Hi, I just got this error message when using ChIPQC (with a metadata table for 4 bam files with peak info...):
Error: BiocParallel errors 4 remote errors, element index: 1, 2, 3, 4 0 unevaluated and other errors
first remote error: Error in if (is.na(peaks)) peaks = NULL: the condition has length > 1
With the following command:
chipObj <- ChIPQC(samples)
Show Traceback gives me:
7. stop(.error_bplist(res))
6. .bpinit(manager = manager, X = X, FUN = FUN, ARGS = ARGS, BPPARAM = BPPARAM,
BPOPTIONS = BPOPTIONS, BPREDO = BPREDO)
5. bplapply(X, FUN, ..., BPREDO = BPREDO, BPPARAM = BPPARAM, BPOPTIONS = BPOPTIONS)
4. bplapply(X, FUN, ..., BPREDO = BPREDO, BPPARAM = BPPARAM, BPOPTIONS = BPOPTIONS)
3. bplapply(samplelist, doChIPQCsample, experiment, chromosomes,
annotation, mapQCth, blacklist, profileWin, fragmentLength,
shifts)
2. bplapply(samplelist, doChIPQCsample, experiment, chromosomes,
annotation, mapQCth, blacklist, profileWin, fragmentLength,
shifts)
1. ChIPQC(samples)
After getting this error, I tried to run ChIPQC with files that had given me great results in the past (ChIPQC report...) and I got the same error message. I can't analyze these other ChIP-seq datasets anymore. I recently updated a bunch of R packages so my guess would be that the new version of one of the packages is encountering some issue.
I tried to install a previous version of ChIPQC (3.10 or 3.11) with:
BiocManager::install("ChIPQC", version = "3.11")
and kept getting error messages of this type:
Error: Bioconductor version '3.11' requires R version '4.0'; use `BiocManager::install(version = '3.15')` with R version 4.2; see https://bioconductor.org/install
I already the version 3.15 of BiocManager and the version 4.2 of R so I am not sure how to overcome this error.
A similar ChIPQC issue (from 3.8 years ago) was described here: ChIPQC - can't read in bam files
It was suggested in the comments to try to open the bam files with Rsamtools function open.bamFile(). I just did that and got the following error message:
Error in value[[3L]](cond) :
failed to open BamFile: unable to find an inherited method for function 'path' for signature '"character"'
6. stop("failed to open BamFile: ", conditionMessage(err))
5. value[[3L]](cond)
4. tryCatchOne(expr, names, parentenv, handlers[[1L]])
3. tryCatchList(expr, classes, parentenv, handlers)
2. tryCatch({
.io_check_exists(path(con))
index <- sub("\\.bai$", "", index(con, asNA = FALSE))
con$.extptr <- .Call(.bamfile_open, path(con), index, "rb") ...
1. open.BamFile("extract_14M_1_PEO1_G9A_1_S4_L002.bam")
Could there be an issue with the latest version of Rsamtools or am I not using Rsamtools correctly?
From another Bioconductor question: DiffBind GreyListChIP error: Error: BiocParallel errors
I tried:
BiocParallel::register(BiocParallel::SerialParam())
And this did not solve my issue.
I also tried a few other things like clearing the workspace, relaunching R, RStudio, my computer, installing the newest version of RStudio, reindexing the bam files... I tried on a different computer that has unfortunately also updated many R packages (it has the version 3.12 of ChIPQC) and got the same error message.
If anyone has any solution or ideas I could try to solve this issue, it would be fantastic and greatly appreciated.
Thank you very much in advance.
