more plot modifications dm and om plots mainly
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6 changed files with 501 additions and 358 deletions
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@ -1,237 +1,230 @@
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#################
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# Numbers
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##################
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nrow(wf_mcsm_lig)
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table(wf_mcsm_lig$mutation_info_labels)
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nrow(wf_mcsm_ppi2)
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table(wf_mcsm_ppi2$mutation_info_labels)
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all_dm_om_df = dm_om_wf_lf_data(df = merged_df3, gene = gene)
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#
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# lf_duet = all_dm_om_df[['lf_duet']]
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# table(lf_duet$param_type)
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################################################################
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geneL_normal = c("pnca")
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geneL_na = c("gid", "rpob")
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geneL_ppi2 = c("alr", "embb", "katg", "rpob")
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#======================
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# Data: Dist+genomics
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#======================
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lf_dist_genP = all_dm_om_df[['lf_dist_gen']]
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wf_dist_genP = all_dm_om_df[['wf_dist_gen']]
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levels(lf_dist_genP$param_type)
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#lf_dist_genP$param_type <- factor(lf_dist_genP$param_type, levels=c("Log10(MAF)", "Lig Dist(Å)", "PPI Dist(Å)"))
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table(lf_dist_genP$param_type)
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if (tolower(gene)%in%geneL_na){
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lf_mcsm_na
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}
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genomics_param = c("Log10(MAF)")
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if (tolower(gene)%in%geneL_ppi2){
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lf_mcsm_ppi2
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}
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dist_genP = lf_bp2(lf_dist_genP
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#, p_title
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, violin_quantiles = c(0.5), monochrome = F)
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colnames(lf_duet)
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table(lf_duet$param_type)
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#-------------------
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# Genomics data plot
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#-------------------
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genomics_dataP = lf_dist_genP[lf_dist_genP$param_type%in%genomics_param,]
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genomics_dataP$param_type = factor(genomics_dataP$param_type)
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table(genomics_dataP$param_type)
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static_colsP = c("Lig Dist(Å)","ASA", "RSA","RD","KD","Log10(MAF)")
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genomicsP = lf_bp2(genomics_dataP
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#, p_title = ""
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, violin_quantiles = c(0.5), monochrome = F)
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stability_suffix <- paste0(delta_symbol, delta_symbol, "G")
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lf_commonP = lf_duet[!lf_duet$param_type%in%c("DUET ΔΔG"),]
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lf_commonP$param_type = levels(droplevels(lf_commonP$param_type))
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table(lf_commonP$param_type); colnames(lf_commonP)
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lf_commonP$outcome = lf_commonP$duet_outcome
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lf_commonP$duet_outcome = NULL
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genomicsP
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#check
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wilcox.test(wf_dist_genP$`Log10(MAF)`[wf_dist_genP$mutation_info_labels=="R"]
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, wf_dist_genP$`Log10(MAF)`[wf_dist_genP$mutation_info_labels=="S"], paired = FALSE)
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lf_duet$outcome = lf_duet$duet_outcome
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lf_duet$duet_outcome = NULL
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lf_duetP = lf_duet[!lf_duet$param_type%in%c(static_colsP, "outcome"),]
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lf_duetP$param_type = levels(droplevels(lf_duetP$param_type))
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table(lf_duetP$param_type); colnames(lf_duetP)
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colnames(lf_duetP)
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tapply(wf_dist_genP$`Log10(MAF)`, wf_dist_genP$mutation_info_labels, summary)
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lf_foldx$outcome = lf_foldx$foldx_outcome
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lf_foldx$foldx_outcome = NULL
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lf_foldxP = lf_foldx[!lf_foldx$param_type%in%c(static_colsP,"outcome"),]
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lf_foldxP$param_type = levels(droplevels(lf_foldxP$param_type))
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table(lf_foldxP$param_type)
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colnames(lf_foldxP)
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#-------------------
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# Distance data plot: not genomics data
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#-------------------
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dist_dataP = lf_dist_genP[!lf_dist_genP$param_type%in%genomics_param,]
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#dist_dataP$param_type = factor(dist_dataP$param_type)
