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isolating observeevent()s

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Tanushree Tunstall 2022-10-10 16:48:55 +01:00
parent 4cdcebb0b2
commit 615aa57d42
1 changed files with 421 additions and 421 deletions
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drug-target/global.R
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@ -651,425 +651,425 @@ if (interactive()){
), ),
) )
) )
server <- function(input, output, session) { # server <- function(input, output, session) {
#
#output$LogoPlotSnps = renderPlot(LogoPlotSnps(mutable_df3)) # #output$LogoPlotSnps = renderPlot(LogoPlotSnps(mutable_df3))
output$lin_sc = renderPlot( # output$lin_sc = renderPlot(
lin_sc( # lin_sc(
input$switch_target, # input$switch_target,
all_lineages = input$all_lineages, # all_lineages = input$all_lineages,
my_xats = 12, # x axis text size # my_xats = 12, # x axis text size
my_yats = 12, # y axis text size # my_yats = 12, # y axis text size
my_xals = 12, # x axis label size # my_xals = 12, # x axis label size
my_yals = 12, # y axis label size # my_yals = 12, # y axis label size
my_lls = 12, # legend label size # my_lls = 12, # legend label size
d_lab_size = 4 # d_lab_size = 4
) # )
) # )
#### lineage_distP #### # #### lineage_distP ####
output$lineage_distP = renderPlot( # output$lineage_distP = renderPlot(
lineage_distP( # lineage_distP(
get(paste0(input$switch_target, '_merged_df2')), # get(paste0(input$switch_target, '_merged_df2')),
all_lineages = input$all_lineages, # all_lineages = input$all_lineages,
x_lab = "Average Stability", # x_lab = "Average Stability",
x_axis = "avg_stability_scaled", # x_axis = "avg_stability_scaled",
fill_categ_cols = c("red", "blue") # fill_categ_cols = c("red", "blue")
) # )
) # )
#
#
#### observeEvent() Fun(tm) #### # #### observeEvent() Fun(tm) ####
observeEvent(input$clear_ngl, { # observeEvent(input$clear_ngl, {
NGLVieweR_proxy("structure") %>% # NGLVieweR_proxy("structure") %>%
removeSelection("Pos") # removeSelection("Pos")
}) # })
# Button to test adding a position # # Button to test adding a position
observeEvent(input$test_ngl, { # observeEvent(input$test_ngl, {
NGLVieweR_proxy("structure") %>% # NGLVieweR_proxy("structure") %>%
addSelection('ball+stick' # addSelection('ball+stick'
, param = list( # , param = list(
name = "Pos" # name = "Pos"
, sele = "35" # , sele = "35"
, color = "green") # , color = "green")
) # )
}) # })
#
observeEvent( # observeEvent(
{ # {
input$display_position_range # input$display_position_range
input$stability_snp_param # input$stability_snp_param
input$logoplot_colour_scheme # input$logoplot_colour_scheme
input$omit_snp_count # input$omit_snp_count
input$switch_target # input$switch_target
input$snp_ligand_dist # input$snp_ligand_dist
input$snp_nca_dist # input$snp_nca_dist
input$snp_interface_dist # input$snp_interface_dist
}, # },
{ # {
print("entering main observeEvent()") # print("entering main observeEvent()")
# C O M P A T I B I L I T Y # # C O M P A T I B I L I T Y
#gene=input$switch_target # #gene=input$switch_target
#drug=target_map[[gene]] # #drug=target_map[[gene]]
target_gene = input$switch_target # target_gene = input$switch_target
merged_df3 = cbind(get(paste0(input$switch_target, '_merged_df3'))) # merged_df3 = cbind(get(paste0(input$switch_target, '_merged_df3')))
#
position_max=max(merged_df3[['position']]) # position_max=max(merged_df3[['position']])
position_min=min(merged_df3[['position']]) # position_min=min(merged_df3[['position']])