Best,
Etienne
sessionInfo( ):
R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] BiocParallel_1.31.8 valr_0.6.4 ChIPseeker_1.32.0 org.Mm.eg.db_3.15.0 ensembldb_2.20.2 AnnotationFilter_1.20.0 GenomicFeatures_1.48.3 AnnotationDbi_1.58.0 AnnotationHub_3.4.0 BiocFileCache_2.4.0
[11] dbplyr_2.1.1 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.9 purrr_0.3.4 readr_2.1.2 tidyr_1.2.0 tibble_3.1.7 tidyverse_1.3.1 ChIPQC_1.32.0
[21] DiffBind_3.6.1 SummarizedExperiment_1.26.1 Biobase_2.56.0 MatrixGenerics_1.8.0 matrixStats_0.62.0 GenomicRanges_1.48.0 GenomeInfoDb_1.32.2 IRanges_2.30.0 S4Vectors_0.34.0 BiocGenerics_0.42.0
[31] ggplot2_3.3.6
loaded via a namespace (and not attached):
[1] utf8_1.2.2 tidyselect_1.1.2 RSQLite_2.2.14 htmlwidgets_1.5.4 grid_4.2.0 scatterpie_0.1.7
[7] munsell_0.5.0 codetools_0.2-18 systemPipeR_2.2.2 withr_2.5.0 colorspace_2.0-3 GOSemSim_2.22.0
[13] filelock_1.0.2 knitr_1.39 rstudioapi_0.13 DOSE_3.22.0 bbmle_1.0.25 GenomeInfoDbData_1.2.8
[19] polyclip_1.10-0 mixsqp_0.3-43 hwriter_1.3.2.1 farver_2.1.0 bit64_4.0.5 treeio_1.20.0
[25] coda_0.19-4 vctrs_0.4.1 TxDb.Rnorvegicus.UCSC.rn4.ensGene_3.2.2 generics_0.1.2 xfun_0.31 R6_2.5.1
[31] graphlayouts_0.8.0 apeglm_1.18.0 invgamma_1.1 locfit_1.5-9.5 gridGraphics_0.5-1 fgsea_1.22.0
[37] bitops_1.0-7 cachem_1.0.6 DelayedArray_0.22.0 assertthat_0.2.1 vroom_1.5.7 promises_1.2.0.1
[43] BiocIO_1.6.0 scales_1.2.0 ggraph_2.0.5 enrichplot_1.16.1 gtable_0.3.0 tidygraph_1.2.1
[49] rlang_1.0.2 splines_4.2.0 rtracklayer_1.56.0 lazyeval_0.2.2 broom_0.8.0 BiocManager_1.30.18
[55] yaml_2.3.5 reshape2_1.4.4 modelr_0.1.8 TxDb.Dmelanogaster.UCSC.dm3.ensGene_3.2.2 backports_1.4.1 httpuv_1.6.5
[61] qvalue_2.28.0 tools_4.2.0 ggplotify_0.1.0 ellipsis_0.3.2 gplots_3.1.3 RColorBrewer_1.1-3
[67] Rcpp_1.0.8.3 plyr_1.8.7 progress_1.2.2 zlibbioc_1.42.0 RCurl_1.98-1.7 prettyunits_1.1.1
[73] viridis_0.6.2 ashr_2.2-54 chipseq_1.46.0 haven_2.5.0 ggrepel_0.9.1 fs_1.5.2
[79] magrittr_2.0.3 data.table_1.14.2 TxDb.Hsapiens.UCSC.hg18.knownGene_3.2.2 DO.db_2.9 reprex_2.0.1 truncnorm_1.0-8
[85] mvtnorm_1.1-3 SQUAREM_2021.1 amap_0.8-18 ProtGenerics_1.28.0 TxDb.Mmusculus.UCSC.mm9.knownGene_3.2.2 patchwork_1.1.1
[91] hms_1.1.1 mime_0.12 xtable_1.8-4 XML_3.99-0.10 emdbook_1.3.12 jpeg_0.1-9
[97] readxl_1.4.0 gridExtra_2.3 compiler_4.2.0 biomaRt_2.52.0 bdsmatrix_1.3-4 shadowtext_0.1.2
[103] KernSmooth_2.23-20 crayon_1.5.1 htmltools_0.5.2 ggfun_0.0.6 later_1.3.0 tzdb_0.3.0
[109] aplot_0.1.6 lubridate_1.8.0 DBI_1.1.2 tweenr_1.0.2 MASS_7.3-57 rappdirs_0.3.3
[115] boot_1.3-28 ShortRead_1.54.0 Matrix_1.4-1 cli_3.3.0 parallel_4.2.0 igraph_1.3.2
[121] pkgconfig_2.0.3 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 GenomicAlignments_1.32.0 numDeriv_2016.8-1.1 TxDb.Celegans.UCSC.ce6.ensGene_3.2.2 xml2_1.3.3
[127] ggtree_3.4.0 XVector_0.36.0 rvest_1.0.2 yulab.utils_0.0.4 digest_0.6.29 Biostrings_2.64.0
[133] fastmatch_1.1-3 cellranger_1.1.0 tidytree_0.3.9 restfulr_0.0.13 GreyListChIP_1.28.1 curl_4.3.2
[139] shiny_1.7.1 Rsamtools_2.12.0 gtools_3.9.2 rjson_0.2.21 nlme_3.1-157 lifecycle_1.0.1
[145] jsonlite_1.8.0 viridisLite_0.4.0 limma_3.52.1 BSgenome_1.64.0 fansi_1.0.3 pillar_1.7.0
[151] lattice_0.20-45 Nozzle.R1_1.1-1 plotrix_3.8-2 KEGGREST_1.36.2 fastmap_1.1.0 httr_1.4.3
[157] GO.db_3.15.0 interactiveDisplayBase_1.34.0 glue_1.6.2 png_0.1-7 BiocVersion_3.15.2 bit_4.0.4
[163] ggforce_0.3.3 stringi_1.7.6 blob_1.2.3 TxDb.Mmusculus.UCSC.mm10.knownGene_3.10.0 latticeExtra_0.6-29 caTools_1.18.2
[169] memoise_2.0.1 ape_5.6-2 irlba_2.3.5