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
|
module OpenTox
# Nanoparticles
class Nanoparticle < Substance
include OpenTox
field :core_id, type: String, default: nil
field :coating_ids, type: Array, default: []
# Get core compound
# @return [OpenTox::Compound]
def core
Compound.find core_id
end
# Get coatings
# @return [Array<OpenTox::Compound>]
def coating
coating_ids.collect{|i| Compound.find i }
end
# Get nanoparticle fingerprint (union of core and coating fingerprints)
# @param [String] fingerprint type
# @return [Array<String>]
def fingerprint type=DEFAULT_FINGERPRINT
core_fp = core.fingerprint type
coating_fp = coating.collect{|c| c.fingerprint type}.flatten.uniq.compact
(core_fp.empty? or coating_fp.empty?) ? [] : (core_fp+coating_fp).uniq.compact
end
# Calculate physchem properties
# @param [Array<Hash>] list of descriptors
# @return [Array<Float>]
def calculate_properties descriptors=PhysChem::OPENBABEL
if core.smiles and !coating.collect{|c| c.smiles}.compact.empty?
core_prop = core.calculate_properties descriptors
coating_prop = coating.collect{|c| c.calculate_properties descriptors if c.smiles}
descriptors.collect_with_index{|d,i| [core_prop[i],coating_prop.collect{|c| c[i] if c}]}
end
end
# Add (measured) feature values
# @param [OpenTox::Feature]
# @param [TrueClass,FalseClass,Float]
# @param [OpenTox::Dataset]
def add_feature feature, value, dataset
unless feature.name == "ATOMIC COMPOSITION" or feature.name == "FUNCTIONAL GROUP" # redundand
case feature.category
when "P-CHEM"
properties[feature.id.to_s] ||= []
properties[feature.id.to_s] << value
properties[feature.id.to_s].uniq!
when "Proteomics"
properties[feature.id.to_s] ||= []
properties[feature.id.to_s] << value
properties[feature.id.to_s].uniq!
when "TOX"
if feature.name.match("Cell Viability Assay") and !feature.name.match("SLOPE") # -log10 transformation
value = -Math.log10(value)
feature.unit = "-log10(#{feature.unit})" unless feature.unit.match "log10"
feature.warnings += ["-log10 transformed values"] unless feature.warnings.include? "-log10 transformed values"
feature.save
end
dataset.add self, feature, value
else
warn "Unknown feature type '#{feature.category}'. Value '#{value}' not inserted."
end
dataset_ids << dataset.id
dataset_ids.uniq!
end
end
# Parse values from Ambit database
# @param [OpenTox::Feature]
# @param [TrueClass,FalseClass,Float]
# @param [OpenTox::Dataset]
def parse_ambit_value feature, v, dataset
# TODO add study id to warnings
v.delete "unit"
# TODO: ppm instead of weights
if v.keys == ["textValue"]
add_feature feature, v["textValue"], dataset
elsif v.keys == ["loValue"]
add_feature feature, v["loValue"], dataset
elsif v.keys.size == 2 and v["errorValue"]
add_feature feature, v["loValue"], dataset
#warn "Ignoring errorValue '#{v["errorValue"]}' for '#{feature.name}'."
elsif v.keys.size == 2 and v["loQualifier"] == "mean"
add_feature feature, v["loValue"], dataset
#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
#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
#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
#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
#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
elsif v == {} # do nothing
else
warn "Cannot parse Ambit eNanoMapper value '#{v}' for feature '#{feature.name}'."
end
end
end
end
|