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table(dist_dataP$param_type)
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distanceP = lf_bp2(dist_dataP
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#, p_title = ""
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, violin_quantiles = c(0.5), monochrome = F)
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lf_deepddg$outcome = lf_deepddg$deepddg_outcome
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lf_deepddg$deepddg_outcome = NULL
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lf_deepddgP = lf_deepddg[!lf_deepddg$param_type%in%c(static_colsP, "outcome"),]
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lf_deepddgP$param_type = levels(droplevels(lf_deepddgP$param_type))
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distanceP
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# check
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wilcox.test(wf_dist_genP$`PPI Dist(Å)`[wf_dist_genP$mutation_info_labels=="R"]
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, wf_dist_genP$`PPI Dist(Å)`[wf_dist_genP$mutation_info_labels=="S"], paired = FALSE)
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wilcox.test(wf_dist_genP$`Lig Dist(Å)`[wf_dist_genP$mutation_info_labels=="R"]
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, wf_dist_genP$`Lig Dist(Å)`[wf_dist_genP$mutation_info_labels=="S"], paired = FALSE)
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tapply(wf_dist_genP$`PPI Dist(Å)`, wf_dist_genP$mutation_info_labels, summary)
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tapply(wf_dist_genP$`Lig Dist(Å)`, wf_dist_genP$mutation_info_labels, summary)
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#==============
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# Plot:DUET
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#==============
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lf_duetP = all_dm_om_df[['lf_duet']]
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#lf_duetP = lf_duet[!lf_duet$param_type%in%c(static_colsP),]
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table(lf_duetP$param_type)
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lf_duetP$param_type = factor(lf_duetP$param_type)
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table(lf_duetP$param_type)
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duetP = lf_bp2(lf_duetP
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#, p_title = paste0("Stability",stability_suffix)
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, violin_quantiles = c(0.5), monochrome = F)
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#==============
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# Plot:FoldX
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#==============
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lf_foldxP = all_dm_om_df[['lf_foldx']]
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#lf_foldxP = lf_foldx[!lf_foldx$param_type%in%c(static_colsP),]
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table(lf_foldxP$param_type)
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lf_foldxP$param_type = factor(lf_foldxP$param_type)
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table(lf_foldxP$param_type)
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foldxP = lf_bp2(lf_foldxP
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#, p_title = paste0("Stability",stability_suffix)
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, violin_quantiles = c(0.5), monochrome = F)
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#==============
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# Plot:DeepDDG
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#==============
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lf_deepddgP = all_dm_om_df[['lf_deepddg']]
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#lf_deepddgP = lf_deepddg[!lf_deepddg$param_type%in%c(static_colsP),]
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table(lf_deepddgP$param_type)
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lf_deepddgP$param_type = factor(lf_deepddgP$param_type)
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table(lf_deepddgP$param_type)
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colnames(lf_deepddgP)
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deepddgP = lf_bp2(lf_deepddgP
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#, p_title = paste0("Stability",stability_suffix)
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, violin_quantiles = c(0.5), monochrome = F
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, dot_transparency = 0.3)
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deepddgP
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lf_dynamut2$outcome = lf_dynamut2$ddg_dynamut2_outcome
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lf_dynamut2$ddg_dynamut2_outcome = NULL
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lf_dynamut2P = lf_dynamut2[!lf_dynamut2$param_type%in%c(static_colsP, "outcome"),]
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lf_dynamut2P$param_type = levels(droplevels(lf_dynamut2P$param_type))
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#==============
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# Plot: Dynamut2
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#==============
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lf_dynamut2P = all_dm_om_df[['lf_dynamut2']]
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#lf_dynamut2P = lf_dynamut2[!lf_dynamut2$param_type%in%c(static_colsP),]
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table(lf_dynamut2P$param_type)
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lf_dynamut2P$param_type = factor(lf_dynamut2P$param_type)
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table(lf_dynamut2P$param_type)
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colnames(lf_dynamut2P)
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dynamut2P = lf_bp2(lf_dynamut2P
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#, p_title = paste0("Stability",stability_suffix)
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, violin_quantiles = c(0.5), monochrome = F)
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lf_consurf$outcome = lf_consurf$consurf_outcome
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lf_consurf$consurf_outcome = NULL
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lf_consurfP = lf_consurf[!lf_consurf$param_type%in%c(static_colsP),]
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lf_consurfP$param_type = levels(droplevels(lf_consurfP$param_type))
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#==============
