From d132e8441b8878861d0b2d0a4563b35387f0e3e9 Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Thu, 14 Jan 2016 14:52:25 +0100 Subject: initial import --- Gemfile | 2 + data/marina.json | 3282 ++++ data/multi-walled-nano-tubes.json | 430 + data/nanowiki.json | 30302 ++++++++++++++++++++++++++++++++++++ data/protein-corona.json | 20614 ++++++++++++++++++++++++ import.rb | 72 + lib/nano-lazar.rb | 1 + lib/nanoparticle.rb | 9 + nano-lazar.gemspec | 22 + 9 files changed, 54734 insertions(+) create mode 100644 Gemfile create mode 100644 data/marina.json create mode 100644 data/multi-walled-nano-tubes.json create mode 100644 data/nanowiki.json create mode 100644 data/protein-corona.json create mode 100644 import.rb create mode 100644 lib/nano-lazar.rb create mode 100644 lib/nanoparticle.rb create mode 100644 nano-lazar.gemspec diff --git a/Gemfile b/Gemfile new file mode 100644 index 0000000..1aa98e4 --- /dev/null +++ b/Gemfile @@ -0,0 +1,2 @@ +source "http://rubygems.org" +gemspec diff 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"URI":"https://apps.ideaconsult.net/enanomapper/dataset/Default", + "type":"Dataset" + }, + "annotation":[] + +}, +"https://apps.ideaconsult.net/enanomapper/feature/http%3A%2F%2Fwww.opentox.org%2Fapi%2F1.1%23CASRNDefault":{ + + "type":"Feature", + "title":"CasRN", + "units":"", + "isNominal":false, + "isNumeric":false, + "isMultiValue":false, + "sameAs":"http://www.opentox.org/api/1.1#CASRN", + "isModelPredictionFeature":false, + "creator":"http://ambit.sourceforge.net", + "order":0, + "source":{ + "URI":"https://apps.ideaconsult.net/enanomapper/dataset/Default", + "type":"Dataset" + }, + "annotation":[] + +}} +} diff --git a/import.rb b/import.rb new file mode 100644 index 0000000..b086a8c --- /dev/null +++ b/import.rb @@ -0,0 +1,72 @@ +require 'json' +require 'yaml' +require_relative "lib/nano-lazar.rb" +include OpenTox + +nanomaterials = [] +names = [] + +["nanowiki.json", "protein-corona.json", "marina.json"].each do |f| + JSON.parse(File.read(File.join("data",f)))["dataEntry"].each do |substance| + nm = Nanomaterial.new + nm.uri = substance["compound"]["URI"] + if substance["composition"] + nr_cores = substance["composition"].select{|c| c["relation"] == "HAS_CORE"}.size + puts "#{substance["compound"]["URI"]} has #{nr_cores} cores" if nr_cores !=1 + #component = substance["composition"]#["component"] + substance["composition"].each do |composition| + component = composition["component"] + if component + name = component["values"]["https://apps.ideaconsult.net/enanomapper/feature/http%3A%2F%2Fwww.opentox.org%2Fapi%2F1.1%23ChemicalNameDefault"] + names << name + if composition["relation"] == "HAS_CORE" + nm.core = name + elsif composition["relation"] == "HAS_COATING" + nm.coating ||= [] + nm.coating << name + end + else + #puts substance.to_yaml + end + end + else + #puts substance.to_yaml + end + substance["values"].each do |k,v| + property = nil + if k.match(/TOX/) + nm.tox ||= [] + property = "tox" + elsif k.match(/P-CHEM/) + nm.p_chem ||= [] + property = "p_chem" + end + if property + v.each do |val| + if val.keys == ["loValue"] + nm.tox << {k => val["loValue"]} if property == "tox" + nm.p_chem << {k => val["loValue"]} if property == "p_chem" + elsif val.keys == ["loQualifier", "loValue"] and val["loQualifier"] == "mean" + nm.tox << {k => val["loValue"]} if property == "tox" + nm.p_chem << {k => val["loValue"]} if property == "p_chem" + elsif val.keys == ["loQualifier", "loValue", "upQualifier", "upValue" ] + nm.tox << {k => (val["loValue"]+val["upValue"])/2} if