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Untracked files:
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Unstaged changes:
    Modified:   analysis/Identify_CNV_Regulators.Rmd
    Modified:   analysis/Identify_Kinase_Regulators.Rmd
    Modified:   analysis/KSEA.Rmd
    Modified:   analysis/index.Rmd
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    Modified:   output/cnv/dset_hnsc.RDS
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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/KSEA.Rmd) and HTML (docs/KSEA.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 85fc7b1 Zhen Zuo 2024-06-24 .
html 85fc7b1 Zhen Zuo 2024-06-24 .
html f0809ae Zhen Zuo 2024-06-17 .
Rmd 9d7bb61 Zhen Zuo 2024-06-16 .
html 9d7bb61 Zhen Zuo 2024-06-16 .
html e55118d Zhen Zuo 2024-06-16 Build site.
html 7576f76 Zhen Zuo 2024-06-16 wflow_publish("*", all = TRUE)
Rmd 3477290 Zhen Zuo 2024-06-16 update workflow
html 3477290 Zhen Zuo 2024-06-16 update workflow
Rmd 8c84adb Zhen Zuo 2024-06-16 .

library(clusterProfiler)
clusterProfiler v4.12.0  For help: https://yulab-smu.top/biomedical-knowledge-mining-book/

If you use clusterProfiler in published research, please cite:
T Wu, E Hu, S Xu, M Chen, P Guo, Z Dai, T Feng, L Zhou, W Tang, L Zhan, X Fu, S Liu, X Bo, and G Yu. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. The Innovation. 2021, 2(3):100141

Attaching package: 'clusterProfiler'
The following object is masked from 'package:stats':

    filter
library(ggplot2)
library(EnsDb.Hsapiens.v86)
Loading required package: ensembldb
Loading required package: BiocGenerics

Attaching package: 'BiocGenerics'
The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs
The following objects are masked from 'package:base':

    anyDuplicated, aperm, append, as.data.frame, basename, cbind,
    colnames, dirname, do.call, duplicated, eval, evalq, Filter, Find,
    get, grep, grepl, intersect, is.unsorted, lapply, Map, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
    Position, rank, rbind, Reduce, rownames, sapply, setdiff, table,
    tapply, union, unique, unsplit, which.max, which.min
Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: S4Vectors

Attaching package: 'S4Vectors'
The following object is masked from 'package:clusterProfiler':

    rename
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    findMatches
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    expand.grid, I, unname
Loading required package: IRanges

Attaching package: 'IRanges'
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    slice
Loading required package: GenomeInfoDb
Loading required package: GenomicFeatures
Loading required package: AnnotationDbi
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Attaching package: 'AnnotationDbi'
The following object is masked from 'package:clusterProfiler':

    select
Loading required package: AnnotationFilter

Attaching package: 'ensembldb'
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    filter
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    filter
full_name <- c("Human Kidney Renal Clear Cell Carcinoma",
"Human Head and Neck Squamous Carcinoma",
"Human Lung Squamous Carcinoma",
"Human Lung Adenocarcinoma",
"Human Pancreas Carcinoma")
names <- c("kirc", "hnsc", "lusc", "luad", "paad")
ksa <- read.gmt("data/gold_standard_CoPheeKSA.gmt")
#meta <- read.csv("data/KSA_gold_standard.csv")
#meta <- meta[!duplicated(meta$seq_15),]
#geneID <- ensembldb::select(EnsDb.Hsapiens.v86, keys = meta$UniProt.ID.1, keytype = "UNIPROTID",
#        columns = c("SYMBOL", "UNIPROTID", "GENEID"))
#meta$UniProt.ID.1_SYMBOL <- plyr::mapvalues(meta$UniProt.ID.1, from = geneID$UNIPROTID,
#        to = geneID$SYMBOL, warn_missing = FALSE)
#meta$GS <- paste(meta$UniProt.ID.1_SYMBOL, meta$Position, sep="_")
#ksa$gene <- plyr::mapvalues(ksa$gene, from = meta$seq_15, to = meta$GS)

i <- 1
for (name in names) {
    cat("\n\n")
    cat("# ", full_name[i], sep = "")
    cat("\n\n")
    i <- i + 1
    dps <- read.csv(paste("output/DPS/", name, "_fc_0.05_kinases.csv",
        sep = ""))
    dps_plus <- dps[dps$Fold_Change > 0, ]
    dps_neg <- dps[dps$Fold_Change < 0, ]
    
    cat("\n\n")
    cat("## Positive")
    cat("\n\n")

    dps <- dps_plus
    dps <- dps[order(dps$Adjusted_P_Value, decreasing = TRUE), ]
    gse <- enricher(gene = dps$Seq, TERM2GENE = ksa)
    dir.create(paste("output/pho/", name, "/", sep = ""), showWarnings = FALSE)
    write.table(gse@result, paste("output/pho/", name, "/KSEA.csv",
        sep = ""))
    cat("\n\n")
    cat("### Barplots")
    cat("\n\n")
    print(mutate(gse, qscore = -log(p.adjust, base = 10)) %>%
        barplot(x = "qscore") + ggtitle(full_name[i]))

