Last updated: 2024-10-22

Checks: 7 0

Knit directory: DEanalysis/

This reproducible R Markdown analysis was created with workflowr (version 1.7.1). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.


Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

The command set.seed(20230508) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version 2c1d57c. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:


Ignored files:
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    data/.Rhistory

Untracked files:
    Untracked:  .DS_Store
    Untracked:  .gitignore
    Untracked:  analysis/analysis_humanspine.Rmd
    Untracked:  analysis/simulation_donor_effect.Rmd
    Untracked:  data/.DS_Store
    Untracked:  data/10X_inputdata.RData
    Untracked:  data/10X_inputdata_cpm.RData
    Untracked:  data/10X_inputdata_integrated.RData
    Untracked:  data/10X_inputdata_lognorm.RData
    Untracked:  data/10Xdata_annotate.rds
    Untracked:  data/Bcells.Rmd
    Untracked:  data/Bcellsce.rds
    Untracked:  data/Kang_DEresult.RData
    Untracked:  data/Kang_data.RData
    Untracked:  data/fallopian_DEresult.RData
    Untracked:  data/fallopian_tubes.RData
    Untracked:  data/fallopian_tubes_all.RData
    Untracked:  data/human/
    Untracked:  data/human_spine.RData
    Untracked:  data/human_spine_DEresult.RData
    Untracked:  data/ls_offset_Result.RData
    Untracked:  data/mouse/
    Untracked:  data/permutation.RData
    Untracked:  data/permutation13.RData
    Untracked:  data/permutation2.RData
    Untracked:  data/splatter_simulation.RData
    Untracked:  data/vstcounts.Rdata
    Untracked:  figure/

Unstaged changes:
    Modified:   analysis/analysis on Kang.Rmd
    Modified:   analysis/analysis on fallopian tubes.Rmd
    Modified:   analysis/group12_19.Rmd
    Modified:   analysis/group2_19.Rmd
    Modified:   analysis/group8_17-2_19.Rmd
    Modified:   analysis/group8_17.Rmd
    Modified:   analysis/preprocess_fallopian_tubes.Rmd
    Modified:   code/DE_methods.R
    Modified:   code/functions_in_rmd.R

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.


These are the previous versions of the repository in which changes were made to the R Markdown (analysis/group12_13.Rmd) and HTML (docs/group12_13.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File Version Author Date Message
Rmd 2c1d57c C-HW 2024-10-22 same criteria, FCcutoff 1.5
html 7bb637a C-HW 2024-10-21 Build site.
html c9a07f9 C-HW 2024-10-21 Build site.
Rmd f659575 C-HW 2024-10-21 same DEG criteria for all methods
html 28b9b7d C-HW 2024-10-14 Build site.
Rmd c4961dc C-HW 2024-10-14 update Seurat result
html 5e86686 C-HW 2023-12-15 Build site.
Rmd 036d5fc C-HW 2023-12-15 wflow_publish(c("analysis/group12_13.Rmd", "analysis/group12_19.Rmd",
html d7a7b73 C-HW 2023-12-10 Build site.
Rmd ae4b56c C-HW 2023-12-10 adjust ylim of p-value histogram
html ac027b0 C-HW 2023-12-09 Build site.
Rmd 582be29 C-HW 2023-12-09 update new DE results
html 2a17159 C-HW 2023-12-05 Build site.
Rmd e7f3de4 C-HW 2023-12-05 fix Wilcox log2FC sign
html e32516f C-HW 2023-12-05 Build site.
html bc13544 C-HW 2023-12-04 Build site.
Rmd 39196a3 C-HW 2023-12-04 fix log2FC sign
html 42900f0 C-HW 2023-12-01 Build site.
Rmd c774a2d C-HW 2023-12-01 modify method title
Rmd 031d955 C-HW 2023-12-01 create t score comparison
html 031d955 C-HW 2023-12-01 create t score comparison
Rmd 3803697 C-HW 2023-12-01 upload rmd
html 59b08c2 C-HW 2023-11-29 update index, FD permuation, plots axes
html e8b0519 C-HW 2023-11-29 update all pairs
html 6faf9c0 C-HW 2023-11-29 group1213
html d7d838c C-HW 2023-08-11 update graph
html f314434 C-HW 2023-07-26 add muscat methods
html 7ee9782 C-HW 2023-07-13 add 8_17
html ccb68e2 C-HW 2023-06-29 log2fc consistence
html 3121ffb C-HW 2023-06-22 color palette heatmap
html d8c99b1 C-HW 2023-06-16 variation description
html 366cd53 C-HW 2023-06-06 add group8_17&2_19
html 95be122 C-HW 2023-05-25 update 2_19
html 2107af3 C-HW 2023-05-24 add methods_details
html 13d726d C-HW 2023-05-18 add DE results on different groups