property == "tox" + nm.p_chem << {k => (val["loValue"]+val["upValue"])/2} if property == "p_chem" + elsif val.keys == ["loQualifier", "loValue"] and val["loQualifier"] == ">=" + else + p val + end + end + else + #p k,v + end + end + nanomaterials << nm + end +end +puts "Total imported: #{nanomaterials.size}" +puts "With TOX data: #{nanomaterials.select{|n| n.tox}.size}" +puts "With nanoparticle characterisation: #{nanomaterials.select{|n| n.p_chem}.size}" +puts "With TOX data and particle characterisation: #{nanomaterials.select{|n| n.tox and n.p_chem}.size}" +#puts names.sort.uniq.to_yaml +#p nanomaterials.collect{|n| n.uri}.uniq.size diff --git a/lib/nano-lazar.rb b/lib/nano-lazar.rb new file mode 100644 index 0000000..718133c --- /dev/null +++ b/lib/nano-lazar.rb @@ -0,0 +1 @@ +Dir[File.join(File.dirname(__FILE__),"*")].each {|f| require_relative f} diff --git a/lib/nanoparticle.rb b/lib/nanoparticle.rb new file mode 100644 index 0000000..3a293ee --- /dev/null +++ b/lib/nanoparticle.rb @@ -0,0 +1,9 @@ +module OpenTox + + class Nanomaterial + include OpenTox + + attr_accessor :uri, :tox, :p_chem, :core, :coating + + end +end diff --git a/nano-lazar.gemspec b/nano-lazar.gemspec new file mode 100644 index 0000000..2e40218 --- /dev/null +++ b/nano-lazar.gemspec @@ -0,0 +1,22 @@ +# -*- encoding: utf-8 -*- +$:.push File.expand_path("../lib", __FILE__) + +Gem::Specification.new do |s| + s.name = "lazar" + s.version = File.read("./VERSION").strip + s.authors = ["Christoph Helma, Micha Rautenberg, David Vorgrimmler, Denis Gebele"] + s.email = ["helma@in-silico.ch"] + s.homepage = "http://github.com/opentox/nano-lazar" + s.summary = %q{Lazar nanotoxicity framework} + s.description = %q{Libraries for nanoparticle lazy structure-activity relationships and read-across.} + s.license = 'GPL-3' + + s.rubyforge_project = "lazar" + s.files = `git ls-files`.split("\n") + s.test_files = `git ls-files -- {test,spec,features}/*`.split("\n") + s.require_paths = ["lib"] + + # specify any dependencies here; for example: + s.add_runtime_dependency "bundler" + s.add_runtime_dependency "lazar" +end -- cgit v1.2.3 From e5b2f59ab602b2fb850a5338f5645ef331e0e66c Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Thu, 14 Jan 2016 17:41:43 +0100 Subject: endpoint counts --- import.rb | 54 +++++++++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 51 insertions(+), 3 deletions(-) diff --git a/import.rb b/import.rb index b086a8c..2a83b94 100644 --- a/import.rb +++ b/import.rb @@ -1,5 +1,6 @@ require 'json' require 'yaml' +#require_relative "../lazar/lib/lazar.rb" require_relative "lib/nano-lazar.rb" include OpenTox @@ -13,7 +14,6 @@ names = [] if substance["composition"] nr_cores = substance["composition"].select{|c| c["relation"] == "HAS_CORE"}.size puts "#{substance["compound"]["URI"]} has #{nr_cores} cores" if nr_cores !=1 - #component = substance["composition"]#["component"] substance["composition"].each do |composition| component = composition["component"] if component @@ -61,12 +61,60 @@ names = [] #p k,v end end + nm.tox.uniq! if nm.tox + nm.p_chem.uniq! if nm.p_chem nanomaterials << nm end end + puts "Total imported: #{nanomaterials.size}" -puts "With TOX data: #{nanomaterials.select{|n| n.tox}.size}" puts "With nanoparticle characterisation: #{nanomaterials.select{|n| n.p_chem}.size}" -puts "With TOX data and particle characterisation: #{nanomaterials.select{|n| n.tox and n.p_chem}.size}" +modelling_data = nanomaterials.select{|n| n.tox and n.p_chem} +puts "With TOX data: #{nanomaterials.select{|n| n.tox}.size}" +puts "With TOX data and particle characterisation: #{modelling_data.size}" +endpoints = modelling_data.collect{|n| n.tox.collect{|t| t.keys}}.flatten.compact.uniq +puts "Endpoints: #{endpoints.size}" + +single_value_endpoints = [] +endpoint_values = {} + +endpoints.each do |e| + #json = `curl -H "Accept:application/json" "#{e}" 2>/dev/null` + #f = JSON.parse(json)["feature"] + #p k unless f.keys.size == 1 + #k = f.keys.first + #p e + #p modelling_data.select{|n| n.tox.select{|t| t[e]}}.size + i = 0 + values = [] + modelling_data.each do |n| + n.tox.each do |t| + if t[e] + i += 1 + values << t[e] + end + end + end + single_value_endpoints << e if values.uniq.size == 1 + endpoint_values[e] = values.size unless values.uniq.size == 1 + #puts "#{f[k]['title']} [#{f[k]['units']}]: #{i} #{values}" +end + +endpoints -= single_value_endpoints +puts "Endpoints with more than one measurement value: #{endpoints.size}" +#endpoint_values.sort{|a,b| b[1] <=> a[1]} +endpoint_values.select!{|k,v| v > 10} +puts "Endpoints with more than 10 measurements: #{endpoint_values.size}" +endpoints = endpoint_values.keys +#puts endpoints.to_yaml +endpoint_values.sort{|a,b| b[1] <=> a[1]}.each do |e,v| + json = `curl -H "Accept:application/json" "#{e}" 2>/dev/null` + f = JSON.parse(json)["feature"] + p k unless f.keys.size == 1 + k = f.keys.first + p e + puts "#{f[k]['title']} [#{f[k]['units']}]: #{v} " +end +#puts "Endpoints with more than one value single_value_endpoints.size #puts names.sort.uniq.to_yaml #p nanomaterials.collect{|n| n.uri}.uniq.size -- cgit v1.2.3 From ff73a102a87d9e8e409ddf925f2e9477d60cafa7 Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Sat, 16 Jan 2016 14:35:53 +0100 Subject: features with unique values removed --- import.rb | 81 +++++++++++++++++++++++++++++++++++++---------------- lib/nanoparticle.rb | 4 +-- 2 files changed, 59 insertions(+), 26 deletions(-) diff --git a/import.rb b/import.rb index 2a83b94..63d8a08 100644 --- a/import.rb +++ b/import.rb @@ -1,16 +1,30 @@ +# TODO: missing data for protein corona silver particles require 'json' require 'yaml' -#require_relative "../lazar/lib/lazar.rb" +require 'csv' require_relative "lib/nano-lazar.rb" include OpenTox +def feature_name uri + f = @features[uri] + name = f['title'] + annotations = f['annotation'].collect{|a| "#{a['p']}: #{a['o']}"}.uniq.join ", " + name << " (#{annotations})" unless annotations.empty? + name << " [#{f['units']}]" if f['units'] and !f['units'].empty? + name +end + nanomaterials = [] -names = [] +feature_names = {} +@features = {} ["nanowiki.json", "protein-corona.json", "marina.json"].each do |f| - JSON.parse(File.read(File.join("data",f)))["dataEntry"].each do |substance| - nm = Nanomaterial.new + bundle = JSON.parse(File.read(File.join("data",f))) + @features.merge! bundle["feature"] + bundle["dataEntry"].each do |substance| + nm = Nanoparticle.new nm.uri = substance["compound"]["URI"] + nm.name = substance["values"]["https://apps.ideaconsult.net/enanomapper/identifier/name"] if substance["values"] if substance["composition"] nr_cores = substance["composition"].select{|c| c["relation"] == "HAS_CORE"}.size puts "#{substance["compound"]["URI"]} has #{nr_cores} cores" if nr_cores !