144 lines
4.5 KiB
R
144 lines
4.5 KiB
R
source("~/git/LSHTM_analysis/config/embb.R")
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source("~/git/LSHTM_analysis/scripts/plotting/plotting_colnames.R")
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source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
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my_gg_pairs=function(plot_df){
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ggpairs(plot_df,
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columns = 1:(ncol(plot_df)-1),
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upper = list(
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continuous = wrap('cor',
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method = "spearman",
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title="ρ",
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digits=2,
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justify_labels = "left",
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title_args=c(colour="black")
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)
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),
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lower = list(
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continuous = wrap("points",
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alpha = 0.7,
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size=0.5),
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combo = wrap("dot",
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alpha = 0.7,
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size=0.5)
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),
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aes(colour = factor(ifelse(plot_df$dst_mode==0,
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"S",
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"R") ),
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alpha = 0.5),
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title="Stability") +
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scale_colour_manual(values = c("red", "blue")) +
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scale_fill_manual(values = c("red", "blue")) +
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theme(text = element_text(size=12,
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face="bold") )
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}
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DistCutOff = 10
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merged_df3 = as.data.frame(merged_df3)
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corr_plotdf = corr_data_extract(merged_df3
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, gene = gene
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, drug = drug
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, extract_scaled_cols = F)
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aff_dist_cols = colnames(corr_plotdf)[grep("Dist", colnames(corr_plotdf))]
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static_cols = c("Log10(MAF)"
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, "Log10(OR)")
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corr_ps_colnames = c(static_cols
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, "DUET"
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, "FoldX"
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, "DeepDDG"
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, "Dynamut2"
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, aff_dist_cols
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, "dst_mode")
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corr_df_ps = corr_plotdf[, corr_ps_colnames]
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complete_obs_ps = nrow(corr_df_ps) - sum(is.na(corr_df_ps$`Log(OR)`))
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color_coln = which(colnames(corr_df_ps) == "dst_mode")
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corr_end = color_coln-1
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# Plot #1
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plot_corr_df_ps = my_gg_pairs(corr_df_ps)
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corr_conservation_cols = c( static_cols
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, "ConSurf"
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, "SNAP2"
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, "PROVEAN"
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, aff_dist_cols
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, "dst_mode"
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)
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corr_df_cons = corr_plotdf[, corr_conservation_cols]
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complete_obs_cons = nrow(corr_df_cons) - sum(is.na(corr_df_cons$`Log(OR)`))
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color_coln = which(colnames(corr_df_cons) == "dst_mode")
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corr_end = color_coln-1
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# Plot #2
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#my_gg_pairs(corr_df_cons)
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plot_corr_df_cons = my_gg_pairs(corr_df_cons)
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corr_df_lig = corr_plotdf[corr_plotdf["Lig-Dist"]<DistCutOff,]
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corr_lig_colnames = c(static_cols
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, "mCSM-lig"
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, "mmCSM-lig"
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, "dst_mode")
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corr_df_lig = corr_plotdf[, corr_lig_colnames]
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complete_obs_lig = nrow(corr_df_lig) - sum(is.na(corr_df_lig$`Log(OR)`))
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color_coln = which(colnames(corr_df_lig) == "dst_mode")
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corr_end = color_coln-1
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# Plot #3
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#my_gg_pairs(corr_df_lig)
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plot_corr_df_lig = my_gg_pairs(corr_df_lig)
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corr_df_ppi2 = corr_plotdf[corr_plotdf["PPI-Dist"]<DistCutOff,]
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corr_ppi2_colnames = c(static_cols
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, "mCSM-PPI2"
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, "dst_mode"
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)
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corr_df_ppi2 = corr_plotdf[, corr_ppi2_colnames]
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complete_obs_ppi2 = nrow(corr_df_ppi2) - sum(is.na(corr_df_ppi2$`Log(OR)`))
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color_coln = which(colnames(corr_df_ppi2) == "dst_mode")
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corr_end = color_coln-1
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# NOTE: DELETE LOG OR FROM CORRELATION PLOTS!!!!!
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# NOTE: ALSO MAYBE DELETE DISTANCES AS WELL
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# NOTE: http://ggobi.github.io/ggally/reference/ggally_cor.html
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# "***" if the p-value is < 0.001
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# "**" if the p-value is < 0.01
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# "*" if the p-value is < 0.05
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# "." if the p-value is < 0.10
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# "" otherwise
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#
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# Plot #4
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#my_gg_pairs(corr_df_ppi2)
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plot_corr_df_ppi2 = my_gg_pairs(corr_df_ppi2)
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# corr_df_na = corr_df_na[corr_df_na["NA-Dist"]<DistCutOff,]
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# corr_na_colnames = c(static_cols
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# , "mCSM-NA"
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# , "dst_mode"
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# )
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#
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# corr_df_na = corr_plotdf[, corr_na_colnames]
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# complete_obs_na = nrow(corr_df_na) - sum(is.na(corr_df_na$`Log(OR)`))
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# color_coln = which(colnames(corr_df_na) == "dst_mode")
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# corr_end = color_coln-1
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#
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# # Plot #5
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# #my_gg_pairs(corr_df_na)
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# plot_corr_df_na = my_gg_pairs(corr_df_na)
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cowplot::plot_grid(ggmatrix_gtable(plot_corr_df_ps),ggmatrix_gtable(plot_corr_df_cons),
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ggmatrix_gtable(plot_corr_df_lig),ggmatrix_gtable(plot_corr_df_ppi2),
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nrow=2, ncol=2, rel_heights = 7,7,3,3)
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