isolating observeevent()s

This commit is contained in:
Tanushree Tunstall 2022-10-10 16:48:55 +01:00
parent 4cdcebb0b2
commit 615aa57d42

View file

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