=1 @@ -18,7 +32,7 @@ names = [] component = composition["component"] if component name = component["values"]["https://apps.ideaconsult.net/enanomapper/feature/http%3A%2F%2Fwww.opentox.org%2Fapi%2F1.1%23ChemicalNameDefault"] - names << name + #names << name if composition["relation"] == "HAS_CORE" nm.core = name elsif composition["relation"] == "HAS_COATING" @@ -73,18 +87,13 @@ modelling_data = nanomaterials.select{|n| n.tox and n.p_chem} puts "With TOX data: #{nanomaterials.select{|n| n.tox}.size}" puts "With TOX data and particle characterisation: #{modelling_data.size}" endpoints = modelling_data.collect{|n| n.tox.collect{|t| t.keys}}.flatten.compact.uniq +puts puts "Endpoints: #{endpoints.size}" single_value_endpoints = [] endpoint_values = {} endpoints.each do |e| - #json = `curl -H "Accept:application/json" "#{e}" 2>/dev/null` - #f = JSON.parse(json)["feature"] - #p k unless f.keys.size == 1 - #k = f.keys.first - #p e - #p modelling_data.select{|n| n.tox.select{|t| t[e]}}.size i = 0 values = [] modelling_data.each do |n| @@ -97,24 +106,48 @@ endpoints.each do |e| end single_value_endpoints << e if values.uniq.size == 1 endpoint_values[e] = values.size unless values.uniq.size == 1 - #puts "#{f[k]['title']} [#{f[k]['units']}]: #{i} #{values}" end endpoints -= single_value_endpoints puts "Endpoints with more than one measurement value: #{endpoints.size}" -#endpoint_values.sort{|a,b| b[1] <=> a[1]} endpoint_values.select!{|k,v| v > 10} puts "Endpoints with more than 10 measurements: #{endpoint_values.size}" endpoints = endpoint_values.keys -#puts endpoints.to_yaml -endpoint_values.sort{|a,b| b[1] <=> a[1]}.each do |e,v| - json = `curl -H "Accept:application/json" "#{e}" 2>/dev/null` - f = JSON.parse(json)["feature"] - p k unless f.keys.size == 1 - k = f.keys.first - p e - puts "#{f[k]['title']} [#{f[k]['units']}]: #{v} " +puts +puts endpoint_values.sort{|a,b| b[1] <=> a[1]}.collect{|e,v| "#{feature_names[e]}: #{v}"}.join("\n") + +endpoint = "https://apps.ideaconsult.net/enanomapper/property/TOX/UNKNOWN_TOXICITY_SECTION/Log2+transformed/94D664CFE4929A0F400A5AD8CA733B52E049A688/E/3ed642f9-1b42-387a-9966-dea5b91e5f8a" +nanomaterials.select!{|nm| nm.tox and nm.tox.collect{|t| t.keys}.flatten.include? endpoint} +p nanomaterials.size + +feature_values = {} +nanomaterials.each do |nm| + (nm.p_chem + nm.tox).each do |f| + feature_names[f] = feature_name f # avoid appending annotations/units with each function call, unclear why it happens + p f unless f.size == 1 + k = f.keys.first + unless f[k].is_a? String + feature_values[k] ||= [] + feature_values[k] << f[k] + end + end +end + +# remove empty values +feature_values.select!{|f,vals| vals.uniq.size > 2} +tox_descriptors = feature_values.select{|f,vals| f.match 'TOX'}.keys +p_chem_descriptors = feature_values.select{|f,vals| f.match 'P-CHEM'}.keys + +#puts @features.to_yaml + +column_names = ["Nanoparticle"] + p_chem_descriptors.collect{|d| feature_names[d]} + tox_descriptors.collect{|d| feature_names[d]} +table = [] +CSV.open(File.join(File.dirname(__FILE__),"data","protein_corona_extract.csv"),"w+") do |csv| + csv << column_names + nanomaterials.each do |nm| + if nm.tox and nm.tox.collect{|t| t.keys}.flatten.include? endpoint + #table << [] + csv << [nm.name] + p_chem_descriptors.collect{|p| nm.p_chem.collect{|pchem| pchem[p]}.compact.first} + tox_descriptors.collect{|p| nm.p_chem.collect{|pchem| pchem[p]}.compact.first} + end + end end -#puts "Endpoints with more than one value single_value_endpoints.size -#puts names.sort.uniq.to_yaml -#p nanomaterials.collect{|n| n.uri}.uniq.size diff --git a/lib/nanoparticle.rb b/lib/nanoparticle.rb index 3a293ee..0ec29a3 100644 --- a/lib/nanoparticle.rb +++ b/lib/nanoparticle.rb @@ -1,9 +1,9 @@ module OpenTox - class Nanomaterial + class Nanoparticle include OpenTox - attr_accessor :uri, :tox, :p_chem, :core, :coating + attr_accessor :name, :uri, :tox, :p_chem, :core, :coating end end -- cgit v1.2.3 From b90e598248489797456fee4c6661cfbe62b8e8ec Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Wed, 20 Jan 2016 12:41:33 +0100 Subject: Sinatra app skeleton --- .gitignore | 4 ++ Gemfile | 2 - application.rb | 21 ++++++++++ config.ru | 3 ++ data.json | 1 + protein_corona.rb | 118 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ 6 files changed, 147 insertions(+), 2 deletions(-) create mode 100644 .gitignore delete mode 100644 Gemfile create mode 100644 application.rb create mode 100644 config.ru create mode 100644 data.json create mode 100644 protein_corona.rb diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..59e48cf --- /dev/null +++ b/.gitignore @@ -0,0 +1,4 @@ +data +papers +*tmp +*swp diff --git a/Gemfile b/Gemfile deleted file mode 100644 index 1aa98e4..0000000 --- a/Gemfile +++ /dev/null @@ -1,2 +0,0 @@ -source "http://rubygems.org" -gemspec diff --git a/application.rb b/application.rb new file mode 100644 index 0000000..add7646 --- /dev/null +++ b/application.rb @@ -0,0 +1,21 @@ +require 'sinatra' +require "sinatra/reloader" if development? +require_relative 'protein_corona.rb' +also_reload './protein_corona.rb' + +get '/?' do + @data = JSON.parse(File.read("./data.json")).select{|id,features| features["composition"]["Core composition"] == '[Au]'} # Silver has too may missing values + @example = @data[@data.keys.sample]["physchem"] + content_type :json + JSON.pretty_generate(@example) +end + +get '/predict/?' do +end + +post '/predict/?' do + @features = params + @neighbors = neighbors params + @features[@endpoint_name] = prediction @neighbors + @prediction = predict params +end diff --git a/config.ru b/config.ru new file mode 100644 index 0000000..a09f5f7 --- /dev/null +++ b/config.ru @@ -0,0 +1,3 @@ +SERVICE = "nano-lazar" +require File.expand_path './application.rb' +run Sinatra::Application diff --git a/data.json b/data.json new file mode 100644 index 0000000..1b0658f --- /dev/null +++ b/data.json @@ -0,0 +1 @@ +{"G15.AC":{"composition":{"Core composition":"[Au]","Surface modifier1":"N-Acetyl-L-cysteine","Surface modifier2":null,"Classification":"Anionic"},"tox":{"Cell.association (Net cell association [mL/ug(Mg)])":0.02751,"Cell.association (Log2 transformed)":-5.184},"physchem":{"Core size [nm]":14.9,"Density [g/cm^3]":19.1,"MW [g/mol]":197.0,"Z-Average Hydrodynamic Diameter [nm]":22.36,"Z-Average Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":57.53,"Z-Average Hydrodynamic Diameter Change":35.1667,"Volume Mean Hydrodynamic Diameter [nm]":21.94,"Volume Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":21.75,"Volume Mean Hydrodynamic Diameter Change":-0.1854,"Number Mean Hydrodynamic Diameter [nm]":23.49,"Number Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":18.38,"Number Mean Hydrodynamic Diameter Change":-5.117,"Intensity Mean Hydrodynamic Diameter [nm]":23.49,"Intensity Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":70.97,"Intensity Mean Hydrodynamic Diameter Change":47.4778,"Polydispersity index [nm]":0.084,"Polydispersity index Human serum (Sigma #H4522) [nm]":0.27,"Polydispersity index Change":0.1867,"ZETA POTENTIAL [mV]":-21.78,"ZETA POTENTIAL Human serum (Sigma #H4522) [mV]":-9.11,"ZETA POTENTIAL Change":12.6717,"Localized Surface Plasmon Resonance (LSPR) index":0.182530253,"Localized Surface Plasmon Resonance (LSPR) index Human serum (Sigma #H4522)":0.454404195,"Localized Surface Plasmon Resonance (LSPR) index Change":0.2719,"LSPR peak position (nm) [nm]":518.77,"Total protein (BCA assay) Human serum (Sigma #H4522) [ug]":2.927,"Autot (ICP-AES) Human serum (Sigma #H4522) [nmol]":255.4430266,"Total surface area (SAtot) Human serum (Sigma #H4522) [cm^2]":11.0,"Protein density Human serum (Sigma #H4522) Mean [ug/cm^2]":0.0,"Protein density Human serum (Sigma #H4522) SEM [ug/cm^2]":0.026465833}},"G15.AHT":{"composition":{"Core composition":"[Au]","Surface modifier1":"6-Amino-1-hexanethiol","Surface modifier2":null,"Classification":"Cationic"},"tox":{"Cell.association (Net cell association [mL/ug(Mg)])":0.49705,"Cell.association (Log2 transformed)":-1.009},"physchem":{"Core size [nm]":14.9,"Density [g/cm^3]":19.1,"MW [g/mol]":197.0,"Z-Average Hydrodynamic Diameter [nm]":30.95,"Z-Average Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":90.06,"Z-Average Hydrodynamic Diameter Change":59.1089,"Volume Mean Hydrodynamic Diameter [nm]":11.76,"Volume Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":67.79,"Volume Mean Hydrodynamic Diameter Change":56.032,"Number Mean Hydrodynamic Diameter [nm]":47.5,"Number Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":53.87,"Number Mean Hydrodynamic Diameter Change":6.3667,"Intensity Mean Hydrodynamic Diameter [nm]":47.5,"Intensity Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":106.7,"Intensity Mean Hydrodynamic Diameter Change":59.2033,"Polydispersity index [nm]":0.399,"Polydispersity index Human serum (Sigma #H4522) [nm]":0.215,"Polydispersity index Change":-0.1837,"ZETA POTENTIAL [mV]":15.22,"ZETA POTENTIAL Human serum (Sigma #H4522) [mV]":-8.79,"ZETA POTENTIAL Change":-24.005,"Localized Surface Plasmon Resonance (LSPR) index":0.458209658,"Localized Surface Plasmon Resonance (LSPR) index Human serum (Sigma #H4522)":0.525747071,"Localized Surface Plasmon Resonance (LSPR) index Change":0.0675,"LSPR peak position (nm) [nm]":526.28,"Total protein (BCA assay) Human serum (Sigma #H4522) [ug]":4.602,"Autot (ICP-AES) Human serum (Sigma #H4522) [nmol]":240.7287996,"Total surface area (SAtot) 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(ICP-AES) Human serum (Sigma #H4522) [nmol]":688.4761522,"Total surface area (SAtot) Human serum (Sigma #H4522) [cm^2]":11.0,"Protein density Human serum (Sigma #H4522) Mean [ug/cm^2]":0.0,"Protein density Human serum (Sigma #H4522) SEM [ug/cm^2]":0.005647305}},"S40.MUTA":{"composition":{"Core composition":"[Ag]","Surface modifier1":"(11-Mercaptoundecyl)-N,N,N-trimethylammonium","Surface modifier2":null,"Classification":"Cationic"},"tox":{"Cell.association (Net cell association [mL/ug(Mg)])":0.73653,"Cell.association (Log2 transformed)":-0.441},"physchem":{"Core size [nm]":38.4,"Density [g/cm^3]":10.5,"MW [g/mol]":108.0,"Z-Average Hydrodynamic Diameter [nm]":null,"Z-Average Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Z-Average Hydrodynamic Diameter Change":null,"Volume Mean Hydrodynamic Diameter [nm]":null,"Volume Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Volume Mean Hydrodynamic Diameter Change":null,"Number Mean Hydrodynamic Diameter [nm]":null,"Number Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Number Mean Hydrodynamic Diameter Change":null,"Intensity Mean Hydrodynamic Diameter [nm]":null,"Intensity Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Intensity Mean Hydrodynamic Diameter Change":null,"Polydispersity index [nm]":null,"Polydispersity index Human serum (Sigma #H4522) [nm]":null,"Polydispersity index Change":null,"ZETA POTENTIAL [mV]":null,"ZETA POTENTIAL Human serum (Sigma #H4522) [mV]":null,"ZETA POTENTIAL Change":null,"Localized