Open Sherry520 opened 5 months ago
library(ChIPseeker) require(GenomicFeatures) GFF_PATH = 'f:/07-CAUS/01-Linux-service/Maize_reference/B73-Ensembl-V4-48/Zea_mays.B73_RefGen_v4.48.gff3.gz' maizev4.db <- makeTxDbFromGFF(GFF_PATH,format = "gff3") peak <- readPeakFile("WRKY67-peak.rmchr.bed") peakAnno <- annotatePeak("WRKY67-peak.rmchr.bed",tssRegion = c(-3000, 3000),TxDb = maizev4.db) peakAnno.df <- as.data.frame(peakAnno) openxlsx::write.xlsx(peakAnno.df,"WRKY67-peak.xlsx")
peak注释的结果中,染色体是ctg开头的,在geneChr的编号成了数字
> sessionInfo() R version 4.3.2 (2023-10-31 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 19045) Matrix products: default locale: [1] LC_COLLATE=Chinese (Simplified)_China.utf8 LC_CTYPE=Chinese (Simplified)_China.utf8 [3] LC_MONETARY=Chinese (Simplified)_China.utf8 LC_NUMERIC=C [5] LC_TIME=Chinese (Simplified)_China.utf8 time zone: Asia/Shanghai tzcode source: internal attached base packages: [1] stats4 stats graphics grDevices utils datasets methods base other attached packages: [1] dplyr_1.1.4 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 ggplot2_3.4.4 [4] GenomicFeatures_1.54.4 AnnotationDbi_1.64.1 Biobase_2.62.0 [7] GenomicRanges_1.54.1 GenomeInfoDb_1.38.1 IRanges_2.36.0 [10] S4Vectors_0.40.2 BiocGenerics_0.48.1 ChIPseeker_1.38.0 [13] BiocManager_1.30.22 loaded via a namespace (and not attached): [1] RColorBrewer_1.1-3 jsonlite_1.8.7 rstudioapi_0.15.0 magrittr_2.0.3 [5] farver_2.1.1 rmarkdown_2.25 fs_1.6.3 BiocIO_1.12.0 [9] zlibbioc_1.48.0 vctrs_0.6.4 memoise_2.0.1 Rsamtools_2.18.0 [13] RCurl_1.98-1.13 ggtree_3.10.0 htmltools_0.5.7 S4Arrays_1.2.0 [17] progress_1.2.2 plotrix_3.8-4 curl_5.1.0 SparseArray_1.2.2 [21] gridGraphics_0.5-1 KernSmooth_2.23-22 plyr_1.8.9 cachem_1.0.8 [25] GenomicAlignments_1.38.1 igraph_1.5.1 lifecycle_1.0.4 pkgconfig_2.0.3 [29] Matrix_1.6-4 R6_2.5.1 fastmap_1.1.1 GenomeInfoDbData_1.2.11 [33] MatrixGenerics_1.14.0 digest_0.6.33 aplot_0.2.2 enrichplot_1.22.0 [37] colorspace_2.1-0 patchwork_1.1.3 DESeq2_1.42.0 RSQLite_2.3.3 [41] labeling_0.4.3 filelock_1.0.2 fansi_1.0.5 httr_1.4.7 [45] polyclip_1.10-6 abind_1.4-5 compiler_4.3.2 bit64_4.0.5 [49] withr_2.5.2 BiocParallel_1.36.0 viridis_0.6.4 DBI_1.1.3 [53] gplots_3.1.3.1 ggforce_0.4.1 biomaRt_2.58.2 MASS_7.3-60 [57] rappdirs_0.3.3 DelayedArray_0.28.0 rjson_0.2.21 HDO.db_0.99.1 [61] caTools_1.18.2 gtools_3.9.5 tools_4.3.2 scatterpie_0.2.1 [65] ape_5.7-1 zip_2.3.0 glue_1.6.2 restfulr_0.0.15 [69] nlme_3.1-163 GOSemSim_2.28.0 shadowtext_0.1.2 grid_4.3.2 [73] reshape2_1.4.4 fgsea_1.28.0 generics_0.1.3 gtable_0.3.4 [77] tidyr_1.3.0 data.table_1.14.8 hms_1.1.3 tidygraph_1.2.3 [81] xml2_1.3.5 utf8_1.2.4 XVector_0.42.0 ggrepel_0.9.4 [85] pillar_1.9.0 stringr_1.5.1 yulab.utils_0.1.0 splines_4.3.2 [89] tweenr_2.0.2 treeio_1.26.0 BiocFileCache_2.10.1 lattice_0.21-9 [93] rtracklayer_1.62.0 bit_4.0.5 tidyselect_1.2.0 locfit_1.5-9.8 [97] GO.db_3.18.0 Biostrings_2.70.1 knitr_1.45 gridExtra_2.3 [101] SummarizedExperiment_1.32.0 xfun_0.41 graphlayouts_1.0.2 factoextra_1.0.7 [105] matrixStats_1.1.0 stringi_1.8.1 lazyeval_0.2.2 ggfun_0.1.3 [109] yaml_2.3.7 boot_1.3-28.1 evaluate_0.23 codetools_0.2-19 [113] RMariaDB_1.3.1 ggraph_2.1.0 qvalue_2.34.0 tibble_3.2.1 [117] ggplotify_0.1.2 cli_3.6.1 munsell_0.5.0 Rcpp_1.0.11 [121] dbplyr_2.4.0 png_0.1-8 XML_3.99-0.16 parallel_4.3.2 [125] blob_1.2.4 prettyunits_1.2.0 DOSE_3.28.1 bitops_1.0-7 [129] tidytree_0.4.5 viridisLite_0.4.2 scales_1.2.1 openxlsx_4.2.5.2 [133] purrr_1.0.2 crayon_1.5.2 rlang_1.1.2 cowplot_1.1.1 [137] fastmatch_1.1-4 KEGGREST_1.42.0
peak注释的结果中,染色体是ctg开头的,在geneChr的编号成了数字