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aadded colnames to plot as names

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This commit is contained in:
Tanushree Tunstall 2022-08-10 14:06:13 +01:00
parent 4315adc556
commit 2f7558a883
3 changed files with 314 additions and 168 deletions
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4
scripts/plotting/plotting_thesis/linage_bp_dist.R
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@ -150,11 +150,11 @@ linP_dm_om
# , "mmcsm_lig_scaled"
# , "mcsm_ppi2_scaled"
# , "mcsm_na_scaled"
# , "avg_affinity_scaled")
# , "avg_lig_affinity_scaled")
# lineage_distP(merged_df2
# , with_facet = F
# , x_axis = "avg_affinity_scaled"
# , x_axis = "avg_lig_affinity_scaled"
# , y_axis = "lineage_labels"
# , x_lab = my_xlabel
# , use_lineages = c("L1", "L2", "L3", "L4")

182
scripts/plotting/plotting_thesis/preformatting.R
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@ -33,17 +33,21 @@ common_cols = c("mutationinformation"
raw_cols_stability = c("duet_stability_change"
, "deepddg"
, "ddg_dynamut2"
, "ddg_foldx")
, "ddg_foldx"
, "avg_stability")
scaled_cols_stability = c("duet_scaled"
, "deepddg_scaled"
, "ddg_dynamut2_scaled"
, "foldx_scaled")
, "foldx_scaled"
, "foldx_scaled_signC" # needed to get avg stability
, "avg_stability_scaled")
outcome_cols_stability = c("duet_outcome"
, "deepddg_outcome"
, "ddg_dynamut2_outcome"
, "foldx_outcome")
, "foldx_outcome"
, "avg_stability_outcome")
all_stability_cols = c(raw_cols_stability
, scaled_cols_stability
@ -54,17 +58,20 @@ all_stability_cols = c(raw_cols_stability
raw_cols_affinity = c("ligand_affinity_change"
, "mmcsm_lig"
, "mcsm_ppi2_affinity"
, "mcsm_na_affinity")
, "mcsm_na_affinity"
, "avg_lig_affinity")
scaled_cols_affinity = c("affinity_scaled"
, "mmcsm_lig_scaled"
, "mcsm_ppi2_scaled"
, "mcsm_na_scaled" )
, "mcsm_na_scaled"
, "avg_lig_affinity_scaled")
outcome_cols_affinity = c( "ligand_outcome"
, "mmcsm_lig_outcome"
, "mcsm_ppi2_outcome"
, "mcsm_na_outcome")
, "mcsm_na_outcome"
, "avg_lig_affinity_outcome")
all_affinity_cols = c(raw_cols_affinity
, scaled_cols_affinity
@ -90,10 +97,6 @@ all_conserv_cols = c(raw_cols_conservation
, outcome_cols_conservation)
all_cols = c(common_cols
, all_stability_cols
, all_affinity_cols
, all_conserv_cols)
########################################
categ_cols_to_factor = grep( "_outcome|_info", colnames(merged_df3) )
@ -118,161 +121,10 @@ cat("\ncols changed to factor are:\n", colnames(merged_df3)[categ_cols_to_factor
plot_cols = c("mutationinformation", "mutation_info_labels", "position", "dst_mode"
, all_cols)
df3 = merged_df3[, colnames(merged_df3)%in%plot_cols]
#=================
# PREFORMATTING: for consistency
#=================
# DONE: combining_dfs.R
# df3$sensitivity = ifelse(df3$dst_mode == 1, "R", "S")
# table(df3$sensitivity)
# ConSurf labels
#consurf_colOld = "consurf_colour_rev"
#consurf_colNew = "consurf_outcome"
#df3[[consurf_colNew]] = df3[[consurf_colOld]]
#df3[[consurf_colNew]] = as.factor(df3[[consurf_colNew]])
#df3[[consurf_colNew]]
# not this bit
#!!!!!!!!!!!!!1
#levels(df3$consurf_outcome) = c( "nsd", 1, 2, 3, 4, 5, 6, 7, 8, 9)
#levels(df3$consurf_outcome)
# SNAP2 labels
#snap2_colname = "snap2_outcome"
#df3[[snap2_colname]] <- str_replace(df3[[snap2_colname]], "effect", "Effect")
#df3[[snap2_colname]] <- str_replace(df3[[snap2_colname]], "neutral", "Neutral")
