diff --git a/Figures_manuscript/scripts/Fig_SUP17_BMI_pred_new_loci.R b/Figures_manuscript/scripts/Fig_SUP17_BMI_pred_new_loci.R index e291dbf5a035d663bbb33e9e90c1a137ff73a509..997a19ed5847e6d5a4dfed4d27ecb001b04992e7 100644 --- a/Figures_manuscript/scripts/Fig_SUP17_BMI_pred_new_loci.R +++ b/Figures_manuscript/scripts/Fig_SUP17_BMI_pred_new_loci.R @@ -2,8 +2,8 @@ library(data.table) library(plotROC) library(cowplot) -Berisa = fread("Y:\\5._ARTICLE_DISCOVERABILITY\\Figures\\inputs\\berisa_region.bed") -JASS_BMI = fread("Y:\\5._ARTICLE_DISCOVERABILITY\\Figures\\inputs\\BMIanalysis\\Evaluation_new_associations_BMI_with_allSNPs.tsv") +Berisa = fread("../inputs/berisa_region.bed") +JASS_BMI = fread("../inputs/BMIanalysis/Evaluation_new_associations_BMI_with_allSNPs.tsv") JASS_BMI = cbind(JASS_BMI,Berisa) JASS_BMI = JASS_BMI[!apply(is.na(JASS_BMI), 1, any),] @@ -41,7 +41,7 @@ p_ROC = p_ROC + annotate("text", y=rev(seq(0.45,0.6,0.05)) ,x=0.6, label=c("AUC" -png("Y:\\5._ARTICLE_DISCOVERABILITY\\Figures\\outputs\\Fig_SUP_BMI_pred_new_loci.png", +png("../outputs/Fig_SUP_BMI_pred_new_loci.png", width = 8, height = 8, units = "in", res = 300, pointsize = 4) diff --git a/Figures_manuscript/scripts/Fig_SUP2_residual_covariance.R b/Figures_manuscript/scripts/Fig_SUP2_residual_covariance.R index 6a19d0b7b8fd7ebd4bda93925c59e8ca20bc08ee..bc08222904236ef6a86b2a35762643e901bf3889 100644 --- a/Figures_manuscript/scripts/Fig_SUP2_residual_covariance.R +++ b/Figures_manuscript/scripts/Fig_SUP2_residual_covariance.R @@ -3,20 +3,20 @@ library(ggplot2) library(cowplot) library("stringr") -trait_72 = fread("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\inputs\\72trait_data_2023-07-07.csv") +trait_72 = fread("../inputs/72trait_data_2023-07-07.csv") #trait_72 = fread("V:\\5._ARTICLE_DISCOVERABILITY\\Tables\\Supp\\Output\\72trait_data_2023-07-07.csv") head(trait_72) trait_72 = trait_72[!is.na(trait_72[,`log10_mes_semilogadjust`]),] setkey(trait_72, "ID") -Rho = fread("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\inputs\\COV_H0.csv") +Rho = fread("../inputs/COV_H0.csv") setkey(Rho, "V1") Rho = Rho[trait_72$ID , c("V1",trait_72$ID), with=FALSE] res_dist = as.dist(1- Rho[trait_72$ID , trait_72$ID, with=FALSE]) res_dist[is.na(res_dist)] = 1 -Rho_gen = fread("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\inputs\\Correlation_matrix_genetic.csv") +Rho_gen = fread("../inputs/Correlation_matrix_genetic.csv") setkey(Rho_gen, "V1") Rho_gen = Rho_gen[trait_72$ID , c("V1",trait_72$ID), with=FALSE] gen_dist = as.dist(1- abs(Rho_gen[trait_72$ID, trait_72$ID, with=FALSE])) @@ -50,7 +50,7 @@ for(tr1 in 1:72){ } } -png("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\outputs\\Fig_sup_residual_covariance.png",width = 20, height = 20, +png("../outputs/Fig_sup_residual_covariance.png",width = 20, height = 20, units = "in", res = 300, pointsize = 4) diff --git a/Figures_manuscript/scripts/Fig_SUPnote3_stratification_illustration.R b/Figures_manuscript/scripts/Fig_SUPnote3_stratification_illustration.R index