min_ligand_distance=min(merged_df3$ligand_distance) # min_ligand_distance=min(merged_df3$ligand_distance)
max_ligand_distance=max(merged_df3$ligand_distance) # max_ligand_distance=max(merged_df3$ligand_distance)
# FIXME: these are IMPORTANT # # FIXME: these are IMPORTANT
# # add "pos_count" position count column # # # add "pos_count" position count column
# merged_df3=merged_df3 %>% dplyr::add_count(position) # # merged_df3=merged_df3 %>% dplyr::add_count(position)
# merged_df3$pos_count=merged_df3$n # # merged_df3$pos_count=merged_df3$n
# merged_df3$n=NULL # # merged_df3$n=NULL
# # #
mutable_df3 = cbind(merged_df3) # mutable_df3 = cbind(merged_df3)
# # #
# # re-sort the dataframe according to position count # # # re-sort the dataframe according to position count
sorted_df = cbind(merged_df3) # sorted_df = cbind(merged_df3)
sorted_df = sorted_df %>% arrange(pos_count) # sorted_df = sorted_df %>% arrange(pos_count)
#
# # #
outdir = paste0(load_dir, "Data/", drug, '/output/') # outdir = paste0(load_dir, "Data/", drug, '/output/')
indir = paste0(load_dir, "Data/", drug , "/input/") # indir = paste0(load_dir, "Data/", drug , "/input/")
#
#
#### nasty special-purpose merged_df3 variants #### # #### nasty special-purpose merged_df3 variants ####
# FIXME: SLOW # # FIXME: SLOW
# corr_plotdf = corr_data_extract( # # corr_plotdf = corr_data_extract(
# merged_df3 # # merged_df3
# , gene = gene # # , gene = gene
# , drug = drug # # , drug = drug
# , extract_scaled_cols = F # # , extract_scaled_cols = F
# ) # # )
#
#input$stability_snp_param # #input$stability_snp_param
#
updateCheckboxGroupInput( # updateCheckboxGroupInput(
session, # session,
"corr_selected", # "corr_selected",
choiceNames = colnames(get(paste0(input$switch_target,"_corr_df_m3_f"))), # choiceNames = colnames(get(paste0(input$switch_target,"_corr_df_m3_f"))),
choiceValues = colnames(get(paste0(input$switch_target,"_corr_df_m3_f"))), # choiceValues = colnames(get(paste0(input$switch_target,"_corr_df_m3_f"))),
selected = c("FoldX", "DeepDDG", "mCSM.DUET") # selected = c("FoldX", "DeepDDG", "mCSM.DUET")
) # )
#
updateSliderInput( # updateSliderInput(
session, # session,
"display_position_range", # "display_position_range",
min = position_min, # min = position_min,
max = position_max # max = position_max
#, value = c(position_min, position_min+150) # #, value = c(position_min, position_min+150)
) # )
#
updateNumericInput(session, "selected_logop_snp_position", min = position_min, max = position_max, value = position_min) # updateNumericInput(session, "selected_logop_snp_position", min = position_min, max = position_max, value = position_min)
updateNumericInput(session, "selected_logop_ed_position", min = position_min, max = position_max, value = position_min) # updateNumericInput(session, "selected_logop_ed_position", min = position_min, max = position_max, value = position_min)
updateNumericInput(session, "corr_lig_dist", min = min_ligand_distance, max = max_ligand_distance, value = min_ligand_distance) # updateNumericInput(session, "corr_lig_dist", min = min_ligand_distance, max = max_ligand_distance, value = min_ligand_distance)
#
updateNumericInput(session, "snp_ligand_dist", min = min(merged_df3$ligand_distance), max = max(merged_df3$ligand_distance)) # updateNumericInput(session, "snp_ligand_dist", min = min(merged_df3$ligand_distance), max = max(merged_df3$ligand_distance))
