Dorsal Horn and Ventral Lateral White DE analysis
Chih-Hsuan Wu
Last updated: 2024-11-12
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Knit directory: DEanalysis/
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Difference in library size
Asymptotic two-sample Kolmogorov-Smirnov test
data: subset(count_cell_df, Region == group1, totalcount)$totalcount and subset(count_cell_df, Region == group2, totalcount)$totalcount
D = 0.12804, p-value < 2.2e-16
alternative hypothesis: two-sided
Welch Two Sample t-test
data: subset(count_cell_df, Region == group1, totalcount)$totalcount and subset(count_cell_df, Region == group2, totalcount)$totalcount
t = 17.059, df = 7783.8, p-value < 2.2e-16
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
235.2685 296.3577
sample estimates:
mean of x mean of y
1549.826 1284.013 Number of DEGs from each method
Volcano plot
Histogram of p-value/adj.p-value
P-Value comparison across different methods
Log2 fold change comparison across different methods
Violin plot of log2mean of DEGs
Violin plot of gene expression frequency of DEGs
Upset plot
Heatmap of top DEGs
Enrichment analysis
GO object
enrichKEGG object
| Version | Author | Date |
|---|---|---|
| 1e340c7 | C-HW | 2024-10-19 |
R version 4.4.1 (2024-06-14)
Platform: x86_64-apple-darwin20
Running under: macOS Monterey 12.6
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: America/Chicago
tzcode source: internal
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] UpSetR_1.4.0 pathview_1.44.0
[3] org.Hs.eg.db_3.19.1 AnnotationDbi_1.66.0
[5] enrichplot_1.24.4 clusterProfiler_4.12.6
[7] reshape_0.8.9 gridExtra_2.3
[9] pheatmap_1.0.12 SingleCellExperiment_1.26.0
[11] SummarizedExperiment_1.34.0 Biobase_2.64.0
[13] GenomicRanges_1.56.2 GenomeInfoDb_1.40.1
[15] IRanges_2.38.1 S4Vectors_0.42.1
[17] BiocGenerics_0.50.0 MatrixGenerics_1.16.0
[19] matrixStats_1.4.1 ggpubr_0.6.0
[21] dplyr_1.1.4 ggplot2_3.5.1
loaded via a namespace (and not attached):
[1] bitops_1.0-9 fs_1.6.4 spatstat.sparse_3.1-0
[4] httr_1.4.7 RColorBrewer_1.1-3 Rgraphviz_2.48.0
[7] tools_4.4.1 sctransform_0.4.1 backports_1.5.0
[10] utf8_1.2.4 R6_2.5.1 lazyeval_0.2.2
[13] uwot_0.2.2 withr_3.0.1 sp_2.1-4
[16] progressr_0.14.0 cli_3.6.3 spatstat.explore_3.3-2
[19] fastDummies_1.7.4 scatterpie_0.2.4 labeling_0.4.3
[22] sass_0.4.9 KEGGgraph_1.64.0 Seurat_5.1.0
[25] spatstat.data_3.1-2 ggridges_0.5.6 pbapply_1.7-2
[28] yulab.utils_0.1.7 gson_0.1.0 DOSE_3.30.5
[31] R.utils_2.12.3 parallelly_1.38.0 rstudioapi_0.17.0
[34] RSQLite_2.3.7 generics_0.1.3 gridGraphics_0.5-1
[37] ica_1.0-3 spatstat.random_3.3-2 car_3.1-3
[40] GO.db_3.19.1 Matrix_1.7-1 fansi_1.0.6
[43] abind_1.4-8 R.methodsS3_1.8.2 lifecycle_1.0.4
[46] whisker_0.4.1 yaml_2.3.10 carData_3.0-5
[49] qvalue_2.36.0 SparseArray_1.4.8 Rtsne_0.17
[52] grid_4.4.1 blob_1.2.4 promises_1.3.0
[55] crayon_1.5.3 miniUI_0.1.1.1 lattice_0.22-6
[58] cowplot_1.1.3 KEGGREST_1.44.1 pillar_1.9.0
[61] knitr_1.48 fgsea_1.30.0 future.apply_1.11.2
[64] codetools_0.2-20 fastmatch_1.1-4 leiden_0.4.3.1
[67] glue_1.8.0 ggfun_0.1.6 spatstat.univar_3.0-1
[70] data.table_1.16.2 vctrs_0.6.5 png_0.1-8
[73] treeio_1.28.0 spam_2.11-0 gtable_0.3.5
[76] cachem_1.1.0 xfun_0.48 S4Arrays_1.4.1
[79] mime_0.12 tidygraph_1.3.1 survival_3.7-0
[82] fitdistrplus_1.2-1 ROCR_1.0-11 nlme_3.1-166
[85] ggtree_3.12.0 bit64_4.5.2 RcppAnnoy_0.0.22
[88] rprojroot_2.0.4 bslib_0.8.0 irlba_2.3.5.1
[91] KernSmooth_2.23-24 colorspace_2.1-1 DBI_1.2.3
[94] tidyselect_1.2.1 bit_4.5.0 compiler_4.4.1
[97] git2r_0.35.0 graph_1.82.0 httr2_1.0.5
[100] DelayedArray_0.30.1 plotly_4.10.4 shadowtext_0.1.4
[103] scales_1.3.0 lmtest_0.9-40 rappdirs_0.3.3
[106] stringr_1.5.1 digest_0.6.37 goftest_1.2-3
[109] spatstat.utils_3.1-0 rmarkdown_2.28 XVector_0.44.0
[112] htmltools_0.5.8.1 pkgconfig_2.0.3 highr_0.11
[115] fastmap_1.2.0 rlang_1.1.4 htmlwidgets_1.6.4
[118] UCSC.utils_1.0.0 shiny_1.9.1 farver_2.1.2
[121] jquerylib_0.1.4 zoo_1.8-12 jsonlite_1.8.9
[124] BiocParallel_1.38.0 GOSemSim_2.30.2 R.oo_1.26.0
[127] RCurl_1.98-1.16 magrittr_2.0.3 Formula_1.2-5
[130] GenomeInfoDbData_1.2.12 ggplotify_0.1.2 dotCall64_1.2
[133] patchwork_1.3.0 munsell_0.5.1 Rcpp_1.0.13
[136] ggnewscale_0.5.0 ape_5.8 viridis_0.6.5
[139] reticulate_1.39.0 stringi_1.8.4 ggraph_2.2.1
[142] zlibbioc_1.50.0 MASS_7.3-61 plyr_1.8.9
[145] parallel_4.4.1 listenv_0.9.1 ggrepel_0.9.6
[148] deldir_2.0-4 Biostrings_2.72.1 graphlayouts_1.2.0
[151] splines_4.4.1 tensor_1.5 igraph_2.1.1
[154] spatstat.geom_3.3-3 ggsignif_0.6.4 RcppHNSW_0.6.0
[157] reshape2_1.4.4 XML_3.99-0.17 evaluate_1.0.1
[160] SeuratObject_5.0.2 tweenr_2.0.3 httpuv_1.6.15
[163] RANN_2.6.2 tidyr_1.3.1 purrr_1.0.2
[166] polyclip_1.10-7 future_1.34.0 scattermore_1.2
[169] ggforce_0.4.2 broom_1.0.7 xtable_1.8-4
[172] RSpectra_0.16-2 tidytree_0.4.6 rstatix_0.7.2
[175] later_1.3.2 viridisLite_0.4.2 tibble_3.2.1
[178] aplot_0.2.3 memoise_2.0.1 cluster_2.1.6
[181] workflowr_1.7.1 globals_0.16.3