    cat("\n\n")
    cat("### Dotplots")
    cat("\n\n")
    print(dotplot(gse, showCategory = 30) + ggtitle(full_name[i]))

    cat("\n\n")
    cat("### Kinase-Concept Network")
    cat("\n\n")
    print(cnetplot(gse, color.params = list(foldChange = dps$Fold_Change)) +
        ggtitle(full_name[i]))

    cat("\n\n")
    cat("### Enrichment Map")
    cat("\n\n")
    print(emapplot(enrichplot::pairwise_termsim(gse)) + ggtitle(full_name[i]))
    
    cat("\n\n")
    cat("## Negative")
    cat("\n\n")

    dps <- dps_neg
    dps <- dps[order(dps$Adjusted_P_Value, decreasing = TRUE), ]
    gse <- enricher(gene = dps$Seq, TERM2GENE = ksa)
    dir.create(paste("output/pho/", name, "/", sep = ""), showWarnings = FALSE)
    write.table(gse@result, paste("output/pho/", name, "/KSEA.csv",
        sep = ""))
    cat("\n\n")
    cat("### Barplots")
    cat("\n\n")
    print(mutate(gse, qscore = -log(p.adjust, base = 10)) %>%
        barplot(x = "qscore") + ggtitle(full_name[i]))

    cat("\n\n")
    cat("### Dotplots")
    cat("\n\n")
    print(dotplot(gse, showCategory = 30) + ggtitle(full_name[i]))

    cat("\n\n")
    cat("### Kinase-Concept Network")
    cat("\n\n")
    print(cnetplot(gse, color.params = list(foldChange = dps$Fold_Change)) +
        ggtitle(full_name[i]))

    cat("\n\n")
    cat("### Enrichment Map")
    cat("\n\n")
    print(emapplot(enrichplot::pairwise_termsim(gse)) + ggtitle(full_name[i]))
}

Human Kidney Renal Clear Cell Carcinoma

Positive

Barplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Dotplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Kinase-Concept Network

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Enrichment Map

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
f0809ae Zhen Zuo 2024-06-17
9d7bb61 Zhen Zuo 2024-06-16
e55118d Zhen Zuo 2024-06-16
3477290 Zhen Zuo 2024-06-16

Negative

Barplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Dotplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Kinase-Concept Network

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Enrichment Map

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Human Head and Neck Squamous Carcinoma

Positive

Barplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
f0809ae Zhen Zuo 2024-06-17
9d7bb61 Zhen Zuo 2024-06-16
e55118d Zhen Zuo 2024-06-16
3477290 Zhen Zuo 2024-06-16

Dotplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Kinase-Concept Network

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Enrichment Map

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Negative

Barplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Dotplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
f0809ae Zhen Zuo 2024-06-17
9d7bb61 Zhen Zuo 2024-06-16
e55118d Zhen Zuo 2024-06-16
3477290 Zhen Zuo 2024-06-16

Kinase-Concept Network

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Enrichment Map

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Human Lung Squamous Carcinoma

Positive

Barplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Dotplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Kinase-Concept Network

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
f0809ae Zhen Zuo 2024-06-17
9d7bb61 Zhen Zuo 2024-06-16
e55118d Zhen Zuo 2024-06-16
3477290 Zhen Zuo 2024-06-16

Enrichment Map

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Negative

Barplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Dotplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Kinase-Concept Network

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Enrichment Map

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
f0809ae Zhen Zuo 2024-06-17
9d7bb61 Zhen Zuo 2024-06-16
e55118d Zhen Zuo 2024-06-16
3477290 Zhen Zuo 2024-06-16

Human Lung Adenocarcinoma

Positive

Barplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24
3477290 Zhen Zuo 2024-06-16

Dotplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Kinase-Concept Network

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Enrichment Map

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Negative

Barplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Dotplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Kinase-Concept Network

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Enrichment Map

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Human Pancreas Carcinoma

Positive

Barplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Dotplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Kinase-Concept Network

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Enrichment Map

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Negative

Barplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Dotplots

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Kinase-Concept Network

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

Enrichment Map

Version Author Date
85fc7b1 Zhen Zuo 2024-06-24

sessionInfo()
R version 4.4.0 (2024-04-24)
Platform: aarch64-apple-darwin20
Running under: macOS Sonoma 14.5

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/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/New_York
tzcode source: internal

