Hi
I am trying to avoid NCBI/UCSC reference genome incompatibility issues by keeping everything NCBI. To run AddMotifs, I am attempting to use a FaFile as the "genome" (I cannot find a BSgenome for chicken that is NCBI-based).
I would appreciate any advice ...
Thanks.
Heithem
When I attempt to run AddMotifs:
DefaultAssay(object) <- 'peaks'
pfm <- getMatrixSet(
x = JASPAR2020,
opts = list(collection = "CORE", tax_group = 'vertebrates', all_versions = FALSE)
)
object <- AddMotifs(
object = object,
genome = chickfasta,
pfm = pfm
)
Building motif matrix
Finding motif positions
Creating Motif object
Error in readDNAStringSet(path(file), ...) :
unused argument (names = new("GRanges", seqnames = new("Rle", values = c(33, 34, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, ...[truncated]), lengths = c(4, 6755, 17889, 13363, 10786, 9600, 7383, 4541, ... [truncated]), elementMetadata = NULL, metadata = list()), ranges = new("IRanges", start = c(180105, 1636934, 3147323, 3959992, 12126, 23949, 30992, 51590, 53102, ... [trucated])
(I made the truncations)
Other info:
cellranger-ATAC was run using a custom chicken reference library prepared using mkref with fasta and gtf files from Ensembl
Annotations library made using AnnotationHub with matching Ensembl chicken files and seqlevelstyle set to 'NCBI' to match:
ah <- AnnotationHub()
query(ah, "EnsDb")
qr <- query(ah, c("gallus", "EnsDb", 105))
edb <- qr[[1]]
annotations <- GetGRangesFromEnsDb(ensdb = edb)
seqlevelsStyle(annotations) <- 'NCBI'
genome(annotations) <- "GRC6a"
Here's how the FaFile was made
chickfasta <- FaFile(file = "path to Gallus_gallus_GRCg6a_dna_toplevel_Copy.fa", index = "path to Gallus_gallus_GRCg6a_dna_toplevel_Copy.fa.fai")
sessionInfo()
R version 4.1.3 (2022-03-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17763)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] R.utils_2.11.0 R.oo_1.24.0 R.methodsS3_1.8.1
[4] readr_2.1.2 stringr_1.4.0 Rsamtools_2.6.0
[7] TFBSTools_1.32.0 JASPAR2020_0.99.10 BSgenome.Ggallus.UCSC.galGal6_1.4.2
[10] BSgenome_1.62.0 Biostrings_2.58.0 XVector_0.30.0
[13] rtracklayer_1.49.5 Matrix.utils_0.9.8 Matrix_1.4-0
[16] AnnotationHub_2.22.1 BiocFileCache_1.14.0 dbplyr_2.1.1
[19] ensembldb_2.14.1 AnnotationFilter_1.14.0 GenomicFeatures_1.42.3
[22] AnnotationDbi_1.56.2 Biobase_2.50.0 hdf5r_1.3.5
[25] patchwork_1.1.1 ggplot2_3.3.5 GenomicRanges_1.42.0
[28] GenomeInfoDb_1.26.7 IRanges_2.24.1 S4Vectors_0.28.1
[31] BiocGenerics_0.40.0 SeuratObject_4.0.4 Seurat_4.1.0
[34] Signac_1.6.0.9008
loaded via a namespace (and not attached):
[1] rappdirs_0.3.3 SnowballC_0.7.0 scattermore_0.8
[4] tidyr_1.2.0 bit64_4.0.5 knitr_1.37
[7] irlba_2.3.5 DelayedArray_0.16.3 data.table_1.14.2
[10] rpart_4.1.16 KEGGREST_1.34.0 RCurl_1.98-1.6
[13] generics_0.1.2 cowplot_1.1.1 RSQLite_2.2.10
