Last updated: 2023-03-13

Checks: 5 1

Knit directory: LungCancer_SotilloLab/analysis/

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Load packages and dataset

Packages

#package
library(SummarizedExperiment)
library(MultiAssayExperiment)
library(PhosR)
library(directPA)
library(tidyverse)
source("../code/utils.R")
data(PhosphoSitePlus)
knitr::opts_chunk$set(warning = FALSE, message = FALSE, autodep = TRUE)

Pre-processed data

load("../output/processedData_RUN5.RData")

#load saved result list
load("../output/allResList_RUN5_timeBased.RData")

Phospho at 10min

10 mins

Differential results

resList <- allResList$diffRatio$time_0.17 %>%
  filter(compare %in% c("combo_DMSO","brigatinib_DMSO","dasatinib_DMSO"))

phosTab <- resList %>%
  mutate(site = paste0(str_replace(toupper(site),"_",";"),";")) %>%
  select(site, t_statistic, compare) %>% 
  arrange(abs(t_statistic)) %>%
  distinct(site, compare,.keep_all = TRUE) %>%
  pivot_wider(names_from = compare, values_from = t_statistic) %>%
  data.frame() %>% column_to_rownames("site")

Down in both dasatinib and brigatinib

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = pi, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
              pvalue       size
Yang.mTOR     4.480679e-08 13  
Yang.S6K      0.0002145583 5   
MTOR          0.001918293  14  
Humphrey.mTOR 0.02827609   6   
PRKACA        0.03066512   8   
GSK3B         0.09570267   7

Down more in brigatinib

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = -3*pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
              pvalue       size
Yang.mTOR     0.0002815882 13  
Yang.S6K      0.001280928  5   
Humphrey.mTOR 0.004591874  6   
Yang.Erk1     0.1155681    12  
PRKACA        0.2834576    8   
CDK1          0.3124617    8

Down more in dasatinib

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = 3*pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
          pvalue     size
GSK3B     0.07319936 7   
CDK1      0.159301   8   
MTOR      0.3201163  14  
Yang.S6K  0.3224696  5   
Yang.mTOR 0.3563981  13  
PRKACA    0.5505595  8

Up in both

Brigatinib up

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = 0, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
          pvalue      size
MAPK1     0.006888582 23  
MAPK14    0.01485456  7   
MAPK3     0.0152895   6   
CSNK2A1   0.2116639   13  
Yang.Erk1 0.250967    12  
CDK1      0.5257975   8

Brigatinib up

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
        pvalue     size
MAPK3   0.05179977 6   
MAPK14  0.05774309 7   
MAPK1   0.3637176  23  
CSNK2A1 0.4731279  13  
CDK1    0.5547844  8   
GSK3B   0.6809414  7

dasatinib up

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = -pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
          pvalue     size
MAPK1     0.08012861 23  
Yang.Erk1 0.0981929  12  
CSNK2A1   0.2117119  13  
MAPK14    0.2379388  7   
MAPK3     0.3363144  6   
CDK1      0.6382996  8

More down in combo compared to brigatinib

kPA1 <- kinasePA(Tc = phosTab[,c(2,1)], direction = 3*pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
              pvalue     size
Yang.mTOR     0.02014496 13  
Yang.S6K      0.03611071 5   
Humphrey.mTOR 0.0644819  6   
CSNK2A1       0.1523511  13  
Yang.Erk1     0.5800391  12  
CDK1          0.6234786  8

More down in combo compared to dasatinib

kPA1 <- kinasePA(Tc = phosTab[,c(3,1)], direction = 3*pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
              pvalue      size
Yang.mTOR     0.001477658 13  
Yang.S6K      0.00252609  5   
Humphrey.mTOR 0.003680745 6   
CSNK2A1       0.1482503   13  
Yang.Erk1     0.2903299   12  
MAPK14        0.6199213   7

Pair-wise comparison

z1 <- perturbPlot2d(Tc=phosTab[,c(1,3)], annotation=PhosphoSite.mouse, cex=0.5, xlim=c(-8, 8), ylim=c(-8, 8), main="Kinase perturbation analysis")

z1 <- perturbPlot2d(Tc=phosTab[,c(1,2)], annotation=PhosphoSite.mouse, cex=0.5, xlim=c(-8, 8), ylim=c(-8, 8), main="Kinase perturbation analysis")

z1 <- perturbPlot2d(Tc=phosTab[,c(2,3)], annotation=PhosphoSite.mouse, cex=0.5, xlim=c(-8, 8), ylim=c(-8, 8), main="Kinase perturbation analysis")