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# Plot:ConSurf
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#==============
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lf_consurfP = all_dm_om_df[['lf_consurf']]
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#lf_consurfP = lf_consurf[!lf_consurf$param_type%in%c(static_colsP),]
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table(lf_consurfP$param_type)
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lf_consurfP$param_type = factor(lf_consurfP$param_type)
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table(lf_consurfP$param_type)
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colnames(lf_consurfP)
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consurfP = lf_bp2(lf_consurfP
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#, p_title = paste0("Stability",stability_suffix)
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, violin_quantiles = c(0.5), monochrome = F)
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lf_snap2$outcome = lf_snap2$snap2_outcome
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lf_snap2$snap2_outcome = NULL
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lf_snap2P = lf_snap2[!lf_snap2$param_type%in%c(static_colsP),]
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lf_snap2P$param_type = levels(droplevels(lf_snap2P$param_type))
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#==============
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# Plot:SNAP2
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#==============
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lf_snap2P = all_dm_om_df[['lf_snap2']]
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#lf_snap2P = lf_snap2[!lf_snap2$param_type%in%c(static_colsP),]
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table(lf_snap2P$param_type)
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lf_snap2P$param_type = factor(lf_snap2P$param_type)
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table(lf_snap2P$param_type)
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colnames(lf_snap2P)
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snap2P = lf_bp2(lf_snap2P
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#, p_title = paste0("Stability",stability_suffix)
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, violin_quantiles = c(0.5), monochrome = F)
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lf_provean$outcome = lf_provean$provean_outcome
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lf_provean$provean_outcome = NULL
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lf_proveanP = lf_provean[!lf_provean$param_type%in%c(static_colsP),]
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lf_proveanP$param_type = levels(droplevels(lf_proveanP$param_type))
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#==============
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# Plot:PROVEAN
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#==============
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lf_proveanP = all_dm_om_df[['lf_provean']]
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#lf_proveanP = lf_provean[!lf_provean$param_type%in%c(static_colsP),]
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table(lf_proveanP$param_type)
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lf_proveanP$param_type = factor(lf_proveanP$param_type)
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table(lf_proveanP$param_type)
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colnames(lf_proveanP)
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bar = rbind(colnames(lf_duetP)
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, colnames(lf_foldxP)
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, colnames(lf_deepddgP)
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, colnames(lf_dynamut2P)
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, colnames(lf_consurfP)
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, colnames(lf_snap2P)
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, colnames(lf_proveanP)
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)
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bar
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lf_df_stabP = rbind((lf_duetP)
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, (lf_foldxP)
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, (lf_deepddgP)
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, (lf_dynamut2P))
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lf_df_consP = rbind((lf_consurfP)
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, (lf_snap2P)
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, (lf_proveanP))
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table(lf_df_stabP$param_type)
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# VERY USEFUL for seeing numbers for param types
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table(lf_df_stabP$param_type,lf_df_stabP$outcome)
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table(lf_df_consP$param_type,lf_df_consP$outcome)
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#==============
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# Plot:BP
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#==============
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stability_suffix <- paste0(delta_symbol, delta_symbol, "G")
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# lf_bp(lf_df_stabP, p_title = paste0("Stability",stability_suffix)
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# , violin_quantiles = c(0.5))
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# lf_bp(lf_df_consP, p_title = "Evolutionary Conservation"
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# , violin_quantiles = c(0.5))
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lf_bp2(lf_df_stabP, p_title = paste0("Stability",stability_suffix)
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proveanP = lf_bp2(lf_proveanP
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#, p_title = paste0("Stability",stability_suffix)
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, violin_quantiles = c(0.5), monochrome = F)
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lf_bp2(lf_duet, p_title = paste0("Stability",stability_suffix)
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, violin_quantiles = c(0.5), monochrome = F)
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lf_bp2(lf_df_consP, p_title = "Evolutionary Conservation"
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, violin_quantiles = c(0.5), monochrome = F)
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#HMMM: Bollocks!