[16] RANN_2.6.1 future_1.24.0 tzdb_0.2.0
[19] bit_4.0.4 spatstat.data_2.1-4 xml2_1.3.3
[22] httpuv_1.6.5 SummarizedExperiment_1.24.0 assertthat_0.2.1
[25] DirichletMultinomial_1.36.0 xfun_0.30 hms_1.1.1
[28] evaluate_0.15 promises_1.2.0.1 fansi_1.0.3
[31] restfulr_0.0.13 progress_1.2.2 caTools_1.18.2
[34] igraph_1.2.11 DBI_1.1.2 htmlwidgets_1.5.4
[37] sparsesvd_0.2 spatstat.geom_2.4-0 purrr_0.3.4
[40] ellipsis_0.3.2 RSpectra_0.16-0 dplyr_1.0.8
[43] backports_1.4.1 annotate_1.72.0 biomaRt_2.50.3
[46] deldir_1.0-6 MatrixGenerics_1.6.0 vctrs_0.4.0
[49] ROCR_1.0-11 abind_1.4-5 cachem_1.0.6
[52] withr_2.5.0 ggforce_0.3.3 grr_0.9.5
[55] vroom_1.5.7 checkmate_2.0.0 sctransform_0.3.3
[58] GenomicAlignments_1.26.0 prettyunits_1.1.1 goftest_1.2-3
[61] cluster_2.1.2 lazyeval_0.2.2 seqLogo_1.60.0
[64] crayon_1.5.1 pkgconfig_2.0.3 slam_0.1-50
[67] labeling_0.4.2 tweenr_1.0.2 nlme_3.1-155
[70] ProtGenerics_1.26.0 nnet_7.3-17 rlang_1.0.2
[73] globals_0.14.0 lifecycle_1.0.1 miniUI_0.1.1.1
[76] dichromat_2.0-0 polyclip_1.10-0 matrixStats_0.61.0
[79] lmtest_0.9-40 ggseqlogo_0.1 zoo_1.8-9
[82] base64enc_0.1-3 ggridges_0.5.3 png_0.1-7
[85] viridisLite_0.4.0 rjson_0.2.21 bitops_1.0-7
[88] KernSmooth_2.23-20 blob_1.2.2 parallelly_1.30.0
[91] spatstat.random_2.2-0 jpeg_0.1-9 CNEr_1.30.0
[94] scales_1.1.1 memoise_2.0.1 magrittr_2.0.3
[97] plyr_1.8.7 ica_1.0-2 zlibbioc_1.36.0
[100] compiler_4.1.3 BiocIO_1.4.0 RColorBrewer_1.1-2
[103] fitdistrplus_1.1-8 cli_3.2.0 listenv_0.8.0
[106] pbapply_1.5-0 htmlTable_2.4.0 Formula_1.2-4
[109] MASS_7.3-55 mgcv_1.8-39 tidyselect_1.1.2
[112] stringi_1.7.6 yaml_2.3.5 latticeExtra_0.6-29
[115] ggrepel_0.9.1 grid_4.1.3 VariantAnnotation_1.36.0
[118] fastmatch_1.1-3 tools_4.1.3 future.apply_1.8.1
[121] parallel_4.1.3 rstudioapi_0.13 TFMPvalue_0.0.8
[124] foreign_0.8-82 lsa_0.73.2 gridExtra_2.3
[127] farver_2.1.0 Rtsne_0.15 digest_0.6.29
[130] BiocManager_1.30.16 pracma_2.3.8 shiny_1.7.1
[133] qlcMatrix_0.9.7 motifmatchr_1.16.0 Rcpp_1.0.8.3
[136] BiocVersion_3.14.0 later_1.3.0 RcppAnnoy_0.0.19
[139] httr_1.4.2 biovizBase_1.38.0 colorspace_2.0-3
[142] XML_3.99-0.9 tensor_1.5 reticulate_1.24
[145] splines_4.1.3 uwot_0.1.11 RcppRoll_0.3.0
[148] spatstat.utils_2.3-0 plotly_4.10.0 xtable_1.8-4
[151] poweRlaw_0.70.6 jsonlite_1.8.0 R6_2.5.1
[154] Hmisc_4.6-0 pillar_1.7.0 htmltools_0.5.2
[157] mime_0.12 glue_1.6.2 fastmap_1.1.0
[160] BiocParallel_1.24.1 interactiveDisplayBase_1.32.0 codetools_0.2-18
[163] utf8_1.2.2 lattice_0.20-45 spatstat.sparse_2.1-0
[166] tibble_3.1.6 curl_4.3.2 leiden_0.3.9
[169] gtools_3.9.2 GO.db_3.14.0 survival_3.3-1
[172] limma_3.50.1 rmarkdown_2.13 docopt_0.7.1
[175] munsell_0.5.0 GenomeInfoDbData_1.2.7 reshape2_1.4.4
[178] gtable_0.3.0 spatstat.core_2.4-0
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