dca12ae706faad78f4182631655454f9de2f53c4..1502b7628bfe2bb9e0dd88947949abea807a60bb 100644 --- a/Figures_manuscript/scripts/Fig_SUPnote3_stratification_illustration.R +++ b/Figures_manuscript/scripts/Fig_SUPnote3_stratification_illustration.R @@ -31,6 +31,6 @@ p_distrib = p_distrib + geom_density(data=xuf, linewidth=1.1,aes(x=X)) +theme_mi p_distrib = p_distrib + scale_color_manual(name= "", label = c("Feature", "mean of the feature (random sets)", "mean of the feature (stratified sets)"),values=c("#E94F37", "#C0A04E", "#111D4A")) -png("Y:\\5._ARTICLE_DISCOVERABILITY\\Figures\\outputs\\Fig_SUPP_illustration_stratification.png", width=500, height=500) +png("../outputs/Fig_SUPP_illustration_stratification.png", width=500, height=500) p_distrib dev.off() diff --git a/Figures_manuscript/scripts/Fig_SUPnote4_simulation_test_boundaries.R b/Figures_manuscript/scripts/Fig_SUPnote4_simulation_test_boundaries.R index be198b18076f6acb1c4c921a8b93f29e546fb571..88b5fc0dcfc67bdd9f289330caa3bed9f4b147a3 100644 --- a/Figures_manuscript/scripts/Fig_SUPnote4_simulation_test_boundaries.R +++ b/Figures_manuscript/scripts/Fig_SUPnote4_simulation_test_boundaries.R @@ -102,7 +102,7 @@ for(hypothesis in names(BG_mat)){ rho_ov= cor(Y1, Y2) * overlap # cor(Y1,Y2)=rho (rho=pe+pg); overlap=NS/N (fraction of overlapping samples out of all samples) D = data.frame(matrix(c(Y1, Y2), ncol = 2)) - png(paste0("/pasteur/zeus/projets/p02/GGS_JASS/5._ARTICLE_DISCOVERABILITY/Figures/outputs/simulations/Phenotype_", hypothesis,"_ov_",overlap,".png")) + png(paste0("../outputs/simulations/Phenotype_", hypothesis,"_ov_",overlap,".png")) p = ggplot(D, aes(x=Y1, y=Y2)) + geom_point() print(p) dev.off() @@ -112,7 +112,7 @@ for(hypothesis in names(BG_mat)){ Beta_est = data.frame(B1 = Beta_estimate1, B2=Beta_estimate2) - png(paste0("/pasteur/zeus/projets/p02/GGS_JASS/5._ARTICLE_DISCOVERABILITY/Figures/outputs/simulations/Beta_", hypothesis,"_ov_",overlap,".png")) + png(paste0("../outputs/simulations/Beta_", hypothesis,"_ov_",overlap,".png")) print(ggplot(Beta_est, aes(x=B1, y=B2)) + geom_point()) dev.off() Z = Beta_est @@ -122,7 +122,7 @@ for(hypothesis in names(BG_mat)){ Z = as.data.frame(Z) names(Z) = c("z1", "z2") - png(paste0("/pasteur/zeus/projets/p02/GGS_JASS/5._ARTICLE_DISCOVERABILITY/Figures/outputs/simulations/Z_", hypothesis,"_ov_",overlap,".png")) + png(paste0("../outputs/simulations/Z_", hypothesis,"_ov_",overlap,".png")) print(ggplot(Z, aes(x=z1, y = z2)) + geom_point(alpha=0.5, size=1, color="blue")) dev.off() # @@ -151,15 +151,15 @@ for(hypothesis in names(BG_mat)){ range_z <- max(abs(Z$z1),abs(Z$z2)) - write.table(Z, paste0("/pasteur/zeus/projets/p02/GGS_JASS/5._ARTICLE_DISCOVERABILITY/Figures/outputs/simulations/Z_scores_", hypothesis, "_ov_", overlap,"_N_", N,"ce_",ce, ".csv"), sep="\t", row.names=TRUE) + write.table(Z, paste0("../outputs/simulations/Z_scores_", hypothesis, "_ov_", overlap,"_N_", N,"ce_",ce, ".csv"), sep="\t", row.names=TRUE) - png(paste0("/pasteur/zeus/projets/p02/GGS_JASS/5._ARTICLE_DISCOVERABILITY/Figures/outputs/simulations/", hypothesis, "_ov_", overlap,"_N_", N,"ce_",ce, ".png"), width=1500, height=1500, res=300) + png(paste0("../outputs/simulations/", hypothesis, "_ov_", overlap,"_N_", N,"ce_",ce, ".png"), width=1500, height=1500, res=300) p = ggplot(Z , id.var=c("z1", "z2"), aes(x=z1, y=z2, color=`Significance status`)) + geom_point(size=1.5) + scale_colour_manual(values = c("#3ba3ec","grey", "#f77189","#50b131")) + xlim(-range_z,range_z) + ylim(-range_z,range_z) print(p + theme_minimal()+ theme(legend.position = "top", panel.spacing = unit(1.5, "lines"), text=element_text(size=16)) + labs(color="Significance Status")) dev.off() simu = simu+1 } } - write.table(D_pval, paste0("/pasteur/zeus/projets/p02/GGS_JASS/5._ARTICLE_DISCOVERABILITY/Figures/outputs/simulations/", hypothesis, "_ov_", overlap,".csv"), sep="\t", row.names=TRUE) + write.table(D_pval, paste0("../outputs/simulations/", hypothesis, "_ov_", overlap,".csv"), sep="\t", row.names=TRUE) } } diff --git a/Figures_manuscript/scripts/Figure_2_feature_description_without_duplicates.R b/Figures_manuscript/scripts/Figure_2_feature_description_without_duplicates.R index 3d647e8a369a64f0dd4e46fe85dd6c92229c2abe..2512ec8b058580cc650bdaa072f2e53666becbf4 100644 --- a/Figures_manuscript/scripts/Figure_2_feature_description_without_duplicates.R +++ b/Figures_manuscript/scripts/Figure_2_feature_description_without_duplicates.R @@ -5,8 +5,7 @@ library(psych) library(latex2exp) library(scales) -trait_features = fread("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\inputs\\72trait_data_2023-07-07.csv") -#trait_features = fread("V:\\5._ARTICLE_DISCOVERABILITY\\Tables\\Supp\\Output\\72trait_data_2023-07-07.csv") +trait_features = fread("../inputs/72trait_data_2023-07-07.csv") head(trait_features) lm_pol_neff <- lm(log10(`polygenicity (unadjusted)`) ~ Neff,data=trait_features) @@ -78,7 +77,7 @@ pG = pG + theme(plot.margin = margin(0,0,0.1,0.1, "cm")) # set level features ################### -set_features = fread("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\inputs\\JASS_5CVdata-2023-08-01\\traitset_jass_5CVcombined_without_duplicates.tsv") +set_features = fread("../inputs/JASS_5CVdata-2023-08-01/traitset_jass_5CVcombined_without_duplicates.tsv") names(set_features) @@ -175,7 +174,7 @@ p_corr = p_corr + scale_x_discrete("Var1", labels=label_parse()) + scale_y_discr p_corr = p_corr + theme(plot.margin = margin(0,0,0.1,0.1, "cm"),axis.title.x=element_blank(), axis.title.y=element_blank()) -png("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\outputs\\fig2_feature_description.png",width = 13.5, height = 16, +png("../outputs/fig2_feature_description.png",width = 13.5, height = 16, units = "in", res = 600, pointsize = 4) diff --git a/Figures_manuscript/scripts/Figure_3_jass_gain_vs_features_descriptive_without_duplicates.R b/Figures_manuscript/scripts/Figure_3_jass_gain_vs_features_descriptive_without_duplicates.R index 9b31c7bd5e8df8af8e40e9bd13ca09c8bcce8522..1879e1f1c9ffdcc21a59d8c792b97366830b87ca 100644 --- a/Figures_manuscript/scripts/Figure_3_jass_gain_vs_features_descriptive_without_duplicates.R +++ b/Figures_manuscript/scripts/Figure_3_jass_gain_vs_features_descriptive_without_duplicates.R @@ -6,7 +6,7 @@ library(stringr) library(latex2exp) library(scales) -set_features = fread("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\inputs\\JASS_5CVdata-2023-08-01\\traitset_jass_5CVcombined_without_duplicates.tsv") +set_features = fread("../inputs/JASS_5CVdata-2023-08-01/traitset_jass_5CVcombined_without_duplicates.tsv") #../inputs/JASS_5CVdata-2023-08-01/traitset_jass_5CVcombined_without_duplicates.tsv") set_features[, percent_increase := 100*((Both+Univariate+Joint) / (Univariate+Both))] @@ -100,7 +100,7 @@ p_corr = p_corr + scale_x_discrete("Var1", labels=label_parse()) + scale_y_discr -png("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\outputs\\Fig_3_jass_association_gain_without_duplicates_2.png", width = 9, height = 4, +png("../outputs/Fig_3_jass_association_gain_without_duplicates_2.png", width = 9, height = 4, units = "in", res = 300, pointsize = 4) diff --git a/Figures_manuscript/scripts/Figure_5_SUP14_JASS_vs_MTAG_without_duplicates.R b/Figures_manuscript/scripts/Figure_5_SUP14_JASS_vs_MTAG_without_duplicates.R index 2f35c0133d8f26567395a20e86beae50c8176c10..723cf3cf30e7b6b89f07c99b23a0200cac76429b 100644 --- a/Figures_manuscript/scripts/Figure_5_SUP14_JASS_vs_MTAG_without_duplicates.R +++ b/Figures_manuscript/scripts/Figure_5_SUP14_JASS_vs_MTAG_without_duplicates.R @@ -17,8 +17,8 @@ library(cowplot) #JASS_res = rbindlist(CV_fold_JASS) #MTAG_res = rbindlist(CV_fold_MTAG) -JASS_res = fread("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\inputs\\JASS_5CVdata-2023-08-01\\traitset_jass_5CVcombined_without_duplicates.tsv") -MTAG_res = fread("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\inputs\\MTAG_5CVdata-2023-08-01\\traitset_mtag_5CVcombined_without_duplicates.tsv") +JASS_res = fread("../inputs/JASS_5CVdata-2023-08-01/traitset_jass_5CVcombined_without_duplicates.tsv") +MTAG_res = fread("../inputs/MTAG_5CVdata-2023-08-01/traitset_mtag_5CVcombined_without_duplicates.tsv") setkey(JASS_res, "Id") setkey(MTAG_res, "Id") @@ -73,11 +73,11 @@ p3 = ggplot(frac_JASS_better, aes(x= `# of traits`, y=`Fraction of set where #JA p3 = p3 + ylab("Fraction of set where #JASS >\n uncorrected #MTAG") + coord_flip() +theme_minimal() -png("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\outputs\\Figure_5_JASS_vs_MTAG_without_duplicates_HJ.png", width=10, height=5, unit="in", res=300) +png("../outputs/Figure_5_JASS_vs_MTAG_without_duplicates_HJ.png", width=10, height=5, unit="in", res=300) plot_grid(p1,NULL,p2,labels = c('A', "",'B'), rel_widths = c(6,0.1,4), nrow=1, ncol=3) dev.off() -png("V:\\5._ARTICLE_DISCOVERABILITY\\Figures\\outputs\\Figure_SUP_JASS_vs_uncorrected_MTAG_without_duplicates_HJ.png", width=10, height=5, unit="in", res=300) +png("../outputs/Figure_SUP_JASS_vs_uncorrected_MTAG_without_duplicates_HJ.png", width=10, height=5, unit="in", res=300) plot_grid(p1c,p3,labels = c('A', 'B'), rel_widths = c(6,4), nrow=1, ncol=2) dev.off()