Last updated: 2024-06-12

Checks: 6 1

Knit directory: BH3profiling/analysis/

This reproducible R Markdown analysis was created with workflowr (version 1.7.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.


The R Markdown is untracked by Git. To know which version of the R Markdown file created these results, you’ll want to first commit it to the Git repo. If you’re still working on the analysis, you can ignore this warning. When you’re finished, you can run wflow_publish to commit the R Markdown file and build the HTML.

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(20200826) 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 90ada8f. 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:    .DS_Store
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    analysis/.DS_Store
    Ignored:    analysis/.Rhistory
    Ignored:    analysis/manuscript_drugResponses_cache/
    Ignored:    analysis/manuscript_overview_cache/
    Ignored:    data/.DS_Store
    Ignored:    data/.Rapp.history
    Ignored:    output/.DS_Store

Untracked files:
    Untracked:  analysis/Annexin_rawInput.Rmd
    Untracked:  analysis/BH3_PCA.csv
    Untracked:  analysis/BH3baseline_analysis_fromBase.Rmd
    Untracked:  analysis/BH3baseline_analysis_fromDBP.Rmd
    Untracked:  analysis/BH3baseline_rawInput.Rmd
    Untracked:  analysis/BH3dynamic_rawInput.Rmd
    Untracked:  analysis/FigS5_RNA_num_associations.pdf
    Untracked:  analysis/analysisVenetoclax.Rmd
    Untracked:  analysis/based_pep_var.pdf
    Untracked:  analysis/clinialTrial_analysis.Rmd
    Untracked:  analysis/compareBaseline.Rmd
    Untracked:  analysis/compareBaseline.pdf
    Untracked:  analysis/deprecated/
    Untracked:  analysis/drugResponse_baseBH3_analysis.Rmd
    Untracked:  analysis/drugResponse_baseBH3_analysis_AUC copy.Rmd
    Untracked:  analysis/drugResponse_baseBH3_analysis_AUC.Rmd
    Untracked:  analysis/dynamicBH3_analysis.Rmd
    Untracked:  analysis/dynamicBH3_analysis_AUC.Rmd
    Untracked:  analysis/landscape_baseBH3_analysis.Rmd
    Untracked:  analysis/landscape_baseBH3_analysis_AUC.Rmd
    Untracked:  analysis/landscape_baseBH3_fromBase_analysis_AUC.Rmd
    Untracked:  analysis/manuscript_clinicalAnalysis.Rmd
    Untracked:  analysis/manuscript_drugResponses.Rmd
    Untracked:  analysis/manuscript_dynamicBH3.Rmd
    Untracked:  analysis/manuscript_dynamicBH3_old.Rmd
    Untracked:  analysis/manuscript_energyMetabolism.Rmd
    Untracked:  analysis/manuscript_overview.Rmd
    Untracked:  analysis/manuscript_overview_fromBaseBH3.Rmd
    Untracked:  analysis/manuscript_overview_singleConc.Rmd
    Untracked:  analysis/outcome_baseBH3_analysis.Rmd
    Untracked:  analysis/outcome_baseBH3_analysis_AUC.Rmd
    Untracked:  analysis/patBack.csv
    Untracked:  analysis/platePlot.pdf
    Untracked:  analysis/platePlot_dynamic.pdf
    Untracked:  analysis/predictOutcomes.Rmd
    Untracked:  analysis/pretreatment_effect_estiamtion.csv
    Untracked:  analysis/revisionAnalysis_ProtRNA_Genomic_correlations.Rmd
    Untracked:  analysis/tableS1_sampleSummary.csv
    Untracked:  analysis/treatTab.csv
    Untracked:  analysis/venePair_auc.pdf
    Untracked:  analysis/venePair_auc_norm.pdf
    Untracked:  analysis/venePair_auc_raw.pdf
    Untracked:  analysis/venePair_con.pdf
    Untracked:  analysis/venePair_conc_unorm.pdf
    Untracked:  code/utils.R
    Untracked:  data/13092020 Patient Outcome Analysis - IBR plus FCR - for Junyan.xlsx
    Untracked:  data/Compiled Baseline BH3 profile for Primary CLL_for Junyan.xlsx
    Untracked:  data/Data for Thorsten .xlsx
    Untracked:  data/Raw data Baseline for Junyan.xlsx
    Untracked:  data/Raw data DBP for Junyan.xlsx
    Untracked:  data/T. Zenz data for Junyan.xlsx
    Untracked:  data/Zenz Project overview cell counts etc.xlsx
    Untracked:  data/commonFiles/
    Untracked:  data/venetoclax_coculture.rds
    Untracked:  data/~$Compiled Baseline BH3 profile for Primary CLL_for Junyan.xlsx
    Untracked:  figures/
    Untracked:  manuscript/
    Untracked:  output/allData.RData
    Untracked:  output/baseBH3.RData
    Untracked:  output/dataAnnexin.RData
    Untracked:  output/dynamicBH3.RData
    Untracked:  prepareData.R

Unstaged changes:
    Modified:   _workflowr.yml
    Modified:   analysis/_site.yml
    Deleted:    analysis/about.Rmd
    Modified:   analysis/index.Rmd
    Deleted:    analysis/license.Rmd

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.


