输入编辑模式
这两个R代码之间有什么区别，desmatrix.dse是具有多个64条件在内的deseqdatasetfrommatrix，包括重复：
plotma（结果（desmatrix.dse，contrast = c（“条件”，“处理过”，“未处理”），ylim = c（-2,2））＃它给出以下图：
并仅在我的两个条件下创建一个子矩阵
deseq2ni18vsun.dse <-desmatrix.dse [，desmatrix.dse@coldata@listData $ condition％in％c（“ treatedc”，“未处理”] deseq2ni18vsun.res $条件按预期给出：1未处理处理的未处理处理[5]治疗治疗的未治疗的治疗
＃然后提取结果以进行绘图res < - 结果（deseq2ni18vsun.dse）plotma（res，ylim = c（-2,2））
这看起来很等同于在获得的所有数据上的图：
plotma（desmatrix.dse，ylim = c（-2,2））
因此，我的subsatrix deseq2ni18vsun.dse真的是desmatrix.dse的子集吗？如果有人可以解释我为什么我不会得到我预期的同样的东西。希望，我已经给出了所有要素以了解情况。感谢您抽出宝贵的时间来研究。
这是我的R条件：
sessionInfo( ) R version 4.0.4 (2021-02-15) Platform: x86_64-apple-darwin17.0 (64-bit) Running under: macOS Mojave 10.14.6 Matrix products: default BLAS: /System/Library/Frameworks/accelerate.framework/versions/a/frameworks/veclib.framework/versions/a/libblas.dylib lapack：/library/frameworks/r.frameworks/r.frameworks/resources/4.0/resources/rib/lib/librlapack.dylib locale：[1] fr_fr。UTF-8/FR_FR.UTF-8/FR_FR.UTF-8/C/FR_FR.UTF-8/FR_FR.UTF.UTF-8附件基本软件包：[1] STATS4 Stats4 Parallel Stats Grable grdevices grdevices utils utils utils datasets datasets方法基础其他附件其他软件包：[[[[[[[[1]1] apeglm_1.12.0 kableExtra_1.3.4 org.Dm.eg.db_3.12.0 GOstats_2.56.0 [5] graph_1.68.0 Category_2.56.0 Matrix_1.3-2 AnnotationDbi_1.52.0 [9] ReportingTools_2.30.2 knitr_1.32 RColorBrewer_1.1-2 gplots_3.1.1 [13] ggplot2_3.3.3 dplyr_1.0.5 DESeq2_1.30.1 SummarizedExperiment_1.20.0 [17] MatrixGenerics_1.2.1 matrixStats_0.58.0 GenomicRanges_1.42.0 GenomeInfoDb_1.26.7 [21] IRanges_2.24.1 S4Vectors_0.28.1 Biobase_2.50.0 BiocGenerics_0.36.0 loaded via a namespace (and not attached): [1] backports_1.2.1 Hmisc_4.5-0 systemfonts_1.0.1 BiocFileCache_1.14.0 [5] plyr_1.8.6 lazyeval_0.2.2 GSEABase_1.52.1 splines_4.0.4 [9] BiocParallel_1.24.1 digest_0.6.27 ensembldb_2.14.0 htmltools_0.5.1.1 [13] GO.db_3.12.1 fansi_0.4.2 magrittr_2.0.1 checkmate_2.0.0 [17] memoise_2.0.0 BSgenome_1.58.0 cluster_2.1.1 limma_3.46.0 [21] Biostrings_2.58.0 annotate_1.68.0 R.utils_2.10.1 svglite_2.0.0 [25] ggbio_1.38.0 bdsmatrix_1.3-4 askpass_1.1 prettyunits_1.1.1 [29] jpeg_0.1-8.1 colorspace_2.0-0 rvest_1.0.0 blob_1.2.1 [33] rappdirs_0.3.3 xfun_0.22 jsonlite_1.7.2 crayon_1.4.1 [37] RCurl_1.98-1.3 genefilter_1.72.1 survival_3.2-10 VariantAnnotation_1.36.0 [41] glue_1.4.2 gtable_0.3.0 zlibbioc_1.36.0 XVector_0.30.0 [45] webshot_0.5.2 DelayedArray_0.16.3 Rgraphviz_2.34.0 scales_1.1.1 [49] mvtnorm_1.1-1 DBI_1.1.1 GGally_2.1.1 edgeR_3.32.1 [53] Rcpp_1.0.6 emdbook_1.3.12 viridisLite_0.4.0 xtable_1.8-4 [57] progress_1.2.2 htmlTable_2.1.0 foreign_0.8-81 bit_4.0.4 [61] OrganismDbi_1.32.0 Formula_1.2-4 AnnotationForge_1.32.0 htmlwidgets_1.5.3 [65] httr_1.4.2 ellipsis_0.3.1 pkgconfig_2.0.3 reshape_0.8.8 [69] XML_3.99-0.6 R.methodsS3_1.8.1 sass_0.3.1 nnet_7.3-15 [73] dbplyr_2.1.1 locfit_1.5-9.4 utf8_1.2.1 tidyselect_1.1.0 [77] rlang_0.4.10 reshape2_1.4.4 munsell_0.5.0 tools_4.0.4 [81] cachem_1.0.4 generics_0.1.0 RSQLite_2.2.6 evaluate_0.14 [85] stringr_1.4.0 fastmap_1.1.0 yaml_2.2.1 bit64_4.0.5 [89] caTools_1.18.2 purrr_0.3.4 AnnotationFilter_1.14.0 RBGL_1.66.0 [93] R.oo_1.24.0 xml2_1.3.2 biomaRt_2.46.3 compiler_4.0.4 [97] rstudioapi_0.13 curl_4.3 png_0.1-7 PFAM.db_3.12.0 [101] tibble_3.1.0 geneplotter_1.68.0 bslib_0.2.4 stringi_1.5.3 [105] highr_0.8 GenomicFeatures_1.42.3 lattice_0.20-41 ProtGenerics_1.22.0 [109] vctrs_0.3.7 pillar_1.6.0 lifecycle_1.0.0 BiocManager_1.30.12 [113] jquerylib_0.1.3 data.table_1.14.0 bitops_1.0-6 rtracklayer_1.50.0 [117] hwriter_1.3.2 R6_2.5.0 latticeExtra_0.6-29 KernSmooth_2.23-18 [121] gridExtra_2.3 dichromat_2.0-0 MASS_7.3-53.1 gtools_3.8.2 [125] assertthat_0.2.1 openssl_1.4.3 withr_2.4.1 GenomicAlignments_1.26.0 [129] Rsamtools_2.6.0 GenomeInfoDbData_1.2.4 hms_1.0.0 grid_4.0.4 [133] rpart_4.1-15 coda_0.19-4 rmarkdown_2.7 biovizBase_1.38.0 [137] bbmle_1.0.23.1 numDeriv_2016.8-1.1 base64enc_0.1-3