Data summary

Version Author Date
28b9b7d C-HW 2024-10-14
6faf9c0 C-HW 2023-11-29
d7d838c C-HW 2023-08-11
7ee9782 C-HW 2023-07-13
3121ffb C-HW 2023-06-22

Difference in library size


    Asymptotic two-sample Kolmogorov-Smirnov test

data:  subset(count_cell_df, Group == group1, totalcount)$totalcount and subset(count_cell_df, Group == group2, totalcount)$totalcount
D = 0.72806, p-value < 2.2e-16
alternative hypothesis: two-sided

    Welch Two Sample t-test

data:  subset(count_cell_df, Group == group1, totalcount)$totalcount and subset(count_cell_df, Group == group2, totalcount)$totalcount
t = 26.526, df = 513.08, p-value < 2.2e-16
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 665.3597 771.8005
sample estimates:
mean of x mean of y 
 2826.130  2107.549 

Mean difference in raw data/normalized data

Version Author Date
28b9b7d C-HW 2024-10-14
42900f0 C-HW 2023-12-01
d7d838c C-HW 2023-08-11
f314434 C-HW 2023-07-26
7ee9782 C-HW 2023-07-13
95be122 C-HW 2023-05-25
2107af3 C-HW 2023-05-24
13d726d C-HW 2023-05-18

Number of DEGs from each method

Version Author Date
28b9b7d C-HW 2024-10-14
ac027b0 C-HW 2023-12-09
42900f0 C-HW 2023-12-01
6faf9c0 C-HW 2023-11-29
f314434 C-HW 2023-07-26
7ee9782 C-HW 2023-07-13
2107af3 C-HW 2023-05-24
13d726d C-HW 2023-05-18

Volcano plot

Version Author Date
c9a07f9 C-HW 2024-10-21
28b9b7d C-HW 2024-10-14
ac027b0 C-HW 2023-12-09
bc13544 C-HW 2023-12-04
42900f0 C-HW 2023-12-01
6faf9c0 C-HW 2023-11-29
3121ffb C-HW 2023-06-22
95be122 C-HW 2023-05-25

Histogram of p-value/adj.p-value

Version Author Date
c9a07f9 C-HW 2024-10-21
28b9b7d C-HW 2024-10-14
42900f0 C-HW 2023-12-01
d7d838c C-HW 2023-08-11
d8c99b1 C-HW 2023-06-16
366cd53 C-HW 2023-06-06
95be122 C-HW 2023-05-25
2107af3 C-HW 2023-05-24
13d726d C-HW 2023-05-18

P-Value comparison across different methods

Version Author Date
28b9b7d C-HW 2024-10-14
d7a7b73 C-HW 2023-12-10
ac027b0 C-HW 2023-12-09
42900f0 C-HW 2023-12-01
6faf9c0 C-HW 2023-11-29
f314434 C-HW 2023-07-26
7ee9782 C-HW 2023-07-13
13d726d C-HW 2023-05-18

Log2 fold change comparison across different methods

Version Author Date
28b9b7d C-HW 2024-10-14
ac027b0 C-HW 2023-12-09
91b404e C-HW 2023-11-29
3121ffb C-HW 2023-06-22
366cd53 C-HW 2023-06-06
95be122 C-HW 2023-05-25

Violin plot of log2mean of DEGs

Version Author Date
28b9b7d C-HW 2024-10-14
ac027b0 C-HW 2023-12-09
42900f0 C-HW 2023-12-01
6faf9c0 C-HW 2023-11-29
d7d838c C-HW 2023-08-11
f314434 C-HW 2023-07-26
7ee9782 C-HW 2023-07-13
3121ffb C-HW 2023-06-22

Violin plot of gene expression frequency of DEGs

Version Author Date
c9a07f9 C-HW 2024-10-21
28b9b7d C-HW 2024-10-14
5e86686 C-HW 2023-12-15
ac027b0 C-HW 2023-12-09
42900f0 C-HW 2023-12-01
d7d838c C-HW 2023-08-11
3121ffb C-HW 2023-06-22

