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I obtain the following error when trying to create a ChIPQC object:
"Unable to process. Each bam file must be associated with at most one peakset."
I am using the latest version of ChIPQC. This previously worked with version 1.14.0. Has the required sample format changed or is this a regression that can be fixed?
The below log shows all of my commands.
> samples <- read.delim("QCexperiment.csv", stringsAsFactors=FALSE)
> experiment <- ChIPQC(samples, annotation="hg38")
ENCFF863PSQ DOHH2 CTCF 1 bed
Error in ChIPQC(samples, annotation = "hg38") :
Unable to process. Each bam file must be associated with at most one peakset.
> samples
SampleID Tissue Factor Replicate bamReads
1 ENCFF863PSQ DOHH2 CTCF 1 ENCFF863PSQ.sorted.markeddup.bam
ControlID bamControl Peaks
1 ENCFF631ENA ENCFF631ENA.sorted.markeddup.bam NA
> samples <- read.delim("QCexperiment.csv")
> samples
SampleID Tissue Factor Replicate bamReads
1 ENCFF863PSQ DOHH2 CTCF 1 ENCFF863PSQ.sorted.markeddup.bam
ControlID bamControl Peaks
I believe that the error checking is accessing an object which lacks the column name, resulting in this error, as shown here:
> experiment = dba(sampleSheet=samples,peakCaller="bed")
ENCFF863PSQ DOHH2 CTCF 1 bed
> experiment$config$mapQCth = 15
> meta = data.frame(t(experiment$class))
> length(unique(meta$bamRead))
[1] 0
> meta
X1 X2 X3 X4 X5 X6 X7 X8 X9
ENCFF863PSQ ENCFF863PSQ DOHH2 CTCF FALSE bed ENCFF631ENA <NA> 1
X10 X11
ENCFF863PSQ ENCFF863PSQ.sorted.markeddup.bam ENCFF631ENA.sorted.markeddup.bam
X12 X13
ENCFF863PSQ <NA>
> sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS/LAPACK: /mnt/work1/users/home2/cviner/.pyenv/versions/miniconda3-latest/envs/Nat_Protoc_2021/lib/libopenblasp-r0.3.12.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] stats4 parallel stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] ChIPQC_1.26.0
[2] DiffBind_3.0.15
[3] SummarizedExperiment_1.20.0
[4] MatrixGenerics_1.2.1
[5] matrixStats_0.58.0
[6] ggplot2_3.3.3
[7] TxDb.Hsapiens.UCSC.hg38.knownGene_3.10.0
[8] GenomicFeatures_1.42.3
[9] AnnotationDbi_1.52.0
[10] Biobase_2.50.0
[11] GenomicRanges_1.42.0
[12] GenomeInfoDb_1.26.7
[13] IRanges_2.24.1
[14] S4Vectors_0.28.1
[15] BiocGenerics_0.36.0
loaded via a namespace (and not attached):
[1] backports_1.2.1
[2] GOstats_2.56.0
[3] BiocFileCache_1.14.0
[4] plyr_1.8.6
[5] GSEABase_1.52.1
[6] splines_4.0.3
[7] BiocParallel_1.24.1
[8] amap_0.8-18
[9] digest_0.6.27
[10] invgamma_1.1
[11] GO.db_3.12.1
[12] SQUAREM_2021.1
[13] fansi_0.4.2
[14] magrittr_2.0.1
[15] checkmate_2.0.0
[16] memoise_2.0.0
[17] BSgenome_1.58.0
[18] base64url_1.4
[19] limma_3.46.0
[20] Nozzle.R1_1.1-1
[21] Biostrings_2.58.0
[22] annotate_1.68.0
[23] systemPipeR_1.24.3