# for ref: not needed perse as function already does this and assigns labels for barplots
# labels_duet = levels(as.factor(df3$duet_outcome))
# labels_foldx = levels(as.factor(df3$foldx_outcome))
# labels_deepddg = levels(as.factor(df3$deepddg_outcome))
# labels_ddg_dynamut2_outcome = levels(as.factor(df3$ddg_dynamut2_outcome))
#
# labels_lig = levels(as.factor(df3_lig$ligand_outcome))
# labels_mmlig = levels(as.factor(df3_lig$mmcsm_lig_outcome))
# labels_ppi2 = levels(as.factor(df3_ppi2$mcsm_ppi2_outcome))
#
# labels_provean = levels(as.factor(df3$provean_outcome))
# labels_snap2 = levels(as.factor(df3$snap2_outcome))
# labels_consurf = levels(as.factor(df3$consurf_colour_rev))
# df3$consurf_colour_rev = as.factor(df3$consurf_colour_rev )
##############################################################################
#######################################
# merged_df2: NECESSARY pre-processing
######################################
df2 = merged_df2
#=================
# PREFORMATTING: for consistency
#=================
# DONE: combining_dfs.R
# df2$sensitivity = ifelse(df2$dst_mode == 1, "R", "S")
# table(df2$sensitivity)
#----------------------------------------------------
# Create dst2: fill na in dst with value of dst_mode
# for epistasis
#----------------------------------------------------
# DONE: combining_dfs.R
# df2$dst2 = ifelse(is.na(df2$dst), df2$dst_mode, df2f$dst)
#----------------------------------------------------
# reverse signs for foldx scaled values for
# to allow average with other tools
#----------------------------------------------------
head(df2['ddg_foldx'])
df2['ddg_foldxC'] = abs(df2$ddg_foldx)
head(df2['ddg_foldxC'])
head(df2['foldx_scaled'])
df2['foldx_scaled_signC'] = abs(df2$foldx_scaled)
head(df2['foldx_scaled_signC'])
rm_foldx_cols = c("ddg_foldx","foldx_scaled")
raw_cols_stab_revised = raw_cols_stability[!raw_cols_stability%in%rm_foldx_cols]
raw_cols_stab_revised = c(raw_cols_stab_revised,"ddg_foldxC")
scaled_cols_stab_revised = scaled_cols_stability[!scaled_cols_stability%in%rm_foldx_cols]
scaled_cols_stab_revised = c(scaled_cols_stab_revised, "foldx_scaled_signC")
######################################################
# Affinity related variables
# DONE:in plotting_globals.R
# DistCutOff = 10
# LigDist_colname # = "ligand_distance" # from globals
# ppi2Dist_colname = "interface_dist"
# naDist_colname = "TBC"
######################################################
# corr colnames
# drug
# "dst_mode"
# "ligand_distance"
# "DUET"
# "mCSM-lig"
# "FoldX"
# "DeepDDG"
# "ASA"
# "RSA"
# "KD"
# "RD"
# "Consurf"
# "SNAP2"
# "MAF"
# "Log (OR)"
# "-Log (P)"
# "Dynamut2"
# "mCSM-PPI2"
# "interface_dist"
corr_ps_colnames = c("DUET"
, "FoldX"
, "DeepDDG"
, "Dynamut2"
, "MAF"
, "Log (OR)"
, "-Log (P)"
# , "ASA"
# , "RSA"
# , "KD"
# , "RD"
# , "Consurf"
# , "SNAP2"
#, "mCSM-lig"
#, "ligand_distance"
#, "mCSM-PPI2"
#, "interface_dist"
, "dst_mode"
, drug
)
corr_lig_colnames = c("mCSM-lig"
, "MAF"
, "Log (OR)"
, "-Log (P)"
, "ligand_distance"
, "dst_mode"
, drug)
corr_ppi2_colnames = c("mCSM-PPI2"
, "SNAP2"
, "Log (OR)"
, "-Log (P)"
, "interface_dist"
, "dst_mode"
, drug)
corr_conservation_cols = c("ConSurf"
, "SNAP2"
, "PROVEAN"
, "MAF"
, "Log (OR)"
, "-Log (P)"
, "dst_mode"
, drug)
all_cols = c(common_cols
, all_stability_cols
, all_affinity_cols
, all_conserv_cols)