diff --git a/bon_wilsonrnaseq_hsc.R b/bon_wilsonrnaseq_hsc.R index 877e0b7..fa2a508 100644 --- a/bon_wilsonrnaseq_hsc.R +++ b/bon_wilsonrnaseq_hsc.R @@ -2,9 +2,7 @@ library(BoolTraineR) library(doParallel) -#path='~/bool_final/' -#path='/home/cyl49/ownCloud/Research_Work/working_directory/boolean_project/res2/' -path='D:/ownCloud/Research_Work/working_directory/boolean_project/res2/' +path='~/bool_final/' setwd(path) #Setting up for parallel processing. diff --git a/gnw_bnlearn_btr_scoring.R b/gnw_bnlearn_btr_scoring.R index 7cb74ea..2cb8a3f 100644 --- a/gnw_bnlearn_btr_scoring.R +++ b/gnw_bnlearn_btr_scoring.R @@ -5,10 +5,7 @@ library(ggplot2) library(gridExtra) #for plotting multiple graphs library(reshape2) -#path='~/res1/' -#path='/home/cyl49/ownCloud/Research_Work/working_directory/boolean_project/res1/' -path='D:/ownCloud/Research_Work/working_directory/boolean_project/res1/' -#path='C:/Users/cyl49/ownCloud/Research_Work/working_directory/boolean_project/res1/' +path='~/res1/' setwd(path) inter_bool = T @@ -49,7 +46,6 @@ for(file_ind in 1:5) tmp_bngraph = empty.graph(colnames(test_data$bn_modamat[[i]][[j]])) amat(tmp_bngraph) = test_data$bn_modamat[[i]][[j]] tmp_score = score(tmp_bngraph, as.data.frame(test_data$cdata)) - #tmp_score = score(tmp_bngraph, as.data.frame(bm_cdata)) names(tmp_score) = test_data$bn_step[[i]][[j]] bnmod_gnw_bnscore = c(bnmod_gnw_bnscore, tmp_score) @@ -76,9 +72,7 @@ for(file_ind in 1:5) tmp_bmmodel = test_data$bm_modmodel[[i]][[j]] overlap_gene = unname(colnames(test_data$cdata)) tmp_bmmodel@target = overlap_gene - #tmp_score = calc_mscore(bmodel=tmp_bmmodel, istate=test_data$istate, fcdata=bm_cdata, overlap_gene=overlap_gene, max_varperrule=max_varperrule, steady_bool=F, distance_only=F) tmp_score = calc_mscore(bmodel=tmp_bmmodel, istate=test_data$istate, fcdata=fcdata, overlap_gene=overlap_gene, max_varperrule=max_varperrule, detail=T) - #tmp_score = calc_mscore(bmodel=tmp_bmmodel, istate=test_data$istate, fcdata=fddata, overlap_gene=overlap_gene, max_varperrule=max_varperrule, steady_bool=F, distance_only=F) names(tmp_score) = rep(j, length(tmp_score)) @@ -159,22 +153,6 @@ colnames(bmscore_mid_df) = c('steps', 'score', 'network', 'low', 'high') #Make plot objects of scoring functions. if(acyclic) { - p1_bn_box = ggplot(bnscore_df, aes(x=factor(bnscore_df[,'steps']), y=bnscore_df[,'score'])) + - geom_boxplot() + xlab('Number of different edges') + ylab('Scores') + ggtitle('BIC scoring function') + - scale_x_discrete(labels=unique(bnscore_df[,'steps'])) + - facet_wrap(~network, scales='free_y', ncol=1) + - theme(text = element_text(size=20), axis.text.x = element_text(size=10)) - - p2_bm_box = ggplot(bmscore_df, aes(x=factor(bmscore_df[,'steps']), y=bmscore_df[,'score'])) + - geom_boxplot() + xlab('Number of different edges') + ylab('Scores') + ggtitle('BSS scoring function') + - scale_x_discrete(labels=unique(bmscore_df[,'steps'])) + - facet_wrap(~network, scales='free_y', ncol=1) + - theme(text = element_text(size=20), axis.text.x = element_text(size=10)) - - png(paste('boolbaye', ifelse(acyclic, '_acyclic', '_cyclic'), ifelse(nonoise, '_nonoise', ''), '_boxplot_compare_score.png', sep=''), width=3000, height=5000, res=300) - grid.arrange(p1_bn_box, p2_bm_box, ncol=2) - dev.off() - p1_bn_mid = ggplot(bnscore_mid_df, aes(x=bnscore_mid_df[, 'steps'], y=bnscore_mid_df[,'score'])) + geom_errorbar(aes(ymin=bnscore_mid_df[, 'low'], ymax=bnscore_mid_df[, 'high'])) + geom_line() + xlab('Number of different edges') + ylab('Scores') + ggtitle('BIC scoring function') + @@ -192,16 +170,6 @@ if(acyclic) dev.off() } else { - p2_bm_box = ggplot(bmscore_df, aes(x=factor(bmscore_df[,'steps']), y=bmscore_df[,'score'])) + - geom_boxplot() + xlab('Number of different edges') + ylab('Scores') + ggtitle('BSS scoring function') + - scale_x_discrete(labels=unique(bmscore_df[,'steps'])) + - facet_wrap(~network, scales='free_y', ncol=1) + - theme(text = element_text(size=20), axis.text.x = element_text(size=10)) - - png(paste('boolbaye', ifelse(acyclic, '_acyclic', '_cyclic'), ifelse(nonoise, '_nonoise', ''), '_boxplot_compare_score.png', sep=''), width=3000, height=5000, res=300) - grid.arrange(p2_bm_box, ncol=2) - dev.off() - p2_bm_mid = ggplot(bmscore_mid_df, aes(x=bmscore_mid_df[, 'steps'], y=bmscore_mid_df[,'score'])) + geom_errorbar(aes(ymin=bmscore_mid_df[, 'low'], ymax=bmscore_mid_df[, 'high'])) + geom_line() + xlab('Number of different edges') + ylab('Scores') + ggtitle('BSS scoring function') + diff --git a/gnw_btr_model_inference.R b/gnw_btr_model_inference.R index f372f40..eac20ff 100644 --- a/gnw_btr_model_inference.R +++ b/gnw_btr_model_inference.R @@ -3,8 +3,6 @@ library(BoolTraineR) library(doParallel) path='~/bool_final/' -#path='/home/cyl49/ownCloud/Research_Work/working_directory/boolean_project/res1/' -#path='D:/ownCloud/Research_Work/working_directory/boolean_project/res1/' setwd(path) inter_bool = T diff --git a/gnw_comparison_network_inference.R b/gnw_comparison_network_inference.R index 18e4665..d2fab6d 100644 --- a/gnw_comparison_network_inference.R +++ b/gnw_comparison_network_inference.R @@ -12,9 +12,7 @@ acyclic = 'cyclic' #acyclic, cyclic, both # sect_1 ------------------------------------------------------------------ -#path='~/res1/' -path='/home/cyl49/ownCloud/Research_Work/working_directory/boolean_project/res1/' -#path='D:/ownCloud/Research_Work/working_directory/boolean_project/res1/' +path='~/res1/' setwd(path) if(acyclic=='acyclic') diff --git a/krum_wilson_grow_hsc.R b/krum_wilson_grow_hsc.R index 54ed521..5f1e1ca 100644 --- a/krum_wilson_grow_hsc.R +++ b/krum_wilson_grow_hsc.R @@ -2,9 +2,7 @@ library(BoolTraineR) library(doParallel) -#path='~/bool_final/' -#path='/home/cyl49/ownCloud/Research_Work/working_directory/boolean_project/res2/' -path='D:/ownCloud/Research_Work/working_directory/boolean_project/res2/' +path='~/bool_final/' setwd(path) #Setting up for parallel processing.