updateNumericInput(session, "snp_interface_dist", min = min(merged_df3$interface_dist), max = max(merged_df3$interface_dist)) # updateNumericInput(session, "snp_interface_dist", min = min(merged_df3$interface_dist), max = max(merged_df3$interface_dist))
updateNumericInput(session, "snp_nca_dist", min = min(merged_df3$nca_distance), max = max(merged_df3$nca_distance)) # updateNumericInput(session, "snp_nca_dist", min = min(merged_df3$nca_distance), max = max(merged_df3$nca_distance))
#
#
# different data ranges required for SNP distances # # different data ranges required for SNP distances
snp_ligand_dist_df3 = merged_df3[merged_df3[['ligand_distance']]<input$snp_ligand_dist,] # snp_ligand_dist_df3 = merged_df3[merged_df3[['ligand_distance']]<input$snp_ligand_dist,]
if ("interface_dist" %in% colnames(merged_df3)){ # if ("interface_dist" %in% colnames(merged_df3)){
snp_interface_dist_df3 = merged_df3[merged_df3[['interface_dist']]<input$snp_interface_dist,] # snp_interface_dist_df3 = merged_df3[merged_df3[['interface_dist']]<input$snp_interface_dist,]
} else { # } else {
snp_interface_dist_df3 = NULL # snp_interface_dist_df3 = NULL
} # }
#
if ("nca_distance" %in% colnames(merged_df3)){ # if ("nca_distance" %in% colnames(merged_df3)){
snp_nca_dist_df3 = merged_df3[merged_df3[['nca_distance']]<input$snp_nca_dist,] # snp_nca_dist_df3 = merged_df3[merged_df3[['nca_distance']]<input$snp_nca_dist,]
} else { # } else {
snp_nca_dist_df3 = NULL # snp_nca_dist_df3 = NULL
} # }
#
stability_colname = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"stability_colname"] # stability_colname = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"stability_colname"]
outcome_colname = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"outcome_colname"] # outcome_colname = stability_boxes_df[stability_boxes_df$stability_type==input$stability_snp_param,"outcome_colname"]
#
display_position_range = input$display_position_range # display_position_range = input$display_position_range
plot_min=display_position_range[1] # plot_min=display_position_range[1]
plot_max=display_position_range[2] # plot_max=display_position_range[2]
#
logoplot_colour_scheme = input$logoplot_colour_scheme # logoplot_colour_scheme = input$logoplot_colour_scheme
omit_snp_count = input$omit_snp_count # omit_snp_count = input$omit_snp_count
#
print(paste0('Plotting positions between: ', plot_min, ' and ', plot_max)) # print(paste0('Plotting positions between: ', plot_min, ' and ', plot_max))
#
subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),] # subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
#
subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),] # subset_mutable_df3=mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
subset_sorted_df=sorted_df[(sorted_df$position>=plot_min & sorted_df$position <=plot_max),] # subset_sorted_df=sorted_df[(sorted_df$position>=plot_min & sorted_df$position <=plot_max),]
#
#### LogoPlotSnps #### # #### LogoPlotSnps ####
output$LogoPlotSnps = renderPlot( # output$LogoPlotSnps = renderPlot(
LogoPlotSnps(subset_mutable_df3, # LogoPlotSnps(subset_mutable_df3,
aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")), # aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")),
active_aa_pos = get(paste0(target_gene,"_active_aa_pos")), # active_aa_pos = get(paste0(target_gene,"_active_aa_pos")),
aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")), # aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")),
aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")), # aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")),
aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3")), # aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3")),
my_logo_col = logoplot_colour_scheme, # my_logo_col = logoplot_colour_scheme,
omit_snp_count = omit_snp_count # omit_snp_count = omit_snp_count
#
) # )
) # )
#
### NGLViewer #### # ### NGLViewer ####
# Structure Viewer WebGL/NGLViewR window # # Structure Viewer WebGL/NGLViewR window
output$structure <- renderNGLVieweR({ # output$structure <- renderNGLVieweR({
#ngl_gene=isolate(input$switch_target) # #ngl_gene=isolate(input$switch_target)
ngl_gene=input$switch_target # ngl_gene=input$switch_target
ngl_drug=target_map[[ngl_gene]] # ngl_drug=target_map[[ngl_gene]]
ngl_pdb_file=paste0(load_dir, "Data/", ngl_drug, '/output/depth/', ngl_gene, '_complex.pdb') # ngl_pdb_file=paste0(load_dir, "Data/", ngl_drug, '/output/depth/', ngl_gene, '_complex.pdb')
print(ngl_pdb_file) # print(ngl_pdb_file)
NGLVieweR(ngl_pdb_file) %>% # NGLVieweR(ngl_pdb_file) %>%
addRepresentation("cartoon", # addRepresentation("cartoon",
param = list(name = "cartoon", # param = list(name = "cartoon",
color="tan" # color="tan"
#, colorScheme = "chainid" # #, colorScheme = "chainid"
) # )
) %>% # ) %>%
stageParameters(backgroundColor = "lightgrey") %>% # stageParameters(backgroundColor = "lightgrey") %>%
setQuality("high") %>% # setQuality("high") %>%
setFocus(0) %>% # setFocus(0) %>%
setSpin(FALSE) # setSpin(FALSE)
}) # })
#
#
#### Shared dataTable() #### # #### Shared dataTable() ####
output$table = DT::renderDataTable( # output$table = DT::renderDataTable(
datatable(subset_sorted_df[,table_columns], # datatable(subset_sorted_df[,table_columns],
filter="top", # filter="top",
selection = "single" # selection = "single"
) # )
) # )
#
#### bp_stability_hmap #### # #### bp_stability_hmap ####
# red/blue tiles wala "Stability SNP by Site" # # red/blue tiles wala "Stability SNP by Site"
output$bp_stability_hmap = renderPlot( # output$bp_stability_hmap = renderPlot(
bp_stability_hmap( # bp_stability_hmap(
subset_sorted_df, # subset_sorted_df,
reorder_position = input$reorder_custom_h, # reorder_position = input$reorder_custom_h,
p_title = NULL, # p_title = NULL,
yvar_colname = stability_colname, # yvar_colname = stability_colname,
stability_colname = stability_colname, # stability_colname = stability_colname,
stability_outcome_colname = outcome_colname, # stability_outcome_colname = outcome_colname,
my_ylab = NULL, # my_ylab = NULL,
y_max_override = max(sorted_df$pos_count), # y_max_override = max(sorted_df$pos_count),
aa_pos_drug = get(paste0("embb","_aa_pos_drug")), # aa_pos_drug = get(paste0("embb","_aa_pos_drug")),
active_aa_pos = get(paste0("embb","_active_aa_pos")), # active_aa_pos = get(paste0("embb","_active_aa_pos")),
aa_pos_lig1 = get(paste0("embb","_aa_pos_lig1")), # aa_pos_lig1 = get(paste0("embb","_aa_pos_lig1")),
aa_pos_lig2 = get(paste0("embb","_aa_pos_lig2")), # aa_pos_lig2 = get(paste0("embb","_aa_pos_lig2")),
aa_pos_lig3 = get(paste0("embb","_aa_pos_lig3")) # aa_pos_lig3 = get(paste0("embb","_aa_pos_lig3"))
) # )
) # )
#### LogoPlotCustomH #### # #### LogoPlotCustomH ####
output$LogoPlotCustomH = renderPlot( # output$LogoPlotCustomH = renderPlot(
LogoPlotCustomH( # LogoPlotCustomH(
subset_sorted_df, # subset_sorted_df,
my_logo_col = logoplot_colour_scheme, # my_logo_col = logoplot_colour_scheme,
aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")), # aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")),