16 h

Differential results

resList <- allResList$diffRatio$time_16 %>%
  filter(compare %in% c("combo_DMSO","brigatinib_DMSO","dasatinib_DMSO"))

phosTab <- resList %>%
  mutate(site = paste0(str_replace(toupper(site),"_",";"),";")) %>%
  select(site, t_statistic, compare) %>% 
  arrange(abs(t_statistic)) %>%
  distinct(site, compare,.keep_all = TRUE) %>%
  pivot_wider(names_from = compare, values_from = t_statistic) %>%
  data.frame() %>% column_to_rownames("site")

phosTab <- phosTab[,c("combo_DMSO","brigatinib_DMSO","dasatinib_DMSO")]

Down in both dasatinib and brigatinib

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = pi, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
          pvalue       size
Yang.S6K  1.935074e-06 5   
Yang.mTOR 0.0001058531 9   
CSNK2A1   0.008407779  12  
CDK1      0.03549036   5   
GSK3B     0.04829208   7   
MTOR      0.2403266    11

Down more in brigatinib

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = -3*pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
          pvalue      size
MAPK1     0.003655472 16  
Yang.Erk1 0.005229815 10  
Yang.S6K  0.005512186 5   
Yang.mTOR 0.006800054 9   
CDK1      0.009076267 5   
CSNK2A1   0.06377695  12

Down more in dasatinib

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = 3*pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
          pvalue     size
Yang.S6K  0.04147193 5   
Yang.mTOR 0.04199342 9   
CSNK2A1   0.08113055 12  
GSK3B     0.1525764  7   
MTOR      0.6049266  11  
CDK1      0.8384538  5

Up in both

Brigatinib up

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = 0, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
       pvalue       size
MAPK14 2.560996e-07 7   
MAPK3  0.2791011    5   
MTOR   0.4380246    11  
PRKACA 0.4380843    5   
MAPK8  0.4953679    5   
MAPK1  0.8510308    16

Brigatinib up

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
        pvalue      size
MAPK14  0.006685154 7   
MTOR    0.6613747   11  
MAPK3   0.7541993   5   
MAPK8   0.8682273   5   
GSK3B   0.9019701   7   
CSNK2A1 0.9111407   12

dasatinib up

kPA1 <- kinasePA(Tc = phosTab[,c(2,3)], direction = -pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
          pvalue     size
MAPK14    0.00556855 7   
PRKACA    0.0229172  5   
MAPK1     0.06440958 16  
MAPK8     0.07506492 5   
MAPK3     0.1194381  5   
Yang.Erk1 0.1994064  10

More down in combo compared to brigatinib

kPA1 <- kinasePA(Tc = phosTab[,c(2,1)], direction = 3*pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
          pvalue       size
Yang.S6K  8.722524e-05 5   
Yang.mTOR 0.008413532  9   
CSNK2A1   0.01957538   12  
CDK1      0.08235032   5   
MAPK8     0.2191317    5   
MAPK1     0.3271426    16

More down in combo compared to dasatinib

kPA1 <- kinasePA(Tc = phosTab[,c(3,1)], direction = 3*pi/4, annotation = PhosphoSite.mouse)

head(kPA1$kinase)
          pvalue       size
Yang.S6K  1.605238e-05 5   
Yang.mTOR 0.009475486  9   
CDK1      0.02400547   5   
CSNK2A1   0.05486415   12  
MAPK1     0.1344611    16  
MAPK8     0.1718649    5

