105 lines
No EOL
4 KiB
R
105 lines
No EOL
4 KiB
R
function(input, output, session) {
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observeEvent(
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{
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input$display_position_full_range #special-purpose for MSA
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input$logoplot_colour_scheme
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input$switch_target
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},
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{
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# C O M P A T I B I L I T Y
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#gene=input$switch_target
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#drug=target_map[[gene]]
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merged_df3=cbind(get(paste0(input$switch_target, '_merged_df3')))
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position_max=max(merged_df3[['position']])
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position_min=min(merged_df3[['position']])
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min_ligand_distance=min(merged_df3$ligand_distance)
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max_ligand_distance=max(merged_df3$ligand_distance)
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# FIXME: these are IMPORTANT
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# # add "pos_count" position count column
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# merged_df3=merged_df3 %>% dplyr::add_count(position)
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# merged_df3$pos_count=merged_df3$n
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# merged_df3$n=NULL
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#
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mutable_df3 = cbind(merged_df3)
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unified_msa = get(paste0(input$switch_target, '_unified_msa'))
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#
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# # re-sort the dataframe according to position count
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sorted_df = cbind(merged_df3)
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sorted_df = sorted_df %>% arrange(pos_count)
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#
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outdir = paste0("~/git/Data/", drug, '/output/')
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indir = paste0("~/git/Data/", drug , "/input/")
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#
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# source("~/git/LSHTM_analysis/scripts/plotting/logo_data_msa.R") # probably unnecessary...
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# source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
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#### nasty special-purpose merged_df3 variants ####
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# FIXME: SLOW
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# corr_plotdf = corr_data_extract(
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# merged_df3
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# , gene = gene
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# , drug = drug
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# , extract_scaled_cols = F
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# )
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#input$stability_snp_param
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updateSliderInput(
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session,
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"display_position_range",
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min = position_min,
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max = position_max
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#, value = c(position_min, position_min+150)
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)
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updateSliderInput(
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session,
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"display_position_full_range",
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min = 1,
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max = position_max #,
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# value = c(position_min, position_min+150)
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)
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updateNumericInput(session, "selected_logop_snp_position", min = position_min, max = position_max, value = position_min)
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updateNumericInput(session, "selected_logop_ed_position", min = position_min, max = position_max, value = position_min)
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updateNumericInput(session, "corr_lig_dist", min = min_ligand_distance, max = max_ligand_distance, value = min_ligand_distance)
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stability_colname = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"stability_colname"]
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outcome_colname = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"outcome_colname"]
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display_position_range = input$display_position_range
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plot_min=display_position_range[1]
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plot_max=display_position_range[2]
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display_position_full_range = input$display_position_full_range
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full_range_min=display_position_full_range[1]
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full_range_max=display_position_full_range[2]
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logoplot_colour_scheme = input$logoplot_colour_scheme
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omit_snp_count = input$omit_snp_count
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print(paste0('Plotting positions between: ', plot_min, ' and ', plot_max))
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subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
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subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
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subset_sorted_df=sorted_df[(sorted_df$position>=plot_min & sorted_df$position <=plot_max),]
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#### LogoPlotMSA/Logo Plot ED ####
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output$LogoPlotMSA = renderPlot(
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LogoPlotMSA(target=input$switch_target,
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plot_positions=full_range_min:full_range_max,
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my_logo_col = logoplot_colour_scheme,
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aa_pos_drug = aa_pos_drug,
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active_aa_pos = active_aa_pos,
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aa_pos_lig1 = aa_pos_lig1,
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aa_pos_lig2 = aa_pos_lig2,
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aa_pos_lig3 = aa_pos_lig3
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)
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)
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}
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)
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} |