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lf_bp2(lf_commonP, p_title = paste0("Residue level properties")
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, violin_quantiles = c(0.5)
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, monochrome = T) # doesn't plot stat bars
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lf_bp(lf_commonP, p_title = paste0("Residue level properties")
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, violin_quantiles = c(0.5)) #plots stat bars but incorrect result
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lf_unpaired_stats(lf_duet)
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wilcox.test(wf_duet$`Lig Dist(Å)`[wf_duet$mutation_info_labels=="R"]
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, wf_duet$`Lig Dist(Å)`[wf_duet$mutation_info_labels=="S"])
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wilcox.test(wf_duet$ASA[wf_duet$mutation_info_labels=="R"]
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, wf_duet$ASA[wf_duet$mutation_info_labels=="S"])
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# 1: variable
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# 9: conserved
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# CHECK THESE
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foo = merged_df3[c("dst_mode", "mutation_info_labels", "consurf_colour_rev"
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, "consurf_scaled"
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, "consurf_score"
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, "consurf_outcome"
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, "snap2_score"
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, "snap2_scaled"
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, "snap2_outcome"
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, "provean_score"
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, "provean_scaled"
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, "provean_outcome")]
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################
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# Affinity
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################
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# ligand
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lf_mcsm_lig$outcome = lf_mcsm_lig$ligand_outcome
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lf_mcsm_lig$ligand_outcome = NULL
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colnames(lf_mcsm_lig)
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table(lf_mcsm_lig$param_type)
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lf_mcsm_lig$outcome = lf_mcsm_lig$ligand_outcome
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lf_mcsm_ligP = lf_mcsm_lig[!lf_mcsm_lig$param_type%in%c(static_colsP, "outcome"),]
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#lf_mcsm_ligP$param_type = levels(droplevels(lf_mcsm_ligP))
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#==============
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# Plot: mCSM-lig
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#==============
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lf_mcsm_ligP = all_dm_om_df[['lf_mcsm_lig']]
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#lf_mcsm_ligP = lf_mcsm_lig[!lf_mcsm_lig$param_type%in%c(static_colsP),]
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table(lf_mcsm_ligP$param_type)
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lf_mcsm_ligP$param_type = factor(lf_mcsm_ligP$param_type)
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table(lf_mcsm_ligP$param_type)
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lf_mcsm_ligP$ligand_outcome = NULL
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colnames(lf_mcsm_ligP)
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if (tolower(gene)%in%geneL_na){
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lf_mcsm_na$outcome = lf_mcsm_na$mcsm_na_outcome
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#lf_mcsm_na$mcsm_na_outcome = NULL
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lf_mcsm_naP = lf_mcsm_na[!lf_mcsm_na$param_type%in%c(static_colsP, "outcome"),]
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#lf_mcsm_naP$param_type = levels(droplevels(lf_mcsm_naP))
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table(lf_mcsm_naP$param_type)
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lf_mcsm_naP$mcsm_na_outcome = NULL
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colnames(lf_mcsm_naP)
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}
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mcsmligP = lf_bp2(lf_mcsm_ligP
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#, p_title = paste0("Stability",stability_suffix)