Upset plot

Version Author Date
28b9b7d C-HW 2024-10-14
5e86686 C-HW 2023-12-15
ac027b0 C-HW 2023-12-09
42900f0 C-HW 2023-12-01
6faf9c0 C-HW 2023-11-29
7ee9782 C-HW 2023-07-13
ccb68e2 C-HW 2023-06-29
3121ffb C-HW 2023-06-22

Heatmap of top DEGs

Poisson-glmm DEGs

UMI counts

Version Author Date
c9a07f9 C-HW 2024-10-21
28b9b7d C-HW 2024-10-14
5e86686 C-HW 2023-12-15
ac027b0 C-HW 2023-12-09
6faf9c0 C-HW 2023-11-29
d7d838c C-HW 2023-08-11

VST data

Version Author Date
c9a07f9 C-HW 2024-10-21
28b9b7d C-HW 2024-10-14
5e86686 C-HW 2023-12-15
ac027b0 C-HW 2023-12-09
91b404e C-HW 2023-11-29
7ee9782 C-HW 2023-07-13
3121ffb C-HW 2023-06-22

CPM data

Version Author Date
c9a07f9 C-HW 2024-10-21
28b9b7d C-HW 2024-10-14
5e86686 C-HW 2023-12-15
ac027b0 C-HW 2023-12-09
6faf9c0 C-HW 2023-11-29
d7d838c C-HW 2023-08-11
ccb68e2 C-HW 2023-06-29
3121ffb C-HW 2023-06-22

Integrated data

Version Author Date
42900f0 C-HW 2023-12-01
d7d838c C-HW 2023-08-11
7ee9782 C-HW 2023-07-13

MA plot

Version Author Date
c9a07f9 C-HW 2024-10-21
28b9b7d C-HW 2024-10-14
5e86686 C-HW 2023-12-15
ac027b0 C-HW 2023-12-09
e8b0519 C-HW 2023-11-29
6faf9c0 C-HW 2023-11-29
f314434 C-HW 2023-07-26
7ee9782 C-HW 2023-07-13
3121ffb C-HW 2023-06-22

Enrichment analysis

GO object

Version Author Date
c9a07f9 C-HW 2024-10-21
28b9b7d C-HW 2024-10-14
5e86686 C-HW 2023-12-15
ac027b0 C-HW 2023-12-09
42900f0 C-HW 2023-12-01
d7d838c C-HW 2023-08-11
7ee9782 C-HW 2023-07-13

Version Author Date
c9a07f9 C-HW 2024-10-21
28b9b7d C-HW 2024-10-14
5e86686 C-HW 2023-12-15
ac027b0 C-HW 2023-12-09
bc13544 C-HW 2023-12-04
42900f0 C-HW 2023-12-01
031d955 C-HW 2023-12-01
6faf9c0 C-HW 2023-11-29
f314434 C-HW 2023-07-26
7ee9782 C-HW 2023-07-13

enrichKEGG object

Version Author Date
c9a07f9 C-HW 2024-10-21
28b9b7d C-HW 2024-10-14
5e86686 C-HW 2023-12-15
ac027b0 C-HW 2023-12-09
6faf9c0 C-HW 2023-11-29
d7d838c C-HW 2023-08-11

Version Author Date
28b9b7d C-HW 2024-10-14
5e86686 C-HW 2023-12-15
ac027b0 C-HW 2023-12-09
2a17159 C-HW 2023-12-05
e32516f C-HW 2023-12-05
bc13544 C-HW 2023-12-04
42900f0 C-HW 2023-12-01
031d955 C-HW 2023-12-01
59b08c2 C-HW 2023-11-29
6faf9c0 C-HW 2023-11-29
d7d838c C-HW 2023-08-11
7ee9782 C-HW 2023-07-13

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                SeuratObject_5.0.2         
 [3] sp_2.1-4                    pathview_1.44.0            
 [5] org.Hs.eg.db_3.19.1         AnnotationDbi_1.66.0       
 [7] enrichplot_1.24.4           clusterProfiler_4.12.6     
 [9] reshape_0.8.9               gridExtra_2.3              
[11] pheatmap_1.0.12             SingleCellExperiment_1.26.0
[13] SummarizedExperiment_1.34.0 Biobase_2.64.0             
[15] GenomicRanges_1.56.2        GenomeInfoDb_1.40.1        
[17] IRanges_2.38.1              S4Vectors_0.42.1           
[19] BiocGenerics_0.50.0         MatrixGenerics_1.16.0      
[21] matrixStats_1.4.1           ggpubr_0.6.0               
[23] dplyr_1.1.4                 ggplot2_3.5.1              

loaded via a namespace (and not attached):
  [1] splines_4.4.1           later_1.3.2             bitops_1.0-9           
  [4] ggplotify_0.1.2         tibble_3.2.1            R.oo_1.26.0            
  [7] polyclip_1.10-7         graph_1.82.0            XML_3.99-0.17          
 [10] lifecycle_1.0.4         httr2_1.0.5             rstatix_0.7.2          
 [13] rprojroot_2.0.4         globals_0.16.3          lattice_0.22-6         
 [16] MASS_7.3-61             backports_1.5.0         magrittr_2.0.3         
 [19] sass_0.4.9              rmarkdown_2.28          jquerylib_0.1.4        
 [22] yaml_2.3.10             httpuv_1.6.15           spam_2.11-0            
 [25] cowplot_1.1.3           DBI_1.2.3               RColorBrewer_1.1-3     
 [28] abind_1.4-8             zlibbioc_1.50.0         purrr_1.0.2            
 [31] R.utils_2.12.3          ggraph_2.2.1            RCurl_1.98-1.16        
 [34] yulab.utils_0.1.7       tweenr_2.0.3            rappdirs_0.3.3         
 [37] git2r_0.35.0            GenomeInfoDbData_1.2.12 ggrepel_0.9.6          
 [40] listenv_0.9.1           tidytree_0.4.6          parallelly_1.38.0      
 [43] codetools_0.2-20        DelayedArray_0.30.1     DOSE_3.30.5            
 [46] ggforce_0.4.2           tidyselect_1.2.1        aplot_0.2.3            
 [49] UCSC.utils_1.0.0        farver_2.1.2            viridis_0.6.5          
 [52] jsonlite_1.8.9          progressr_0.14.0        tidygraph_1.3.1        
 [55] Formula_1.2-5           ggnewscale_0.5.0        tools_4.4.1            
 [58] treeio_1.28.0           Rcpp_1.0.13             glue_1.8.0             
 [61] SparseArray_1.4.8       xfun_0.48               qvalue_2.36.0          
 [64] withr_3.0.1             fastmap_1.2.0           fansi_1.0.6            
 [67] digest_0.6.37           R6_2.5.1                gridGraphics_0.5-1     
 [70] colorspace_2.1-1        GO.db_3.19.1            RSQLite_2.3.7          
 [73] R.methodsS3_1.8.2       utf8_1.2.4              tidyr_1.3.1            
 [76] generics_0.1.3          data.table_1.16.2       graphlayouts_1.2.0     
 [79] httr_1.4.7              S4Arrays_1.4.1          scatterpie_0.2.4       
 [82] whisker_0.4.1           pkgconfig_2.0.3         gtable_0.3.5           
 [85] blob_1.2.4              workflowr_1.7.1         XVector_0.44.0         
 [88] shadowtext_0.1.4        htmltools_0.5.8.1       carData_3.0-5          
 [91] dotCall64_1.2           fgsea_1.30.0            scales_1.3.0           
 [94] png_0.1-8               ggfun_0.1.6             knitr_1.48             
 [97] rstudioapi_0.17.0       reshape2_1.4.4          nlme_3.1-166           
[100] cachem_1.1.0            stringr_1.5.1           parallel_4.4.1         
[103] pillar_1.9.0            grid_4.4.1              vctrs_0.6.5            
[106] promises_1.3.0          car_3.1-3               Rgraphviz_2.48.0       
[109] evaluate_1.0.1          KEGGgraph_1.64.0        cli_3.6.3              
[112] compiler_4.4.1          rlang_1.1.4             crayon_1.5.3           
[115] future.apply_1.11.2     ggsignif_0.6.4          labeling_0.4.3         
[118] plyr_1.8.9              fs_1.6.4                stringi_1.8.4          
[121] viridisLite_0.4.2       BiocParallel_1.38.0     munsell_0.5.1          
[124] Biostrings_2.72.1       lazyeval_0.2.2          GOSemSim_2.30.2        
[127] Matrix_1.7-1            patchwork_1.3.0         bit64_4.5.2            
[130] future_1.34.0           KEGGREST_1.44.1         highr_0.11             
[133] igraph_2.1.1            broom_1.0.7             memoise_2.0.1          
[136] bslib_0.8.0             ggtree_3.12.0           fastmatch_1.1-4        
[139] bit_4.5.0               ape_5.8                 gson_0.1.0