active_aa_pos = get(paste0(target_gene,"_active_aa_pos")), # active_aa_pos = get(paste0(target_gene,"_active_aa_pos")),
aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")), # aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")),
aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")), # aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")),
aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3")) # aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3"))
) # )
) # )
#
#### wideP_consurf3 #### # #### wideP_consurf3 ####
output$wideP_consurf3 = renderPlot( # output$wideP_consurf3 = renderPlot(
wideP_consurf3( # wideP_consurf3(
subset_sorted_df, # subset_sorted_df,
point_colours = consurf_colours, # point_colours = consurf_colours,
aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")), # aa_pos_drug = get(paste0(target_gene,"_aa_pos_drug")),
active_aa_pos = get(paste0(target_gene,"_active_aa_pos")), # active_aa_pos = get(paste0(target_gene,"_active_aa_pos")),
aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")), # aa_pos_lig1 = get(paste0(target_gene,"_aa_pos_lig1")),
aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")), # aa_pos_lig2 = get(paste0(target_gene,"_aa_pos_lig2")),
aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3")) # aa_pos_lig3 = get(paste0(target_gene,"_aa_pos_lig3"))
) # )
) # )
#
#### site_snp_count_bp #### # #### site_snp_count_bp ####
#mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),] # #mutable_df3[(mutable_df3$position>=plot_min & mutable_df3$position <=plot_max),]
# ligand_distance # # ligand_distance
# interface_dist # # interface_dist
# nca_distance # # nca_distance
# change to: multiple plots, all use site_snp_count_bp # # change to: multiple plots, all use site_snp_count_bp
# 4 x plots side by side, one normal (no dist. filter), 2/3 filtered by distance columns above # # 4 x plots side by side, one normal (no dist. filter), 2/3 filtered by distance columns above
# use "subtitle text" from pos_count_bp_i.R # # use "subtitle text" from pos_count_bp_i.R
#
output$site_snp_count_bp = renderPlot( # output$site_snp_count_bp = renderPlot(
site_snp_count_bp( # site_snp_count_bp(
mutable_df3, # mutable_df3,
title_colour = 'black', # title_colour = 'black',
subtitle_colour = "black", # subtitle_colour = "black",
leg_text_size = 12, # leg_text_size = 12,
axis_label_size = 12, # axis_label_size = 12,
geom_ls = 4 # geom_ls = 4
) # )
) # )
output$site_snp_count_bp_ligand = renderPlot( # output$site_snp_count_bp_ligand = renderPlot(
site_snp_count_bp( # site_snp_count_bp(
snp_ligand_dist_df3, # snp_ligand_dist_df3,
title_colour = 'black', # title_colour = 'black',
subtitle_colour = "black", # subtitle_colour = "black",
leg_text_size = 12, # leg_text_size = 12,
axis_label_size = 12, # axis_label_size = 12,
geom_ls = 4 # geom_ls = 4
) # )
) # )
#
# if ("interface_dist" %in% colnames(input$switch_target)) { # # if ("interface_dist" %in% colnames(input$switch_target)) {
output$site_snp_count_interface = renderPlot( # output$site_snp_count_interface = renderPlot(
site_snp_count_bp( # site_snp_count_bp(
snp_interface_dist_df3, # snp_interface_dist_df3,
title_colour = 'black', # title_colour = 'black',
subtitle_colour = "black", # subtitle_colour = "black",
leg_text_size = 12, # leg_text_size = 12,
axis_label_size = 12, # axis_label_size = 12,
geom_ls = 4 # geom_ls = 4
) # )
) # )
# } #else { # # } #else {
# output$site_snp_count_interface = renderPlot( # # output$site_snp_count_interface = renderPlot(
# ggplot() + annotate(x=1,y=1,"text", label="No interface data for this target")+theme_void() # # ggplot() + annotate(x=1,y=1,"text", label="No interface data for this target")+theme_void()
# ) # # )
# } # # }
#
output$site_snp_count_nca = renderPlot( #{ # output$site_snp_count_nca = renderPlot( #{
#if ("nca_distance" %in% colnames(input$switch_target)) { # #if ("nca_distance" %in% colnames(input$switch_target)) {
site_snp_count_bp( # site_snp_count_bp(
snp_nca_dist_df3, # snp_nca_dist_df3,
title_colour = 'black', # title_colour = 'black',
subtitle_colour = "black", # subtitle_colour = "black",
leg_text_size = 12, # leg_text_size = 12,
axis_label_size = 12, # axis_label_size = 12,
geom_ls = 4 # geom_ls = 4
) # )
# } else { # # } else {
# ggplot() + annotate(x=1,y=1,"text", label="No RNA data for this target")+theme_void() # # ggplot() + annotate(x=1,y=1,"text", label="No RNA data for this target")+theme_void()
# } # # }
# } # # }
) # )
#
#
#
#### DM OM Plots #### # #### DM OM Plots ####
#dm_om_param # #dm_om_param
# order needs to be: # # order needs to be:
# embb_lf_duet, embb_lf_foldx, embb_lf_deepddg, embb_lf_dynamut2, embb_lf_dist_gen, # # embb_lf_duet, embb_lf_foldx, embb_lf_deepddg, embb_lf_dynamut2, embb_lf_dist_gen,
# embb_lf_consurf, embb_lf_provean, embb_lf_snap2, embb_lf_mcsm_lig, embb_lf_mmcsm_lig, # # embb_lf_consurf, embb_lf_provean, embb_lf_snap2, embb_lf_mcsm_lig, embb_lf_mmcsm_lig,
# embb_lf_mcsm_ppi2, SOMETHING NA # # embb_lf_mcsm_ppi2, SOMETHING NA
#
# embb_lf_mmcsm_lig SOMETHING NA, # # embb_lf_mmcsm_lig SOMETHING NA,
#dm_om_selection=input$dm_om_param # #dm_om_selection=input$dm_om_param
#dm_om_df = dm_om_map[[dm_om_selection]] # #dm_om_df = dm_om_map[[dm_om_selection]]
#output$lf_bp2 = renderPlot(lf_bp2(get(paste0(input$switch_target, '_', dm_om_df)))) # #output$lf_bp2 = renderPlot(lf_bp2(get(paste0(input$switch_target, '_', dm_om_df))))
#
output$lf_bp2 = renderPlot( # output$lf_bp2 = renderPlot(
cowplot::plot_grid( # cowplot::plot_grid(
plotlist = lapply( # plotlist = lapply(
ls(name=.GlobalEnv, # ls(name=.GlobalEnv,
pattern=paste0( # pattern=paste0(
target_gene, # target_gene,
'_lf_' # '_lf_'
) # )
), # ),
function(x){ # function(x){
lf_bp2(get(x)) # lf_bp2(get(x))
} # }
)#, nrow=3 # )#, nrow=3
), height=800 # ), height=800
) # )
} # }
) # )
#
#
# FIXME: Doesn't add selected table rows correctly # # FIXME: Doesn't add selected table rows correctly
observeEvent( # observeEvent(
{ # {
input$table_rows_selected # input$table_rows_selected
}, # },
{ # {
# having to duplicate this is a bit annoying :-( # # having to duplicate this is a bit annoying :-(
ngl_merged_df3=cbind(get(paste0(input$switch_target, '_merged_df3'))) # ngl_merged_df3=cbind(get(paste0(input$switch_target, '_merged_df3')))
ngl_sorted_df = cbind(ngl_merged_df3) # ngl_sorted_df = cbind(ngl_merged_df3)
ngl_sorted_df = ngl_sorted_df %>% arrange(pos_count) # ngl_sorted_df = ngl_sorted_df %>% arrange(pos_count)
#
position_max=max(ngl_merged_df3[['position']]) # position_max=max(ngl_merged_df3[['position']])
position_min=min(ngl_merged_df3[['position']]) # position_min=min(ngl_merged_df3[['position']])
display_position_range = input$display_position_range # display_position_range = input$display_position_range
plot_min=display_position_range[1] # plot_min=display_position_range[1]
plot_max=display_position_range[2] # plot_max=display_position_range[2]
#ngl_subset_df=ngl_merged_df3[(ngl_merged_df3$position>=plot_min & ngl_merged_df3$position <=plot_max),] # #ngl_subset_df=ngl_merged_df3[(ngl_merged_df3$position>=plot_min & ngl_merged_df3$position <=plot_max),]
