I am performing a differential accessibility analysis of ATACseq data with diffbind after using MACS2 for peak calling. However, somehow (I don't know where it goes wrong) the chromosomes are just numbered 1, 2, 3 etc in my peak files instead of chr1, chr2, chr3. Here's my code for differential analysis:
>OT1 <- dba(sampleSheet = samples) >OT1 <- dba.count(OT1, summits = 250) >OT1 <- dba.normalize(OT1, library = DBA_LIBSIZE_PEAKREADS) >OT1 <- dba.contrast(OT1, categories = DBA_CONDITION)
And now I want to remove blacklisted regions
> OT1 <- dba.blacklist(OT1, blacklist = DBA_BLACKLIST_MM10, greylist = FALSE) Genome detected: Mmusculus.UCSC.mm10 Applying blacklist... Removed: 0 of 70147 intervals. No intervals removed. Warning message: Blacklist does not overlap any peak chromosomes!
The warning is because in the blacklisted file the chromosomes are names chr1, chr2, chr3 and in my dba object 1, 2, 3 etc.
Is there an easy way to add chr to a dba object? I know how to do it with addchr() to a GRanges object but is there a similar approach for this case? That will allow me to continue my analysis without having to redo MACS2 or any steps before where the chr should've been included.
> sessionInfo() R version 4.0.4 (2021-02-15) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 19042) Matrix products: default locale:  LC_COLLATE=Dutch_Netherlands.1252 LC_CTYPE=Dutch_Netherlands.1252  LC_MONETARY=Dutch_Netherlands.1252 LC_NUMERIC=C  LC_TIME=Dutch_Netherlands.1252 attached base packages:  parallel stats4 stats graphics grDevices utils datasets methods base other attached packages:  org.Mm.eg.db_3.12.0 forcats_0.5.1  stringr_1.4.0 dplyr_1.0.5  purrr_0.3.4 readr_1.4.0  tidyr_1.1.3 tibble_3.1.0  ggplot2_3.3.3 tidyverse_1.3.0  diffloop_1.18.0 TxDb.Mmusculus.UCSC.mm10.knownGene_3.10.0  GenomicFeatures_1.42.2 AnnotationDbi_1.52.0  DiffBind_3.0.14 SummarizedExperiment_1.20.0  Biobase_2.50.0 MatrixGenerics_1.2.1  matrixStats_0.58.0 GenomicRanges_1.42.0  GenomeInfoDb_1.26.4 IRanges_2.24.1  S4Vectors_0.28.1 BiocGenerics_0.36.0  ChIPseeker_1.26.2