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, violin_quantiles = c(0.5), monochrome = F)
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#==============
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# Plot: mCSM-ppi2
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#==============
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if (tolower(gene)%in%geneL_ppi2){
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lf_mcsm_ppi2$outcome = lf_mcsm_ppi2$mcsm_ppi2_outcome
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colnames(lf_mcsm_ppi2)
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#lf_mcsm_ppi2$mcsm_ppi2_outcome = NULL
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lf_mcsm_ppi2P = lf_mcsm_ppi2[!lf_mcsm_ppi2$param_type%in%c(static_colsP, "outcome"),]
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#lf_mcsm_ppi2P$param_type = levels(droplevels(lf_mcsm_ppi2P))
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lf_mcsm_ppi2P = all_dm_om_df[['lf_mcsm_ppi2']]
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#lf_mcsm_ppi2P = lf_mcsm_ppi2[!lf_mcsm_ppi2$param_type%in%c(static_colsP),]
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table(lf_mcsm_ppi2P$param_type)
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lf_mcsm_ppi2P$param_type = factor(lf_mcsm_ppi2P$param_type)
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table(lf_mcsm_ppi2P$param_type)
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lf_mcsm_ppi2P$mcsm_ppi2_outcome = NULL
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colnames(lf_mcsm_ppi2P)
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mcsmppi2P = lf_bp2(lf_mcsm_ppi2P
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#, p_title = paste0("Stability",stability_suffix)
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, violin_quantiles = c(0.5), monochrome = F)
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}
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#==============
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# Plot: mCSM-NA
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#==============
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if (tolower(gene)%in%geneL_na){
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lf_mcsm_naP = all_dm_om_df[['lf_mcsm_na']]
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#lf_mcsm_naP = lf_mcsm_na[!lf_mcsm_na$param_type%in%c(static_colsP),]
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table(lf_mcsm_naP$param_type)
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lf_mcsm_naP$param_type = factor(lf_mcsm_naP$param_type)
|
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table(lf_mcsm_naP$param_type)
|
||||
|
||||
mcsmnaP = lf_bp2(lf_mcsm_naP
|
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#, p_title = paste0("Stability",stability_suffix)
|
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, violin_quantiles = c(0.5), monochrome = F)
|
||||
}
|
||||
|
||||
bar = rbind(colnames(lf_mcsm_ligP)
|
||||
#, colnames(lf_mcsm_naP)
|
||||
, colnames(lf_mcsm_ppi2P))
|
||||
bar
|
||||
######################################
|
||||
# Outplot with stats
|
||||
######################################
|
||||
|
||||
lf_df_affP = rbind((lf_mcsm_ligP)
|
||||
, (lf_mcsm_ppi2P))
|
||||
cowplot::plot_grid(
|
||||
cowplot::plot_grid(duetP, foldxP, deepddgP, dynamut2P, genomicsP, distanceP
|
||||
, nrow=1),
|
||||
# cowplot::plot_grid(genomicsP, distanceP
|
||||
# , nrow = 1),
|
||||
cowplot::plot_grid(consurfP, snap2P, proveanP
|
||||
, mcsmligP
|
||||
, mcsmppi2P
|
||||
#, mcsmnaP
|
||||
, nrow=1),
|
||||
nrow=2)
|
||||
|
||||
lf_bp(lf_df_affP, p_title = paste0("Affinity changes")
|
||||
, violin_quantiles = c(0.5))
|
||||
#, monochrome = T) # doesn't plot stat bars
|
||||
|
||||
wilcox.test(wf_mcsm_lig$ASA[wf_mcsm_lig$mutation_info_labels=="R"]
|
||||
, wf_mcsm_lig$ASA[wf_mcsm_lig$mutation_info_labels=="S"])
|
||||
foo = lf_consurfP
|
||||
|
||||
wilcox.test(wf_mcsm_ppi2$ASA[wf_mcsm_ppi2$mutation_info_labels=="R"]
|
||||
, wf_mcsm_ppi2$ASA[wf_mcsm_ppi2$mutation_info_labels=="S"])
|
||||
# proveanP = lf_bp2(lf_proveanP, colour_categ = "mutation_info_labels"
|
||||
# , p_title = paste0("Evolutionary conservation")
|
||||
# , dot_transparency = 1
|
||||
# , violin_quantiles = c(0.5), monochrome = F)
|
||||
#
|
||||
# proveanP
|
||||
|
||||
#===============================
|
||||
p1 = lf_bp2(lf_df_stabP, p_title = paste0("Stability",stability_suffix)
|
||||
, violin_quantiles = c(0.5), monochrome = F)
|
||||
|
||||
p2 = lf_bp2(lf_df_consP, p_title = "Evolutionary Conservation"
|
||||
, violin_quantiles = c(0.5), monochrome = F)
|
||||
|
||||
p3 = lf_bp2(lf_df_affP, p_title = paste0("Affinity changes")
|
||||
, violin_quantiles = c(0.5), monochrome = F)
|
||||
|
||||
cowplot::plot_grid(p1,cowplot::plot_grid(p2, p3), nrow=2)
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue