Last updated: 2023-04-17

Checks: 7 0

Knit directory: Cardiotoxicity/

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.


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(20230109) 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 8a5a1e1. 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:    .RData
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    data/ACresponse_cluster24h.csv
    Ignored:    data/Clamp_Summary.csv
    Ignored:    data/Cormotif_24_k1-5_raw.RDS
    Ignored:    data/DAgostres24.RDS
    Ignored:    data/DAtable1.csv
    Ignored:    data/DDE_reQTL.txt
    Ignored:    data/DDEresp_list.csv
    Ignored:    data/DEG_cormotif.RDS
    Ignored:    data/DF_Plate_Peak.csv
    Ignored:    data/Da24counts.txt
    Ignored:    data/Dx24counts.txt
    Ignored:    data/Dx_reQTL_specific.txt
    Ignored:    data/Ep24counts.txt
    Ignored:    data/GOplots.R
    Ignored:    data/K_cluster
    Ignored:    data/K_cluster_kisthree.csv
    Ignored:    data/K_cluster_kistwo.csv
    Ignored:    data/Mt24counts.txt
    Ignored:    data/RINsamplelist.txt
    Ignored:    data/Seonane2019supp1.txt
    Ignored:    data/TOP2Bi-24hoursGO_analysis.csv
    Ignored:    data/TR24counts.txt
    Ignored:    data/Top2biresp_cluster24h.csv
    Ignored:    data/Viabilitylistfull.csv
    Ignored:    data/allexpressedgenes.txt
    Ignored:    data/allgenes.txt
    Ignored:    data/allmatrix.RDS
    Ignored:    data/avgLD50.RDS
    Ignored:    data/backGL.txt
    Ignored:    data/cormotif_3hk1-8.RDS
    Ignored:    data/cormotif_ER_cluster.txt
    Ignored:    data/cormotif_ER_respint.txt
    Ignored:    data/cormotif_ER_respset.txt
    Ignored:    data/cormotif_LR_cluster.txt
    Ignored:    data/cormotif_LR_respint.txt
    Ignored:    data/cormotif_LR_respset.txt
    Ignored:    data/cormotif_NRset.txt
    Ignored:    data/cormotif_TI_cluster.txt
    Ignored:    data/cormotif_TI_respint.txt
    Ignored:    data/cormotif_TI_respset.txt
    Ignored:    data/cormotif_initalK5.RDS
    Ignored:    data/cormotif_initialK5.RDS
    Ignored:    data/cormotif_initialall.RDS
    Ignored:    data/counts24hours.RDS
    Ignored:    data/cpmnorm_counts.csv
    Ignored:    data/dat_cpm.RDS
    Ignored:    data/data_outline.txt
    Ignored:    data/efit2.RDS
    Ignored:    data/efit2results.RDS
    Ignored:    data/ensembl_backup.RDS
    Ignored:    data/ensgtotal.txt
    Ignored:    data/filenameonly.txt
    Ignored:    data/filtered_cpm_counts.csv
    Ignored:    data/filtered_raw_counts.csv
    Ignored:    data/filtermatrix_x.RDS
    Ignored:    data/folder_05top/
    Ignored:    data/gene_prob_tran3h.RDS
    Ignored:    data/gene_probabilityk5.RDS
    Ignored:    data/gostresTop2bi_ER.RDS
    Ignored:    data/gostresTop2bi_LR
    Ignored:    data/gostresTop2bi_LR.RDS
    Ignored:    data/gostresTop2bi_TI.RDS
    Ignored:    data/gostrescoNR
    Ignored:    data/heartgenes.csv
    Ignored:    data/individualDRCfile.RDS
    Ignored:    data/knowles56.GMT
    Ignored:    data/knowlesGMT.GMT
    Ignored:    data/mymatrix.RDS
    Ignored:    data/nonresponse_cluster24h.csv
    Ignored:    data/norm_LDH.csv
    Ignored:    data/norm_counts.csv
    Ignored:    data/plan2plot.png
    Ignored:    data/raw_counts.csv
    Ignored:    data/response_cluster24h.csv
    Ignored:    data/sigVDA24.txt
    Ignored:    data/sigVDA3.txt
    Ignored:    data/sigVDX24.txt
    Ignored:    data/sigVDX3.txt
    Ignored:    data/sigVEP24.txt
    Ignored:    data/sigVEP3.txt
    Ignored:    data/sigVMT24.txt
    Ignored:    data/sigVMT3.txt
    Ignored:    data/sigVTR24.txt
    Ignored:    data/sigVTR3.txt
    Ignored:    data/siglist.RDS
    Ignored:    data/table3a.omar
    Ignored:    data/tvl24hour.txt
    Ignored:    data/tvl24hourw.txt
    Ignored:    data/venn_code.R

Untracked files:
    Untracked:  .RDataTmp
    Untracked:  .RDataTmp1
    Untracked:  .RDataTmp2
    Untracked:  analysis/other_analysis.Rmd
    Untracked:  code/extra_code.R
    Untracked:  corMotifcustom.R
    Untracked:  output/output-old/
    Untracked:  output/plan48ldh.png
    Untracked:  output/sequencing_info.txt
    Untracked:  output/tableNR.csv
    Untracked:  output/tabletop2Bi_ER.csv
    Untracked:  output/tabletop2Bi_LR.csv
    Untracked:  output/tabletop2Bi_TI.csv
    Untracked:  output/toplistall.csv
    Untracked:  reneebasecode.R

Unstaged changes:
    Modified:   analysis/DEG-GO_analysis.Rmd
    Modified:   code/Cormotifgenelist.R
    Modified:   code/Corrscripts.R
    Modified:   code/eQTLcodes.R
    Deleted:    output/Cormotif.svg
    Deleted:    output/Ctrxn24-3-23.svg
    Deleted:    output/Ctxnrate3-23.png
    Deleted:    output/Decay_Slope3-23.svg
    Deleted:    output/ERmotif5_LFC.svg
    Deleted:    output/GOBP_motif345.svg
    Deleted:    output/KEGGmotif_345.svg
    Deleted:    output/LD503-21-23.png
    Deleted:    output/LDH_24-3-23.svg
    Deleted:    output/LDH_243-23.svg
    Deleted:    output/LFCbytreatment3-25.svg
    Deleted:    output/LFCmotif4_LR.svg
    Deleted:    output/LR_RespMoti4.svg
    Deleted:    output/MeanAmp243-23.svg
    Deleted:    output/NRmotif1_LFC.svg
    Deleted:    output/Rise_Slope3-23.svg
    Deleted:    output/TI_LFC.svg
    Deleted:    output/TVLcorr3-23.svg
    Deleted:    output/TropI3-23.svg
    Deleted:    output/Venn24DEG-3-24.png
    Deleted:    output/motif1NR_LFC.svg
    Deleted:    output/motif3TIlfc3-25.svg
    Deleted:    output/motif4LR3-25LFC.svg
    Deleted:    output/motif5ER-LFC-3-25.svg
    Deleted:    output/nolegendLDH.svg
    Deleted:    output/resultsigVDA24.csv
    Deleted:    output/tropI_24-3-23.svg

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/run_all_analysis.Rmd) and HTML (docs/run_all_analysis.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 8a5a1e1 reneeisnowhere 2023-04-17 update html page
html 7f62d67 reneeisnowhere 2023-04-17 Build site.
Rmd 363ddad reneeisnowhere 2023-04-17 update with GO links
html 21fd945 reneeisnowhere 2023-04-17 Build site.
Rmd e1c63d9 reneeisnowhere 2023-04-17 wflow_publish("analysis/run_all_analysis.Rmd")
html 8221ec3 reneeisnowhere 2023-04-16 Build site.
Rmd 9e88c22 reneeisnowhere 2023-04-16 updated run data
Rmd 6d925a2 reneeisnowhere 2023-04-16 updating cormotif with updated RNAseq counts
html 8d08bd2 reneeisnowhere 2023-04-11 Build site.
Rmd 0aaa63d reneeisnowhere 2023-04-11 cormotif analysis update
Rmd 575fd81 reneeisnowhere 2023-04-11 updating cormotif
html 4cd8ac4 reneeisnowhere 2023-04-11 Build site.
html 08936e7 reneeisnowhere 2023-04-10 Build site.
Rmd fa2cbeb reneeisnowhere 2023-04-10 monday end
html 85526c5 reneeisnowhere 2023-04-10 Build site.
Rmd 1444a85 reneeisnowhere 2023-04-10 update push of new data
html b266b76 reneeisnowhere 2023-04-10 Build site.
Rmd d3f8cf7 reneeisnowhere 2023-04-10 update push of new data
html f0a75e1 reneeisnowhere 2023-04-10 Build site.
Rmd 8ca4c7e reneeisnowhere 2023-04-10 first rmd commit
Rmd 2e69969 reneeisnowhere 2023-04-10 adding data
Rmd 0f1f1da reneeisnowhere 2023-04-10 final run analysis

This starts the documentation of the RNA-seq cardiotoxicity analysis for my manuscript

library(edgeR)#
library(limma)#
library(RColorBrewer)
library(mixOmics)
library(gridExtra)#
library(reshape2)#
library(data.table)
library(AnnotationHub)
library(tidyverse)
library(scales)
library(biomaRt)#
library(Homo.sapiens)
library(cowplot)#
library(ggrepel)#
library(corrplot)
library(Hmisc)
library(ggpubr)
 ###now we add genenames to the geneid###
 
geneid <- rownames(mymatrix) ### pulls the names we have in the counts file
genes <- select(Homo.sapiens, keys=geneid, columns=c("SYMBOL"),
  keytype="ENTREZID")
genes <- genes[!duplicated(genes$ENTREZID),]
mymatrix$genes <- genes
#saveRDS(mymatrix, "data/allmatrix.RDS")
##note-not filtered!

Initial RNA-seq quality checks

Initial histograms from count matrix

[1] 28395    72
[1] 14084    72

PCA by treatment and as a whole



###  Vehicle 



###  Daunorubicin 



###  Doxorubicin 



###  Epirubicin 



###  Mitoxantrone 



###  Trastuzumab 

        samplenames indv         drug time RIN group       PC1      PC2
Da.1.3h MCW_RM_R_11    1 Daunorubicin   3h 9.3     1 -18.33154 61.71013
Do.1.3h MCW_RM_R_12    1  Doxorubicin   3h 9.8     2 -12.36280 73.97678
Ep.1.3h MCW_RM_R_13    1   Epirubicin   3h 9.8     3 -11.16205 66.48794
Mi.1.3h MCW_RM_R_14    1 Mitoxantrone   3h  10     4 -10.19948 73.48343
Tr.1.3h MCW_RM_R_15    1  Trastuzumab   3h 9.6     5 -12.17619 80.01454
Ve.1.3h MCW_RM_R_16    1      Vehicle   3h 9.9     6 -14.98226 76.62199
              PC3        PC4        PC5       PC6
Da.1.3h 44.039139  -4.547031  24.642107 -35.03245
Do.1.3h 24.576395  -8.626528 -19.908580 -18.97447
Ep.1.3h 33.025628  -9.349549  18.083569 -43.06551
Mi.1.3h 19.016766 -14.639651  -9.065324 -24.29908
Tr.1.3h  2.640624 -17.019296 -34.253925 -11.77881
Ve.1.3h 12.706808  -4.173412 -39.846595 -17.16213

                            PC1      PC2      PC3      PC4      PC5      PC6
Standard deviation     63.98853 47.11608 34.21502 32.58775 28.22245 23.90977
Proportion of Variance  0.29072  0.15762  0.08312  0.07540  0.05655  0.04059
Cumulative Proportion   0.29072  0.44834  0.53146  0.60687  0.66342  0.70401
                            PC7
Standard deviation     21.56133
Proportion of Variance  0.03301
Cumulative Proportion   0.73702

Typical genes expressed in iPSC-CMS

correlation heatmap of counts matrix

now to get the counts set for DEG!!