Pair-wise comparison

z1 <- perturbPlot2d(Tc=phosTab[,c(1,3)], annotation=PhosphoSite.mouse, cex=0.5, xlim=c(-8, 8), ylim=c(-8, 8), main="Kinase perturbation analysis")

z1 <- perturbPlot2d(Tc=phosTab[,c(1,2)], annotation=PhosphoSite.mouse, cex=0.5, xlim=c(-8, 8), ylim=c(-8, 8), main="Kinase perturbation analysis")

z1 <- perturbPlot2d(Tc=phosTab[,c(2,3)], annotation=PhosphoSite.mouse, cex=0.5, xlim=c(-8, 8), ylim=c(-8, 8), main="Kinase perturbation analysis")


sessionInfo()
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] forcats_0.5.1               stringr_1.4.1              
 [3] dplyr_1.0.9                 purrr_0.3.4                
 [5] readr_2.1.2                 tidyr_1.2.0                
 [7] tibble_3.1.8                ggplot2_3.4.1              
 [9] tidyverse_1.3.2             directPA_1.5               
[11] PhosR_1.6.0                 MultiAssayExperiment_1.22.0
[13] SummarizedExperiment_1.26.1 Biobase_2.56.0             
[15] GenomicRanges_1.48.0        GenomeInfoDb_1.32.2        
[17] IRanges_2.30.0              S4Vectors_0.34.0           
[19] BiocGenerics_0.42.0         MatrixGenerics_1.8.1       
[21] matrixStats_0.62.0         

loaded via a namespace (and not attached):
  [1] googledrive_2.0.0      colorspace_2.0-3       ggsignif_0.6.3        
  [4] ellipsis_0.3.2         class_7.3-20           rprojroot_2.0.3       
  [7] circlize_0.4.15        XVector_0.36.0         GlobalOptions_0.1.2   
 [10] ggdendro_0.1.23        fs_1.5.2               rstudioapi_0.13       
 [13] proxy_0.4-27           ggpubr_0.4.0           lubridate_1.8.0       
 [16] fansi_1.0.3            xml2_1.3.3             cachem_1.0.6          
 [19] knitr_1.39             jsonlite_1.8.3         workflowr_1.7.0       
 [22] broom_1.0.0            dbplyr_2.2.1           pheatmap_1.0.12       
 [25] compiler_4.2.0         httr_1.4.3             backports_1.4.1       
 [28] assertthat_0.2.1       Matrix_1.4-1           fastmap_1.1.0         
 [31] gargle_1.2.0           limma_3.52.2           cli_3.4.1             
 [34] later_1.3.0            htmltools_0.5.4        tools_4.2.0           
 [37] igraph_1.3.4           coda_0.19-4            gtable_0.3.0          
 [40] glue_1.6.2             GenomeInfoDbData_1.2.8 reshape2_1.4.4        
 [43] Rcpp_1.0.9             carData_3.0-5          cellranger_1.1.0      
 [46] statnet.common_4.6.0   jquerylib_0.1.4        vctrs_0.5.2           
 [49] preprocessCore_1.58.0  xfun_0.31              network_1.17.2        
 [52] rvest_1.0.2            lifecycle_1.0.3        rstatix_0.7.0         
 [55] dendextend_1.16.0      googlesheets4_1.0.0    zlibbioc_1.42.0       
 [58] MASS_7.3-58            scales_1.2.0           pcaMethods_1.88.0     
 [61] hms_1.1.1              promises_1.2.0.1       RColorBrewer_1.1-3    
 [64] yaml_2.3.5             gridExtra_2.3          sass_0.4.2            
 [67] reshape_0.8.9          calibrate_1.7.7        stringi_1.7.8         
 [70] highr_0.9              e1071_1.7-11           shape_1.4.6           
 [73] rlang_1.0.6            pkgconfig_2.0.3        bitops_1.0-7          
 [76] evaluate_0.15          lattice_0.20-45        ruv_0.9.7.1           
 [79] tidyselect_1.1.2       GGally_2.1.2           plyr_1.8.7            
 [82] magrittr_2.0.3         R6_2.5.1               generics_0.1.3        
 [85] DelayedArray_0.22.0    DBI_1.1.3              withr_2.5.0           
 [88] pillar_1.8.0           haven_2.5.0            abind_1.4-5           
 [91] RCurl_1.98-1.7         crayon_1.5.2           modelr_0.1.8          
 [94] car_3.1-0              utf8_1.2.2             tzdb_0.3.0            
 [97] rmarkdown_2.14         viridis_0.6.2          readxl_1.4.0          
[100] grid_4.2.0             git2r_0.30.1           reprex_2.0.1          
[103] digest_0.6.30          httpuv_1.6.6           munsell_0.5.0         
[106] viridisLite_0.4.0      bslib_0.4.1