1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
|
require_relative 'helper.rb'
include OpenTox
#require File.join(ENV["HOME"],".opentox","config","lazar-gui.rb") # until added to ot-tools
# DG: workaround for https://github.com/sinatra/sinatra/issues/808
# Date: 18/11/2013
#set :protection, :except => :path_traversal
configure :development do
$logger = Logger.new(STDOUT)
end
helpers do
class Numeric
def percent_of(n)
self.to_f / n.to_f * 100.0
end
end
end
get '/?' do
redirect to('/predict')
end
get '/predict/?' do
@models = OpenTox::Model::Prediction.all
@endpoints = @models.collect{|m| m.endpoint}.sort.uniq
@models.count <= 0 ? (haml :info) : (haml :predict)
end
get '/predict/modeldetails/:model' do
model = OpenTox::Model::Prediction.find params[:model]
return haml :model_details, :layout=> false, :locals => {:model => model}
end
get '/jme_help/?' do
File.read(File.join('views','jme_help.html'))
end
# get individual compound details
get '/prediction/:neighbor/details/?' do
@compound = OpenTox::Compound.new params[:neighbor]
@smiles = @compound.smiles
task = OpenTox::Task.run("Get names for '#{@smiles}'.") do
names = @compound.names
end
task.wait
case task[RDF::OT.hasStatus]
when "Error"
@names = "No names for this compound available."
when "Completed"
@names = @compound.names
else
@names = "No names for this compound available."
end
@inchi = @compound.inchi.gsub("InChI=", "")
haml :details, :layout => false
end
=begin
# sdf representation for datasets
#TODO fix 502 errors from compound service
get '/predict/:dataset_uri/sdf/?' do
uri = CGI.unescape(params[:dataset_uri])
$logger.debug uri
bad_request_error "Not a dataset uri." unless URI.dataset? uri
dataset = OpenTox::Dataset.find uri
@compounds = dataset.compounds
@data_entries = dataset.data_entries
sum=""
@compounds.each_with_index{ |c, idx|
sum << c.inchi
sum << c.sdf.sub(/\n\$\$\$\$/,'')
@data_entries[idx].each{ |f,v|
sum << "> <\"#{f}\">\n"
sum << v.join(", ")
sum << "\n\n"
}
sum << "$$$$\n"
}
send_file sum, :filename => "#{dataset.title}.sdf"
end
=end
# fingerprints for compound in predictions
get '/prediction/:model_uri/:type/:compound_uri/fingerprints/?' do
@type = params[:type]
model = OpenTox::Model::Lazar.find params[:model_uri]
feature_dataset = OpenTox::Dataset.find model[RDF::OT.featureDataset]
@compound = OpenTox::Compound.new params[:compound_uri]
@significant_fragments = []
if @type =~ /classification/i
# collect all feature values with fingerprint
fingerprints = OpenTox::Algorithm::Descriptor.send("smarts_match", [@compound], feature_dataset.features.collect{ |f| f[RDF::DC.title]})[@compound.uri]
#$logger.debug "fingerprints:\t#{fingerprints}\n"
# collect fingerprints with value 1
@fingerprint_values = fingerprints.collect{|smarts, value| [smarts, value] if value > 0}
# collect all features from feature_dataset
@features = feature_dataset.features.collect{|f| f }
# search for each fingerprint in all features and collect feature values( effect, smarts, pValue )
@fingerprint_values.each{ |fi, v| @features.each{ |f| @significant_fragments << [f[RDF::OT.effect].to_i, f[RDF::OT.smarts], f[RDF::OT.pValue]] if fi == f[RDF::OT.smarts] } }
# pass value_map, important to interprete effect value
prediction_feature_uri = ""
model.parameters.each {|p|
if p[RDF::DC.title].to_s == "prediction_feature_uri"
prediction_feature_uri = p[RDF::OT.paramValue].object
end
}
prediction_feature = OpenTox::Feature.find prediction_feature_uri
@value_map = prediction_feature.value_map
else #regression
feature_calc_algo = ""
model.parameters.each {|p|
if p[RDF::DC.title].to_s == "feature_calculation_algorithm"
feature_calc_algo = p[RDF::OT.paramValue].object
end
}
@desc = []
fingerprints = OpenTox::Algorithm::Descriptor.send( feature_calc_algo, [ @compound ], feature_dataset.features.collect{ |f| f[RDF::DC.title] } )
fingerprints.each{|x, h| h.each{|descriptor, value| @desc << [descriptor, [value]]}}
pc_descriptor_titles_descriptions = {}
feature_dataset.features.collect{ |f|
pc_descriptor_titles_descriptions[f[RDF::DC.title]]= f[RDF::DC.description]
}
@desc.each{|d, v| @significant_fragments << [pc_descriptor_titles_descriptions[d], v] }
end
haml :significant_fragments, :layout => false
end
get '/prediction/:model_uri/:type/:neighbor/significant_fragments/?' do
@type = params[:type]