DEG analysis

summary

        V.DA  V.DX  V.EP  V.MT  V.TR V.DA24 V.DX24 V.EP24 V.MT24 V.TR24
Down     109     3    30    24     0   3540   3336   3105    428      0
NotSig 13552 14065 13874 14009 14084   7067   7439   7756  12969  14084
Up       423    16   180    51     0   3477   3309   3223    687      0

cormotif analysis More In-depth

written summary so far: pending T values sorting. Response sets look similar to previous results. This data is based on the filtered count matrix (using rowmeans>0 of cpm(log=true)). Classification of patterns appear to be:

motif 1- No Response set: 7362 (gene list made by filtering each column by posterior probability of <0.55)

motif 2- Time-independent Top2Bi response cluster: 432

motif 3- Early Top2Bi response cluster: 481

motif 4- All BC drug response set (only 1!) (I could not really isolate this gene from the p.post data)

motif 5- Late Top2Bi response cluster: 4850

NOTE: these are based on the most recent counts (motif numbers have changed a little)

More analysis on corMotif (aka Baysian gene anaylsis can be found on this page:) CorMotif

Volcano plots from pairwise gene analysis


R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

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

other attached packages:
 [1] ggpubr_0.6.0                           
 [2] Hmisc_4.8-0                            
 [3] Formula_1.2-5                          
 [4] survival_3.5-3                         
 [5] corrplot_0.92                          
 [6] ggrepel_0.9.3                          
 [7] cowplot_1.1.1                          
 [8] Homo.sapiens_1.3.1                     
 [9] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[10] org.Hs.eg.db_3.15.0                    
[11] GO.db_3.15.0                           
[12] OrganismDbi_1.38.1                     
[13] GenomicFeatures_1.48.4                 
[14] GenomicRanges_1.48.0                   
[15] GenomeInfoDb_1.32.4                    
[16] AnnotationDbi_1.58.0                   
[17] IRanges_2.30.1                         
[18] S4Vectors_0.34.0                       
[19] Biobase_2.56.0                         
[20] biomaRt_2.52.0                         
[21] scales_1.2.1                           
[22] lubridate_1.9.2                        
[23] forcats_1.0.0                          
[24] stringr_1.5.0                          
[25] dplyr_1.1.0                            
[26] purrr_1.0.1                            
[27] readr_2.1.4                            
[28] tidyr_1.3.0                            
[29] tibble_3.1.8                           
[30] tidyverse_2.0.0                        
[31] AnnotationHub_3.4.0                    
[32] BiocFileCache_2.4.0                    
[33] dbplyr_2.3.1                           
[34] BiocGenerics_0.42.0                    
[35] data.table_1.14.8                      
[36] reshape2_1.4.4                         
[37] gridExtra_2.3                          
[38] mixOmics_6.20.0                        
[39] ggplot2_3.4.1                          
[40] lattice_0.20-45                        
[41] MASS_7.3-58.2                          
[42] RColorBrewer_1.1-3                     
[43] edgeR_3.38.4                           
[44] limma_3.52.4                           
[45] workflowr_1.7.0                        

