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
|
module OpenTox
class Nanoparticle < Substance
include OpenTox
field :core, type: String
field :coating, type: Array, default: []
field :bundles, type: Array, default: []
field :proteomics, type: Hash, default: {}
def nanoparticle_neighbors params
dataset = Dataset.find(params[:training_dataset_id])
Dataset.find(params[:training_dataset_id]).nanoparticles.collect do |np|
np["tanimoto"] = 1
np unless np.toxicities.empty?
end.compact
end
def add_feature feature, value, dataset_id
case feature.category
when "P-CHEM"
physchem_descriptors[feature.id.to_s] ||= []
physchem_descriptors[feature.id.to_s] << value
physchem_descriptors[feature.id.to_s].uniq!
when "Proteomics"
proteomics[feature.id.to_s] ||= []
proteomics[feature.id.to_s] << value
proteomics[feature.id.to_s].uniq!
when "TOX"
toxicities[feature.id.to_s] ||= {}
toxicities[feature.id.to_s][dataset_id.to_s] ||= []
# TODO generic way of parsing TOX values
if feature.name == "7.99 Toxicity (other) ICP-AES" and feature.unit == "mL/ug(Mg)"
toxicities[feature.id.to_s][dataset_id.to_s] << -Math.log10(value)
else
toxicities[feature.id.to_s][dataset_id.to_s] << value
end
toxicities[feature.id.to_s][dataset_id.to_s].uniq!
else
warn "Unknown feature type '#{feature.category}'. Value '#{value}' not inserted."
end
end
def parse_ambit_value feature, v, dataset_id
v.delete "unit"
# TODO: ppm instead of weights
if v.keys == ["textValue"]
add_feature feature, v["textValue"], dataset_id
elsif v.keys == ["loValue"]
add_feature feature, v["loValue"], dataset_id
elsif v.keys.size == 2 and v["errorValue"]
add_feature feature, v["loValue"], dataset_id
warn "Ignoring errorValue '#{v["errorValue"]}' for '#{feature.name}'."
elsif v.keys.size == 2 and v["loQualifier"] == "mean"
add_feature feature, v["loValue"], dataset_id
warn "'#{feature.name}' is a mean value. Original data is not available."
elsif v.keys.size == 2 and v["loQualifier"] #== ">="
warn "Only min value available for '#{feature.name}', entry ignored"
elsif v.keys.size == 2 and v["upQualifier"] #== ">="
warn "Only max value available for '#{feature.name}', entry ignored"
elsif v.keys.size == 3 and v["loValue"] and v["loQualifier"].nil? and v["upQualifier"].nil?
add_feature feature, v["loValue"], dataset_id
warn "loQualifier and upQualifier are empty."
elsif v.keys.size == 3 and v["loValue"] and v["loQualifier"] == "" and v["upQualifier"] == ""
add_feature feature, v["loValue"], dataset_id
warn "loQualifier and upQualifier are empty."
elsif v.keys.size == 4 and v["loValue"] and v["loQualifier"].nil? and v["upQualifier"].nil?
add_feature feature, v["loValue"], dataset_id
warn "loQualifier and upQualifier are empty."
elsif v.size == 4 and v["loQualifier"] and v["upQualifier"] and v["loValue"] and v["upValue"]
add_feature feature, [v["loValue"],v["upValue"]].mean, dataset_id
warn "Using mean value of range #{v["loValue"]} - #{v["upValue"]} for '#{feature.name}'. Original data is not available."
elsif v.size == 4 and v["loQualifier"] == "mean" and v["errorValue"]
warn "'#{feature.name}' is a mean value. Original data is not available. Ignoring errorValue '#{v["errorValue"]}' for '#{feature.name}'."
add_feature feature, v["loValue"], dataset_id
elsif v == {} # do nothing
else
warn "Cannot parse Ambit eNanoMapper value '#{v}' for feature '#{feature.name}'."
end
end
end
end
|