@compound = OpenTox::Compound.new params[:neighbor]
model = OpenTox::Model::Lazar.find params[:model_uri]
#$logger.debug "model for significant fragments:\t#{model.uri}"
feature_dataset = OpenTox::Dataset.find model[RDF::OT.featureDataset]
$logger.debug "feature_dataset_uri:\t#{feature_dataset.uri}\n"
# load all compounds
feature_dataset.compounds
# load all features
@features = feature_dataset.features.collect{|f| f}
# find all features and values for a neighbor compound
@significant_fragments = []
# check type first
if @type =~ /classification/i
# get compound index in feature dataset
c_idx = feature_dataset.compound_indices @compound.uri
# collect feature uris with value
@feat = @features.collect{|f| [feature_dataset.data_entry_value(c_idx[0], f.uri), f.uri]}
#$logger.debug "@feat:\t#{@feat}\n"
# pass feature uris if value > 0
@feat.each do |f|
# search relevant features
if f[0] > 0
f = OpenTox::Feature.find f[1]
# pass relevant features with [ effect, smarts, pValue ]
@significant_fragments << [f[RDF::OT.effect].to_i, f[RDF::OT.smarts], f[RDF::OT.pValue].to_f.round(3)]
end
end
# pass value_map, important to interprete effect value
prediction_feature_uri = ""
model.parameters.each {|p|
if p[RDF::DC.title].to_s == "prediction_feature_uri"
prediction_feature_uri = p[RDF::OT.paramValue].object
end
}
prediction_feature = OpenTox::Feature.find prediction_feature_uri
@value_map = prediction_feature.value_map
else # regression
# find a value in feature dataset by compound and feature
@values = @features.collect{|f| feature_dataset.values(@compound, f)}
#$logger.debug "values in fd:\t#{@values}"
@features.each_with_index{|f, i| @significant_fragments << [f.description, @values[i]]}
end
#$logger.debug "significant fragments:\t#{@significant_fragments}\n"
haml :significant_fragments, :layout => false
end
get '/predict/?:csv?' do
response['Content-Type'] = "text/csv"
@csv = "\"Compound\",\"Endpoint\",\"Type\",\"Prediction\",\"Confidence\"\n"
@@batch.each do |key, values|
values.each do |array|
model = array[0]
prediction = array[1]
compound = key.smiles
endpoint = "#{model.endpoint.gsub('_', ' ')} (#{model.species})"
if prediction[:confidence] == "measured"
type = ""
pred = prediction[:value].numeric? ? "#{prediction[:value].round(3)} (#{model.unit})" : prediction[:value]
confidence = "measured activity"
elsif prediction[:neighbors].size > 0
type = model.model.class.to_s.match("Classification") ? "Classification" : "Regression"
pred = prediction[:value].numeric? ? "#{'%.2e' % prediction[:value]} #{model.unit}" : prediction[:value]
confidence = prediction[:confidence]
else
type = ""
pred = "Not enough similar compounds in training dataset."
confidence = ""
end
@csv += "\"#{compound}\",\"#{endpoint}\",\"#{type}\",\"#{pred}\",\"#{confidence}\"\n"
end
end
@csv
end
post '/predict/?' do
# process batch prediction
if !params[:fileselect].blank?
if params[:fileselect][:filename] !~ /\.csv$/
@error_report = "Please submit a csv file."
return haml :error
end
File.open('tmp/' + params[:fileselect][:filename], "w") do |f|
f.write(params[:fileselect][:tempfile].read)
end
@filename = params[:fileselect][:filename]
input = OpenTox::Dataset.from_csv_file File.join "tmp", params[:fileselect][:filename]
dataset = OpenTox::Dataset.find input.id
@compounds = dataset.compounds
if @compounds.size == 0
@error_report = "No valid SMILES submitted."
dataset.delete
return haml :error
end
@batch = {}
@compounds.each do |compound|
@batch[compound] = []
params[:selection].keys.each do |model_id|
model = Model::Prediction.find model_id
prediction = model.predict(compound)
@batch[compound] << [model, prediction]
end
end
@@batch = @batch
dataset.delete
return haml :batch
end
# validate identifier input
# transfered input
if !params[:identifier].blank?
@identifier = params[:identifier]
$logger.debug "input:#{@identifier}"
# get compound from SMILES
@compound = Compound.from_smiles @identifier
if @compound.blank?
@error_report = "Attention, '#{@identifier}' is not a valid SMILES string."
return haml :error
end
@models = []
@predictions = []
params[:selection].keys.each do |model_id|
model = Model::Prediction.find model_id
@models << model
@predictions << model.predict(@compound)
end
haml :prediction
end
end
get '/style.css' do
headers 'Content-Type' => 'text/css; charset=utf-8'
scss :style
end
|