################# # Numbers ################## all_dm_om_df = dm_om_wf_lf_data(df = merged_df3, gene = gene) # # lf_duet = all_dm_om_df[['lf_duet']] # table(lf_duet$param_type) ################################################################ #====================== # Data: Dist+Genomics #====================== lf_dist_genP = all_dm_om_df[['lf_dist_gen']] wf_dist_genP = all_dm_om_df[['wf_dist_gen']] levels(lf_dist_genP$param_type) #lf_dist_genP$param_type <- factor(lf_dist_genP$param_type, levels=c("Log10(MAF)", "Lig Dist(Å)", "PPI Dist(Å)")) table(lf_dist_genP$param_type) genomics_param = c("Log10(MAF)") dist_genP = lf_bp2(lf_dist_genP #, p_title , violin_quantiles = c(0.5), monochrome = F) #dist_genP #------------------- # Genomics data plot #------------------- genomics_dataP = lf_dist_genP[lf_dist_genP$param_type%in%genomics_param,] genomics_dataP$param_type = factor(genomics_dataP$param_type) table(genomics_dataP$param_type) genomicsP = lf_bp2(genomics_dataP #, p_title = "" , violin_quantiles = c(0.5), monochrome = F) genomicsP #check wilcox.test(wf_dist_genP$`Log10(MAF)`[wf_dist_genP$mutation_info_labels=="R"] , wf_dist_genP$`Log10(MAF)`[wf_dist_genP$mutation_info_labels=="S"], paired = FALSE) tapply(wf_dist_genP$`Log10(MAF)`, wf_dist_genP$mutation_info_labels, summary) #------------------- # Distance data plot: #-------------------- # not genomics dist_dataP = lf_dist_genP[!lf_dist_genP$param_type%in%genomics_param,] dist_dataP$param_type = factor(dist_dataP$param_type) table(dist_dataP$param_type) levels(dist_dataP$param_type) # relevel factor to control ordering of appearance of plot dist_dataP$param_type <-relevel(dist_dataP$param_type, "Lig Dist(Å)" ) table(dist_dataP$param_type) levels(dist_dataP$param_type) distanceP = lf_bp2(dist_dataP #, p_title = "" , violin_quantiles = c(0.5), monochrome = F) distanceP # check wilcox.test(wf_dist_genP$`PPI Dist(Å)`[wf_dist_genP$mutation_info_labels=="R"] , wf_dist_genP$`PPI Dist(Å)`[wf_dist_genP$mutation_info_labels=="S"], paired = FALSE) wilcox.test(wf_dist_genP$`Lig Dist(Å)`[wf_dist_genP$mutation_info_labels=="R"] , wf_dist_genP$`Lig Dist(Å)`[wf_dist_genP$mutation_info_labels=="S"], paired = FALSE) tapply(wf_dist_genP$`PPI Dist(Å)`, wf_dist_genP$mutation_info_labels, summary) tapply(wf_dist_genP$`Lig Dist(Å)`, wf_dist_genP$mutation_info_labels, summary) #------------------- # Distance data plot: LigDist #-------------------- levels(dist_dataP$param_type)[[1]] #Lig Dist(Å), PPI Dist(Å) dist_data_lig = dist_dataP[dist_dataP$param_type%in%c(levels(dist_dataP$param_type)[[1]]),] dist_data_lig$param_type = factor(dist_data_lig$param_type) table(dist_data_lig$param_type) levels(dist_data_lig$param_type) distanceP_lig = lf_bp2(dist_data_lig #, p_title = "" , violin_quantiles = c(0.5), monochrome = F) distanceP_lig if (tolower(gene)%in%geneL_ppi2){ #------------------- # Distance data plot: LigDist #-------------------- levels(dist_dataP$param_type)[[2]] #Lig Dist(Å), PPI Dist(Å) dist_data_ppi2 = dist_dataP[dist_dataP$param_type%in%c(levels(dist_dataP$param_type)[[2]]),] dist_data_ppi2$param_type = factor(dist_data_ppi2$param_type) table(dist_data_ppi2$param_type) levels(dist_data_ppi2$param_type) distanceP_ppi2 = lf_bp2(dist_data_ppi2 #, p_title = "" , violin_quantiles = c(0.5), monochrome = F) distanceP_ppi2 } if (tolower(gene)%in%geneL_na){ #------------------- # Distance data plot: NADist #-------------------- levels(dist_dataP$param_type)[[3]] #Lig Dist(Å), PPI Dist(Å) dist_data_na = dist_dataP[dist_dataP$param_type%in%c(levels(dist_dataP$param_type)[[3]]),] dist_data_na$param_type = factor(dist_data_na$param_type) table(dist_data_na$param_type) levels(dist_data_na$param_type) distanceP_na = lf_bp2(dist_data_na #, p_title = "" , violin_quantiles = c(0.5), monochrome = F) distanceP_na } #============== # Plot:DUET #============== lf_duetP = all_dm_om_df[['lf_duet']] #lf_duetP = lf_duet[!lf_duet$param_type%in%c(static_colsP),] table(lf_duetP$param_type) lf_duetP$param_type = factor(lf_duetP$param_type) table(lf_duetP$param_type) duetP = lf_bp2(lf_duetP #, p_title = "" , violin_quantiles = c(0.5), monochrome = F , dot_transparency = 0.2) #============== # Plot:FoldX #============== lf_foldxP = all_dm_om_df[['lf_foldx']] #lf_foldxP = lf_foldx[!lf_foldx$param_type%in%c(static_colsP),] table(lf_foldxP$param_type) lf_foldxP$param_type = factor(lf_foldxP$param_type) table(lf_foldxP$param_type) foldxP = lf_bp2(lf_foldxP #, p_title = "" , violin_quantiles = c(0.5), monochrome = F , dot_transparency = 0.1) #============== # Plot:DeepDDG #============== lf_deepddgP = all_dm_om_df[['lf_deepddg']] #lf_deepddgP = lf_deepddg[!lf_deepddg$param_type%in%c(static_colsP),] table(lf_deepddgP$param_type) lf_deepddgP$param_type = factor(lf_deepddgP$param_type) table(lf_deepddgP$param_type) deepddgP = lf_bp2(lf_deepddgP #, p_title = "" , violin_quantiles = c(0.5), monochrome = F , dot_transparency = 0.2) deepddgP #============== # Plot: Dynamut2 #============== lf_dynamut2P = all_dm_om_df[['lf_dynamut2']] #lf_dynamut2P = lf_dynamut2[!lf_dynamut2$param_type%in%c(static_colsP),] table(lf_dynamut2P$param_type) lf_dynamut2P$param_type = factor(lf_dynamut2P$param_type) table(lf_dynamut2P$param_type) dynamut2P = lf_bp2(lf_dynamut2P #, p_title = "" , violin_quantiles = c(0.5), monochrome = F , dot_transparency = 0.2) #============== # Plot:ConSurf #============== lf_consurfP = all_dm_om_df[['lf_consurf']] #lf_consurfP = lf_consurf[!lf_consurf$param_type%in%c(static_colsP),] table(lf_consurfP$param_type) lf_consurfP$param_type = factor(lf_consurfP$param_type) table(lf_consurfP$param_type) consurfP = lf_bp2(lf_consurfP #, p_title = "" , violin_quantiles = c(0.5), monochrome = F) #============== # Plot:PROVEAN #============== lf_proveanP = all_dm_om_df[['lf_provean']] #lf_proveanP = lf_provean[!lf_provean$param_type%in%c(static_colsP),] table(lf_proveanP$param_type) lf_proveanP$param_type = factor(lf_proveanP$param_type) table(lf_proveanP$param_type) proveanP = lf_bp2(lf_proveanP #, p_title = "" , violin_quantiles = c(0.5), monochrome = F) #============== # Plot:SNAP2 #============== lf_snap2P = all_dm_om_df[['lf_snap2']] #lf_snap2P = lf_snap2[!lf_snap2$param_type%in%c(static_colsP),] table(lf_snap2P$param_type) lf_snap2P$param_type = factor(lf_snap2P$param_type) table(lf_snap2P$param_type) snap2P = lf_bp2(lf_snap2P #, p_title = "" , violin_quantiles = c(0.5), monochrome = F) ############################################################################ #================ # Plot: mCSM-lig #================ lf_mcsm_ligP = all_dm_om_df[['lf_mcsm_lig']] #lf_mcsm_ligP = lf_mcsm_lig[!lf_mcsm_lig$param_type%in%c(static_colsP),] table(lf_mcsm_ligP$param_type) lf_mcsm_ligP$param_type = factor(lf_mcsm_ligP$param_type) table(lf_mcsm_ligP$param_type) mcsmligP = lf_bp2(lf_mcsm_ligP #, p_title = "" , violin_quantiles = c(0.5), monochrome = F , dot_transparency = 1) #================= # Plot: mmCSM-lig2 #================= lf_mmcsm_lig2P = all_dm_om_df[['lf_mmcsm_lig2']] #lf_mmcsm_lig2P = lf_mmcsm_lig2P[!lf_mmcsm_lig2P$param_type%in%c(static_colsP),] table(lf_mmcsm_lig2P$param_type) lf_mmcsm_lig2P$param_type = factor(lf_mmcsm_lig2P$param_type) table(lf_mmcsm_lig2P$param_type) mcsmlig2P = lf_bp2(lf_mmcsm_lig2P #, p_title = "" , violin_quantiles = c(0.5), monochrome = F , dot_transparency = 1) mcsmlig2P #================ # Plot: mCSM-ppi2 #================ if (tolower(gene)%in%geneL_ppi2){ lf_mcsm_ppi2P = all_dm_om_df[['lf_mcsm_ppi2']] #lf_mcsm_ppi2P = lf_mcsm_ppi2[!lf_mcsm_ppi2$param_type%in%c(static_colsP),] table(lf_mcsm_ppi2P$param_type) lf_mcsm_ppi2P$param_type = factor(lf_mcsm_ppi2P$param_type) table(lf_mcsm_ppi2P$param_type) mcsmppi2P = lf_bp2(lf_mcsm_ppi2P #, p_title = "" , violin_quantiles = c(0.5), monochrome = F , dot_transparency = 1) } #============== # Plot: mCSM-NA #============== if (tolower(gene)%in%geneL_na){ lf_mcsm_naP = all_dm_om_df[['lf_mcsm_na']] #lf_mcsm_naP = lf_mcsm_na[!lf_mcsm_na$param_type%in%c(static_colsP),] table(lf_mcsm_naP$param_type) lf_mcsm_naP$param_type = factor(lf_mcsm_naP$param_type) table(lf_mcsm_naP$param_type) mcsmnaP = lf_bp2(lf_mcsm_naP #, p_title = "" , violin_quantiles = c(0.5), monochrome = F , dot_transparency = 1) } ###################################### # Outplot with stats ###################################### # outdir_images = paste0("~/git/Writing/thesis/images/results/", tolower(gene), "/") # # dm_om_combinedP = paste0(outdir_images # ,tolower(gene) # ,"_dm_om_all.svg" ) # # cat("DM OM plots with stats:", dm_om_combinedP) # svg(dm_om_combinedP, width = 32, height = 18) # cowplot::plot_grid( # cowplot::plot_grid(duetP, foldxP, deepddgP, dynamut2P, genomicsP, distanceP # , nrow=1 # , rel_widths = c(1/7, 1/7,1/7,1/7, 1/7, 1.75/7)), # #, rel_widths = c(1/8, 1/8,1/8,1/8, 1/8, 2.75/8)), # for 3 distances # cowplot::plot_grid(consurfP, proveanP, snap2P # , mcsmligP # , mcsmlig2P # , mcsmppi2P # #, mcsmnaP # , nrow=1), # nrow=2) # # dev.off()