There are no past versions. Publish this analysis with wflow_publish() to start tracking its development.


Load and pre-process datasets

Define interested genes

Genes will be considered in the analysis

    BCL-2     MCL-1    BCL-xL     BFL-1       BAX       BAK       BIM      PUMA 
   "BCL2"    "MCL1"  "BCL2L1"  "BCL2A1"     "BAX"    "BAK1" "BCL2L11"    "BBC3" 
     NOXA     COX5A     COX5B      SOD1      SOD2 
 "PMAIP1"   "COX5A"   "COX5B"    "SOD1"    "SOD2" 

The first row shows the commonly used protein names and the second row shows the corresponding official gene symbols

BH3 profiling data

RNAseq data

   BCL2    MCL1  BCL2L1  BCL2A1     BAX    BAK1 BCL2L11    BBC3  PMAIP1   COX5A 
   TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE    TRUE 
  COX5B    SOD1    SOD2 
   TRUE    TRUE    TRUE 
[1] 13 71

Proteomics

   BCL2    MCL1  BCL2L1  BCL2A1     BAX    BAK1 BCL2L11    BBC3  PMAIP1   COX5A 
   TRUE   FALSE   FALSE   FALSE    TRUE   FALSE    TRUE   FALSE   FALSE    TRUE 
  COX5B    SOD1    SOD2 
   TRUE   FALSE    TRUE 
[1]  6 91

Genomics

Prepare patient genomic background

[1] "IGHV.status" "del11q"      "del13q"      "del17p"      "trisomy12"  
[6] "NOTCH1"      "SF3B1"       "TP53"       

Correlation between the baseline mRNA expression of the interested genes and mutations in CLL

Result table

Plot associations with 10% FDR

Correlation between the protein expressions of the interested genes and mutations in CLL

Result table

Only the associations between BAX and trisomy12 passed 10% FDR

Plot associations with 10% FDR

Differential expression of the interested genes before and after ex-vivo Ibrutinib treatment

Load dataset

Preprocessing

Subset for DMSO and Ibr

Subset for interested genes

[1]  13 187

Differential expression between Ibr treatment and DMSO

Plot associations with 10% FDR

Wether the expression of interested genes before and after ex-vivo ibrutinib treatment associated with ibrutinib responses?

Prepare drug response profile

Prepare gene expression

Association test

Table of significant associations (10%)

In the treatment column:
- Ibrutinib_48h means the gene expression after Ibrutinib treatment for 48 hours
- DMSO_48h means the gene expression after 48h incubation with just DMSO
- FoldChange means the log fold change between Ibrutinib and DMSO after 48 hourse

Note that in this experiment, we don’t have the real baseline (0 hour)

Plot the significant associations

Wether the expression of interested genes before and after ex-vivo ibrutinib treatment associated with BH3 profiling data?

Prepare drug response profile

Association test

Table of significant associations (10%)

Plot the significant associations

It’s interesting to see that the gene expression after 48h DMSO incubation show stronger association to BH3 profile than the real baseline gene expression (0h) we used in the manuscript
This could be because the BH3 profiling data we are using is also the BH3 profile after 48h DMSO incubation
You can see from the below longitudinal gene expression profile, some of those genes show strong changes during culturing in DMSO

Look at the longitudinal gene expression data

Visualize the time-course expression of the interested genes in DMSO and Ibrutinib treated samples

Correlate the protein expression with in-vivo Ibr treated patients (a smaller cohort from Heidelberg)

Load dataset

Subset for interested genes

[1]  6 10

Result table

Plot associations with 10% FDR

Contrary to the gene expression after ex-vivo Ibr treatment, BCL2 protein level increased after in-vivo ibrutinib treatment

Correlate the protein expression with in-vivo Ibr treated patients (look at a larger cohort from Zurich)

Load dataset

Selected appropriate samples

[1]  9 30

Differential expression

Result table

Plot associations with 10% FDR

The trend is similar to the smaller cohort from Heidelberg

Correlate the gene expression with in-vivo Ibr treated patients (those are the sample samples as the ones above)

Load dataset

Selected appropriate samples

[1] 12 70

Differential expression

Plot associations with 10% FDR

It seems the trend on mRNA level is not consistent with the trend on protein level..