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

other attached packages:
 [1] EnsDb.Hsapiens.v86_2.99.0 ensembldb_2.28.0         
 [3] AnnotationFilter_1.28.0   GenomicFeatures_1.56.0   
 [5] AnnotationDbi_1.66.0      Biobase_2.64.0           
 [7] GenomicRanges_1.56.1      GenomeInfoDb_1.40.1      
 [9] IRanges_2.38.0            S4Vectors_0.42.0         
[11] BiocGenerics_0.50.0       ggplot2_3.5.1            
[13] clusterProfiler_4.12.0   

loaded via a namespace (and not attached):
  [1] RColorBrewer_1.1-3          rstudioapi_0.16.0          
  [3] jsonlite_1.8.8              magrittr_2.0.3             
  [5] farver_2.1.2                rmarkdown_2.27             
  [7] BiocIO_1.14.0               fs_1.6.4                   
  [9] zlibbioc_1.50.0             vctrs_0.6.5                
 [11] Rsamtools_2.20.0            memoise_2.0.1              
 [13] RCurl_1.98-1.14             ggtree_3.12.0              
 [15] S4Arrays_1.4.1              htmltools_0.5.8.1          
 [17] curl_5.2.1                  SparseArray_1.4.8          
 [19] gridGraphics_0.5-1          sass_0.4.9                 
 [21] bslib_0.7.0                 plyr_1.8.9                 
 [23] cachem_1.1.0                GenomicAlignments_1.40.0   
 [25] whisker_0.4.1               igraph_2.0.3               
 [27] lifecycle_1.0.4             pkgconfig_2.0.3            
 [29] Matrix_1.7-0                R6_2.5.1                   
 [31] fastmap_1.2.0               gson_0.1.0                 
 [33] MatrixGenerics_1.16.0       GenomeInfoDbData_1.2.12    
 [35] digest_0.6.35               aplot_0.2.3                
 [37] enrichplot_1.24.0           ggnewscale_0.4.10          
 [39] colorspace_2.1-0            patchwork_1.2.0            
 [41] rprojroot_2.0.4             RSQLite_2.3.7              
 [43] labeling_0.4.3              fansi_1.0.6                
 [45] abind_1.4-5                 httr_1.4.7                 
 [47] polyclip_1.10-6             compiler_4.4.0             
 [49] bit64_4.0.5                 withr_3.0.0                
 [51] BiocParallel_1.38.0         viridis_0.6.5              
 [53] DBI_1.2.3                   highr_0.11                 
 [55] ggforce_0.4.2               MASS_7.3-61                
 [57] DelayedArray_0.30.1         rjson_0.2.21               
 [59] HDO.db_0.99.1               tools_4.4.0                
 [61] ape_5.8                     scatterpie_0.2.3           
 [63] httpuv_1.6.15               glue_1.7.0                 
 [65] restfulr_0.0.15             nlme_3.1-165               
 [67] GOSemSim_2.30.0             promises_1.3.0             
 [69] grid_4.4.0                  shadowtext_0.1.3           
 [71] reshape2_1.4.4              fgsea_1.30.0               
 [73] generics_0.1.3              gtable_0.3.5               
 [75] tidyr_1.3.1                 data.table_1.15.4          
 [77] tidygraph_1.3.1             utf8_1.2.4                 
 [79] XVector_0.44.0              ggrepel_0.9.5              
 [81] pillar_1.9.0                stringr_1.5.1              
 [83] yulab.utils_0.1.4           later_1.3.2                
 [85] splines_4.4.0               dplyr_1.1.4                
 [87] tweenr_2.0.3                treeio_1.28.0              
 [89] lattice_0.22-6              rtracklayer_1.64.0         
 [91] bit_4.0.5                   tidyselect_1.2.1           
 [93] GO.db_3.19.1                Biostrings_2.72.1          
 [95] knitr_1.47                  git2r_0.33.0               
 [97] gridExtra_2.3               ProtGenerics_1.36.0        
 [99] SummarizedExperiment_1.34.0 xfun_0.45                  
[101] graphlayouts_1.1.1          matrixStats_1.3.0          
[103] stringi_1.8.4               UCSC.utils_1.0.0           
[105] workflowr_1.7.1             lazyeval_0.2.2             
[107] ggfun_0.1.5                 yaml_2.3.8                 
[109] evaluate_0.24.0             codetools_0.2-20           
[111] ggraph_2.2.1                tibble_3.2.1               
[113] qvalue_2.36.0               ggplotify_0.1.2            
[115] cli_3.6.2                   munsell_0.5.1              
[117] jquerylib_0.1.4             Rcpp_1.0.12                
[119] png_0.1-8                   XML_3.99-0.16.1            
[121] parallel_4.4.0              blob_1.2.4                 
[123] DOSE_3.30.1                 bitops_1.0-7               
[125] viridisLite_0.4.2           tidytree_0.4.6             
[127] scales_1.3.0                purrr_1.0.2                
[129] crayon_1.5.2                rlang_1.1.4                
[131] cowplot_1.1.3               fastmatch_1.1-4            
[133] KEGGREST_1.44.0