewer_1.1-2 progress_1.2.2 httr_1.4.1
[7] Rgraphviz_2.30.0 backports_1.1.6 tools_3.6.0
[10] R6_2.4.1 KernSmooth_2.23-16 DBI_1.1.0
[13] colorspace_1.4-1 withr_2.1.2 tidyselect_1.0.0
[16] prettyunits_1.1.1 bit_1.1-15.2 curl_4.3
[19] compiler_3.6.0 graph_1.64.0 cli_2.0.2
[22] rtracklayer_1.46.0 checkmate_2.0.0 caTools_1.18.0
[25] scales_1.1.0 genefilter_1.68.0 RBGL_1.62.1
[28] askpass_1.1 rappdirs_0.3.1 stringr_1.4.0
[31] digest_0.6.25 Rsamtools_2.2.3 AnnotationForge_1.28.0
[34] XVector_0.26.0 jpeg_0.1-8.1 pkgconfig_2.0.3
[37] BSgenome_1.54.0 dbplyr_1.4.2 limma_3.42.2
[40] rlang_0.4.5 RSQLite_2.2.0 GOstats_2.52.0
[43] hwriter_1.3.2 gtools_3.8.2 dplyr_0.8.5
[46] VariantAnnotation_1.32.0 RCurl_1.98-1.1 magrittr_1.5
[49] GO.db_3.10.0 GenomeInfoDbData_1.2.2 Matrix_1.2-18
[52] Rcpp_1.0.4.6 munsell_0.5.0 fansi_0.4.1
[55] lifecycle_0.2.0 yaml_2.2.1 stringi_1.4.6
[58] edgeR_3.28.1 zlibbioc_1.32.0 gplots_3.0.3
[61] BiocFileCache_1.10.2 grid_3.6.0 blob_1.2.1
[64] ggrepel_0.8.2 gdata_2.18.0 crayon_1.3.4
[67] lattice_0.20-41 splines_3.6.0 Biostrings_2.54.0
[70] annotate_1.64.0 GenomicFeatures_1.38.2 hms_0.5.3
[73] batchtools_0.9.13 locfit_1.5-9.4 pillar_1.4.3
[76] rjson_0.2.20 systemPipeR_1.20.0 base64url_1.4
[79] biomaRt_2.42.1 XML_3.99-0.3 glue_1.4.0
[82] ShortRead_1.44.3 latticeExtra_0.6-29 data.table_1.12.8
[85] vctrs_0.2.4 png_0.1-7 gtable_0.3.0
[88] openssl_1.4.1 purrr_0.3.3 amap_0.8-18
[91] assertthat_0.2.1 ggplot2_3.3.0 xtable_1.8-4
[94] survival_3.1-12 pheatmap_1.0.12 tibble_3.0.0
[97] GenomicAlignments_1.22.1 AnnotationDbi_1.48.0 memoise_1.1.0
[100] brew_1.0-6 ellipsis_0.3.0 GSEABase_1.48.0
Note that if you run dba.count() again using the consensus peaks from the first call, it will find the summit of the merged peak and re-center, leaving you with all peaks the same width (but one fewer peak)..