ngl_subset_df=ngl_sorted_df[(ngl_sorted_df$position>=plot_min & ngl_sorted_df$position <=plot_max),] # ngl_subset_df=ngl_sorted_df[(ngl_sorted_df$position>=plot_min & ngl_sorted_df$position <=plot_max),]
#
#
#table_rows_selected = isolate(input$table_rows_selected) # #table_rows_selected = isolate(input$table_rows_selected)
table_rows_selected = input$table_rows_selected # table_rows_selected = input$table_rows_selected
class(table_rows_selected) # class(table_rows_selected)
#cat(paste0("Target: ", as.character(input$switch_target), "\nTable Rows for NGLViewR: ", as.character(table_rows_selected))) # #cat(paste0("Target: ", as.character(input$switch_target), "\nTable Rows for NGLViewR: ", as.character(table_rows_selected)))
#
struct_pos=(as.character(ngl_subset_df[table_rows_selected,"position"])) # struct_pos=(as.character(ngl_subset_df[table_rows_selected,"position"]))
cat(paste0('Table Index: ', table_rows_selected, "position: ", struct_pos)) # cat(paste0('Table Index: ', table_rows_selected, "position: ", struct_pos))
#
NGLVieweR_proxy("structure") %>% # NGLVieweR_proxy("structure") %>%
#addSelection('ball+stick' # #addSelection('ball+stick'
addSelection('hyperball' # addSelection('hyperball'
, param = list( # , param = list(
name = "Pos" # name = "Pos"
, sele = struct_pos # , sele = struct_pos
#, color = "#00ff00" # #, color = "#00ff00"
, colorValue="00ff00" # , colorValue="00ff00"
, colorScheme="element" # , colorScheme="element"
) # )
) # )
#cat(paste0('Done NGLViewR addSelection for: ', positions_to_add)) # #cat(paste0('Done NGLViewR addSelection for: ', positions_to_add))
} # }
) # )
#### Correlation observeEvent #### # #### Correlation observeEvent ####
# Yet another special-case observeEvent to handle the correlation pair plot # # Yet another special-case observeEvent to handle the correlation pair plot
#
observeEvent( # observeEvent(
{ # {
input$corr_selected # input$corr_selected
input$corr_method # input$corr_method
input$corr_lig_dist # input$corr_lig_dist
}, # },
{ # {
dist_cutoff_user = input$corr_lig_dist # dist_cutoff_user = input$corr_lig_dist
target_gene=input$switch_target # target_gene=input$switch_target
plot_title=paste0(target_map[[target_gene]],"/",target_gene) # plot_title=paste0(target_map[[target_gene]],"/",target_gene)
#
corr_plot_df = get( # corr_plot_df = get(
paste0( # paste0(
input$switch_target,"_corr_df_m3_f" # input$switch_target,"_corr_df_m3_f"
) # )
)[,c(input$corr_selected, "dst_mode")] # )[,c(input$corr_selected, "dst_mode")]
#
#if ( dist_cutoff_user >= 2) { # #if ( dist_cutoff_user >= 2) {
#corr_plotdf_subset = corr_plot_df[corr_plot_df[['Lig.Dist']] < dist_cutoff_user,] # #corr_plotdf_subset = corr_plot_df[corr_plot_df[['Lig.Dist']] < dist_cutoff_user,]
#} # #}
# else { # # else {
# corr_plotdf_subset = corr_plot_df # # corr_plotdf_subset = corr_plot_df
# } # # }
#
#### Correlation using ggpairs() #### # #### Correlation using ggpairs() ####
output$my_corr_pairs = renderPlot( # output$my_corr_pairs = renderPlot(
dashboard_ggpairs( # dashboard_ggpairs(
corr_plot_df, # corr_plot_df,
plot_title = plot_title, # plot_title = plot_title,
method = input$corr_method, # method = input$corr_method,
tt_args_size = 7, # tt_args_size = 7,
gp_args_size = 7 # gp_args_size = 7
), height = 900 # ), height = 900
) # )
} # }
) # )
} # }
#
#
app <- shinyApp(ui, server) # app <- shinyApp(ui, server)
runApp(app) # runApp(app)
} }