Analysis of Stephen’s Western Blot data

T-test

Boxplot


R version 4.2.0 (2022-04-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur/Monterey 10.16

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats4    stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] latex2exp_0.9.4             forcats_0.5.1              
 [3] stringr_1.4.1               dplyr_1.1.4.9000           
 [5] purrr_0.3.4                 readr_2.1.2                
 [7] tidyr_1.2.0                 tibble_3.2.1               
 [9] ggplot2_3.4.1               tidyverse_1.3.2            
[11] DESeq2_1.36.0               SummarizedExperiment_1.26.1
[13] Biobase_2.56.0              MatrixGenerics_1.8.1       
[15] matrixStats_0.62.0          GenomicRanges_1.48.0       
[17] GenomeInfoDb_1.32.2         IRanges_2.30.0             
[19] S4Vectors_0.34.0            BiocGenerics_0.42.0        
[21] jyluMisc_0.1.5             

loaded via a namespace (and not attached):
  [1] utf8_1.2.4             shinydashboard_0.7.2   tidyselect_1.2.1      
  [4] RSQLite_2.2.15         AnnotationDbi_1.58.0   htmlwidgets_1.5.4     
  [7] grid_4.2.0             BiocParallel_1.30.3    maxstat_0.7-25        
 [10] munsell_0.5.0          codetools_0.2-18       DT_0.23               
 [13] withr_3.0.0            colorspace_2.0-3       highr_0.9             
 [16] knitr_1.39             proDA_1.10.0           rstudioapi_0.13       
 [19] ggsignif_0.6.3         labeling_0.4.2         git2r_0.30.1          
 [22] slam_0.1-50            GenomeInfoDbData_1.2.8 KMsurv_0.1-5          
 [25] farver_2.1.1           bit64_4.0.5            rprojroot_2.0.3       
 [28] vctrs_0.6.5            generics_0.1.3         TH.data_1.1-1         
 [31] xfun_0.31              sets_1.0-21            R6_2.5.1              
 [34] ggbeeswarm_0.6.0       locfit_1.5-9.6         bitops_1.0-7          
 [37] cachem_1.0.6           fgsea_1.22.0           DelayedArray_0.22.0   
 [40] assertthat_0.2.1       promises_1.2.0.1       scales_1.2.0          
 [43] multcomp_1.4-19        googlesheets4_1.0.0    beeswarm_0.4.0        
 [46] gtable_0.3.0           extraDistr_1.9.1       sandwich_3.0-2        
 [49] workflowr_1.7.0        rlang_1.1.3            genefilter_1.78.0     
 [52] splines_4.2.0          rstatix_0.7.0          gargle_1.2.0          
 [55] broom_1.0.0            yaml_2.3.5             abind_1.4-5           
 [58] modelr_0.1.8           crosstalk_1.2.0        backports_1.4.1       
 [61] httpuv_1.6.6           tools_4.2.0            relations_0.6-12      
 [64] ellipsis_0.3.2         gplots_3.1.3           jquerylib_0.1.4       
 [67] RColorBrewer_1.1-3     Rcpp_1.0.9             visNetwork_2.1.0      
 [70] zlibbioc_1.42.0        RCurl_1.98-1.7         ggpubr_0.4.0          
 [73] cowplot_1.1.1          zoo_1.8-10             haven_2.5.0           
 [76] cluster_2.1.3          exactRankTests_0.8-35  fs_1.5.2              
 [79] magrittr_2.0.3         data.table_1.14.8      reprex_2.0.1          
 [82] survminer_0.4.9        googledrive_2.0.0      mvtnorm_1.1-3         
 [85] hms_1.1.1              shinyjs_2.1.0          mime_0.12             
 [88] evaluate_0.15          xtable_1.8-4           XML_3.99-0.10         
 [91] readxl_1.4.0           gridExtra_2.3          compiler_4.2.0        
 [94] KernSmooth_2.23-20     crayon_1.5.2           htmltools_0.5.4       
 [97] mgcv_1.8-40            later_1.3.0            tzdb_0.3.0            
[100] geneplotter_1.74.0     lubridate_1.8.0        DBI_1.1.3             
[103] dbplyr_2.2.1           MASS_7.3-58            Matrix_1.5-4          
[106] car_3.1-0              cli_3.6.2              marray_1.74.0         
[109] parallel_4.2.0         igraph_1.3.4           pkgconfig_2.0.3       
[112] km.ci_0.5-6            piano_2.12.0           xml2_1.3.3            
[115] annotate_1.74.0        vipor_0.4.5            bslib_0.4.1           
[118] XVector_0.36.0         drc_3.0-1              rvest_1.0.2           
[121] digest_0.6.30          Biostrings_2.64.0      rmarkdown_2.14        
[124] cellranger_1.1.0       fastmatch_1.1-3        survMisc_0.5.6        
[127] shiny_1.7.4            gtools_3.9.3           nlme_3.1-158          
[130] lifecycle_1.0.4        jsonlite_1.8.3         carData_3.0-5         
[133] limma_3.52.2           fansi_1.0.6            pillar_1.9.0          
[136] lattice_0.20-45        KEGGREST_1.36.3        fastmap_1.1.0         
[139] httr_1.4.3             plotrix_3.8-2          survival_3.4-0        
[142] glue_1.7.0             png_0.1-7              bit_4.0.4             
[145] stringi_1.7.8          sass_0.4.2             blob_1.2.3            
[148] caTools_1.18.2         memoise_2.0.1