[24] askpass_1.1
[25] bdsmatrix_1.3-4
[26] prettyunits_1.1.1
[27] jpeg_0.1-8.1
[28] colorspace_2.0-0
[29] blob_1.2.1
[30] rappdirs_0.3.3
[31] apeglm_1.12.0
[32] ggrepel_0.9.1
[33] dplyr_1.0.5
[34] crayon_1.4.1
[35] RCurl_1.98-1.3
[36] jsonlite_1.7.2
[37] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[38] graph_1.68.0
[39] chipseq_1.40.0
[40] genefilter_1.72.1
[41] brew_1.0-6
[42] survival_3.2-10
[43] VariantAnnotation_1.36.0
[44] glue_1.4.2
[45] gtable_0.3.0
[46] zlibbioc_1.36.0
[47] XVector_0.30.0
[48] DelayedArray_0.16.3
[49] V8_3.4.0
[50] Rgraphviz_2.34.0
[51] scales_1.1.1
[52] pheatmap_1.0.12
[53] mvtnorm_1.1-1
[54] DBI_1.1.1
[55] edgeR_3.32.1
[56] TxDb.Mmusculus.UCSC.mm9.knownGene_3.2.2
[57] Rcpp_1.0.6
[58] xtable_1.8-4
[59] progress_1.2.2
[60] emdbook_1.3.12
[61] bit_4.0.4
[62] rsvg_2.1
[63] AnnotationForge_1.32.0
[64] truncnorm_1.0-8
[65] httr_1.4.2
[66] gplots_3.1.1
[67] RColorBrewer_1.1-2
[68] ellipsis_0.3.1
[69] pkgconfig_2.0.3
[70] XML_3.99-0.6
[71] dbplyr_2.1.1
[72] locfit_1.5-9.4
[73] utf8_1.2.1
[74] reshape2_1.4.4
[75] tidyselect_1.1.0
[76] rlang_0.4.10
[77] munsell_0.5.0
[78] tools_4.0.3
[79] cachem_1.0.4
[80] generics_0.1.0
[81] RSQLite_2.2.5
[82] stringr_1.4.0
[83] fastmap_1.1.0
[84] yaml_2.2.1
[85] bit64_4.0.5
[86] caTools_1.18.2
[87] purrr_0.3.4
[88] RBGL_1.66.0
[89] TxDb.Rnorvegicus.UCSC.rn4.ensGene_3.2.2
[90] xml2_1.3.2
[91] biomaRt_2.46.3
[92] compiler_4.0.3
[93] rstudioapi_0.13
[94] curl_4.3
[95] png_0.1-7
[96] tibble_3.1.0
[97] stringi_1.5.3
[98] TxDb.Hsapiens.UCSC.hg18.knownGene_3.2.2
[99] lattice_0.20-41
[100] Matrix_1.3-2
[101] vctrs_0.3.7
[102] pillar_1.6.0
[103] lifecycle_1.0.0
[104] TxDb.Mmusculus.UCSC.mm10.knownGene_3.10.0
[105] irlba_2.3.3
[106] data.table_1.14.0
[107] bitops_1.0-6
[108] TxDb.Celegans.UCSC.ce6.ensGene_3.2.2
[109] rtracklayer_1.50.0
[110] R6_2.5.0
[111] latticeExtra_0.6-29
[112] hwriter_1.3.2
[113] ShortRead_1.48.0
[114] KernSmooth_2.23-18
[115] MASS_7.3-53.1
[116] gtools_3.8.2
[117] assertthat_0.2.1
[118] openssl_1.4.3
[119] Category_2.56.0
[120] rjson_0.2.20
[121] withr_2.4.1
[122] GenomicAlignments_1.26.0
[123] batchtools_0.9.15
[124] Rsamtools_2.6.0
[125] GenomeInfoDbData_1.2.4
[126] hms_1.0.0
[127] grid_4.0.3
[128] TxDb.Dmelanogaster.UCSC.dm3.ensGene_3.2.2
[129] DOT_0.1
[130] coda_0.19-4
[131] GreyListChIP_1.22.0
[132] ashr_2.2-47
[133] mixsqp_0.3-43
[134] bbmle_1.0.23.1
[135] numDeriv_2016.8-1.1
Add another sample could solve this problem, which works for me.
I've looked this issue up and multiple sites list the answer as "Add another sample". I'm completely new to this and I don't understand what this means. Can someone clarify? I only have one sample at this point. Do I just want another row in the .csv file pointing to the same .bam files?