loaded via a namespace (and not attached):
  [1] utf8_1.2.3                    tidyselect_1.2.0             
  [3] RSQLite_2.3.0                 htmlwidgets_1.6.1            
  [5] grid_4.2.2                    BiocParallel_1.30.4          
  [7] munsell_0.5.0                 codetools_0.2-19             
  [9] statmod_1.5.0                 interp_1.1-3                 
 [11] withr_2.5.0                   colorspace_2.1-0             
 [13] filelock_1.0.2                highr_0.10                   
 [15] knitr_1.42                    rstudioapi_0.14              
 [17] ggsignif_0.6.4                MatrixGenerics_1.8.1         
 [19] labeling_0.4.2                git2r_0.31.0                 
 [21] GenomeInfoDbData_1.2.8        pheatmap_1.0.12              
 [23] farver_2.1.1                  bit64_4.0.5                  
 [25] rprojroot_2.0.3               vctrs_0.5.2                  
 [27] generics_0.1.3                xfun_0.37                    
 [29] timechange_0.2.0              R6_2.5.1                     
 [31] locfit_1.5-9.7                bitops_1.0-7                 
 [33] cachem_1.0.7                  DelayedArray_0.22.0          
 [35] promises_1.2.0.1              BiocIO_1.6.0                 
 [37] nnet_7.3-18                   gtable_0.3.1                 
 [39] processx_3.8.0                rlang_1.0.6                  
 [41] splines_4.2.2                 rtracklayer_1.56.1           
 [43] rstatix_0.7.2                 broom_1.0.3                  
 [45] checkmate_2.1.0               BiocManager_1.30.20          
 [47] yaml_2.3.7                    abind_1.4-5                  
 [49] backports_1.4.1               httpuv_1.6.9                 
 [51] RBGL_1.72.0                   tools_4.2.2                  
 [53] ellipsis_0.3.2                jquerylib_0.1.4              
 [55] Rcpp_1.0.10                   plyr_1.8.8                   
 [57] base64enc_0.1-3               progress_1.2.2               
 [59] zlibbioc_1.42.0               RCurl_1.98-1.10              
 [61] ps_1.7.2                      prettyunits_1.1.1            
 [63] rpart_4.1.19                  deldir_1.0-6                 
 [65] SummarizedExperiment_1.26.1   cluster_2.1.4                
 [67] fs_1.6.1                      magrittr_2.0.3               
 [69] RSpectra_0.16-1               whisker_0.4.1                
 [71] matrixStats_0.63.0            hms_1.1.2                    
 [73] mime_0.12                     evaluate_0.20                
 [75] xtable_1.8-4                  XML_3.99-0.13                
 [77] jpeg_0.1-10                   compiler_4.2.2               
 [79] ellipse_0.4.3                 crayon_1.5.2                 
 [81] htmltools_0.5.4               corpcor_1.6.10               
 [83] later_1.3.0                   tzdb_0.3.0                   
 [85] DBI_1.1.3                     rappdirs_0.3.3               
 [87] Matrix_1.5-3                  car_3.1-1                    
 [89] cli_3.6.0                     parallel_4.2.2               
 [91] igraph_1.4.1                  pkgconfig_2.0.3              
 [93] getPass_0.2-2                 GenomicAlignments_1.32.1     
 [95] foreign_0.8-84                xml2_1.3.3                   
 [97] rARPACK_0.11-0                bslib_0.4.2                  
 [99] XVector_0.36.0                callr_3.7.3                  
[101] digest_0.6.31                 graph_1.74.0                 
[103] Biostrings_2.64.1             rmarkdown_2.20               
[105] htmlTable_2.4.1               restfulr_0.0.15              
[107] curl_5.0.0                    shiny_1.7.4                  
[109] Rsamtools_2.12.0              rjson_0.2.21                 
[111] lifecycle_1.0.3               jsonlite_1.8.4               
[113] carData_3.0-5                 fansi_1.0.4                  
[115] pillar_1.8.1                  KEGGREST_1.36.3              
[117] fastmap_1.1.1                 httr_1.4.5                   
[119] interactiveDisplayBase_1.34.0 glue_1.6.2                   
[121] png_0.1-8                     BiocVersion_3.15.2           
[123] bit_4.0.5                     stringi_1.7.12               
[125] sass_0.4.5                    blob_1.2.3                   
[127] latticeExtra_0.6-30           memoise_2.0.1