Surface Plasmon Resonance (LSPR) index":null,"Localized Surface Plasmon Resonance (LSPR) index Human serum (Sigma #H4522)":null,"Localized Surface Plasmon Resonance (LSPR) index Change":null,"LSPR peak position (nm) [nm]":null,"Total protein (BCA assay) Human serum (Sigma #H4522) [ug]":2.1,"Autot (ICP-AES) Human serum (Sigma #H4522) [nmol]":747.9733811,"Total surface area (SAtot) Human serum (Sigma #H4522) [cm^2]":12.0,"Protein density 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Hydrodynamic Diameter [nm]":null,"Intensity Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Intensity Mean Hydrodynamic Diameter Change":null,"Polydispersity index [nm]":null,"Polydispersity index Human serum (Sigma #H4522) [nm]":null,"Polydispersity index Change":null,"ZETA POTENTIAL [mV]":null,"ZETA POTENTIAL Human serum (Sigma #H4522) [mV]":null,"ZETA POTENTIAL Change":null,"Localized Surface Plasmon Resonance (LSPR) index":null,"Localized Surface Plasmon Resonance (LSPR) index Human serum (Sigma #H4522)":null,"Localized Surface Plasmon Resonance (LSPR) index Change":null,"LSPR peak position (nm) [nm]":null,"Total protein (BCA assay) Human serum (Sigma #H4522) [ug]":0.4,"Autot (ICP-AES) Human serum (Sigma #H4522) [nmol]":689.2859255,"Total surface area (SAtot) Human serum (Sigma #H4522) [cm^2]":11.0,"Protein density Human serum (Sigma #H4522) Mean [ug/cm^2]":0.0,"Protein density Human serum (Sigma #H4522) SEM [ug/cm^2]":0.007516076}},"S40.PLL-SH":{"composition":{"Core composition":"[Ag]","Surface modifier1":"Thiolated poly(L-lysine)","Surface modifier2":null,"Classification":"Cationic"},"tox":{"Cell.association (Net cell association [mL/ug(Mg)])":0.94668,"Cell.association (Log2 transformed)":-0.079},"physchem":{"Core size [nm]":38.4,"Density [g/cm^3]":10.5,"MW [g/mol]":108.0,"Z-Average Hydrodynamic Diameter [nm]":null,"Z-Average Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Z-Average Hydrodynamic Diameter Change":null,"Volume Mean Hydrodynamic Diameter [nm]":null,"Volume Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Volume Mean Hydrodynamic Diameter Change":null,"Number Mean Hydrodynamic Diameter [nm]":null,"Number Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Number Mean Hydrodynamic Diameter Change":null,"Intensity Mean Hydrodynamic Diameter [nm]":null,"Intensity Mean Hydrodynamic Diameter Human serum (Sigma #H4522) 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modifier2":null,"Classification":"Neutral"},"tox":{"Cell.association (Net cell association [mL/ug(Mg)])":0.12559,"Cell.association (Log2 transformed)":-2.993},"physchem":{"Core size [nm]":38.4,"Density [g/cm^3]":10.5,"MW [g/mol]":108.0,"Z-Average Hydrodynamic Diameter [nm]":null,"Z-Average Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Z-Average Hydrodynamic Diameter Change":null,"Volume Mean Hydrodynamic Diameter [nm]":null,"Volume Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Volume Mean Hydrodynamic Diameter Change":null,"Number Mean Hydrodynamic Diameter [nm]":null,"Number Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Number Mean Hydrodynamic Diameter Change":null,"Intensity Mean Hydrodynamic Diameter [nm]":null,"Intensity Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Intensity Mean Hydrodynamic Diameter Change":null,"Polydispersity index [nm]":null,"Polydispersity index Human serum (Sigma #H4522) [nm]":null,"Polydispersity index Change":null,"ZETA POTENTIAL [mV]":null,"ZETA POTENTIAL Human serum (Sigma #H4522) [mV]":null,"ZETA POTENTIAL Change":null,"Localized Surface Plasmon Resonance (LSPR) index":null,"Localized Surface Plasmon Resonance (LSPR) index Human serum (Sigma #H4522)":null,"Localized Surface Plasmon Resonance (LSPR) index Change":null,"LSPR peak position (nm) [nm]":null,"Total protein (BCA assay) Human serum (Sigma #H4522) [ug]":2.34,"Autot (ICP-AES) Human serum (Sigma #H4522) [nmol]":630.4443636,"Total surface area (SAtot) Human serum (Sigma #H4522) [cm^2]":10.0,"Protein density Human serum (Sigma #H4522) Mean [ug/cm^2]":0.0,"Protein density Human serum (Sigma #H4522) SEM [ug/cm^2]":0.014004945}},"S40.SA":{"composition":{"Core composition":"[Ag]","Surface modifier1":"Stearic acid","Surface modifier2":null,"Classification":"Anionic"},"tox":{"Cell.association (Net cell association [mL/ug(Mg)])":0.13245,"Cell.association (Log2 transformed)":-2.916},"physchem":{"Core size [nm]":38.4,"Density [g/cm^3]":10.5,"MW [g/mol]":108.0,"Z-Average Hydrodynamic Diameter [nm]":null,"Z-Average Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Z-Average Hydrodynamic Diameter Change":null,"Volume Mean Hydrodynamic Diameter [nm]":null,"Volume Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Volume Mean Hydrodynamic Diameter Change":null,"Number Mean Hydrodynamic Diameter [nm]":null,"Number Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Number Mean Hydrodynamic Diameter Change":null,"Intensity Mean Hydrodynamic Diameter [nm]":null,"Intensity Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":null,"Intensity Mean Hydrodynamic Diameter Change":null,"Polydispersity index [nm]":null,"Polydispersity index Human serum (Sigma #H4522) [nm]":null,"Polydispersity index Change":null,"ZETA POTENTIAL [mV]":null,"ZETA POTENTIAL Human serum (Sigma #H4522) [mV]":null,"ZETA POTENTIAL Change":null,"Localized Surface Plasmon Resonance (LSPR) index":null,"Localized Surface Plasmon Resonance (LSPR) index Human serum (Sigma #H4522)":null,"Localized Surface Plasmon Resonance (LSPR) index Change":null,"LSPR peak position (nm) [nm]":null,"Total protein (BCA assay) Human serum (Sigma #H4522) [ug]":1.18,"Autot (ICP-AES) Human serum (Sigma #H4522) [nmol]":653.5183257,"Total surface area (SAtot) Human serum (Sigma #H4522) [cm^2]":11.0,"Protein density Human serum (Sigma #H4522) Mean [ug/cm^2]":0.0,"Protein density Human serum (Sigma #H4522) SEM [ug/cm^2]":0.013965863}}} diff --git a/protein_corona.rb b/protein_corona.rb new file mode 100644 index 0000000..35970dc --- /dev/null +++ b/protein_corona.rb @@ -0,0 +1,118 @@ +require 'json' +require 'yaml' +require 'csv' +#require_relative "../lazar/lib/lazar.rb" +#include OpenTox + +class Object + def numeric? + true if Float(self) rescue false + end +end + +def euclidean_distance(a, b) + sq = a.zip(b).map{|a,b| (a - b) ** 2} + Math.sqrt(sq.inject(0) {|s,c| s + c}) +end + +def dot_product(a, b) + products = a.zip(b).map{|a, b| a * b} + products.inject(0) {|s,p| s + p} +end + +def magnitude(point) + squares = point.map{|x| x ** 2} + Math.sqrt(squares.inject(0) {|s, c| s + c}) +end + +def cosine_similarity(a, b) + dot_product(a, b) / (magnitude(a) * magnitude(b)) +end + +#@endpoint = @data.collect{|r| r[5]} + +def neighbors query +end + +def csv2json + csv = CSV.read("data/MergedSheets_edit.csv") + csv.collect!{|row| row[0..36].collect{|c| c.numeric? ? c.to_f : c } }.compact + feature_names = [ + "ID", + csv[0][1], + csv[0][2], + csv[0][3], + csv[6][4], + "#{csv[0][5]} (#{csv[6][5]} [#{csv[11][5]}])", # endpoint + "#{csv[0][6]} (#{csv[6][6]})", # endpoint + "#{csv[6][7]} [#{csv[11][7]}]", + "#{csv[6][8]} [#{csv[11][8]}]", + "#{csv[6][9]} [#{csv[11][9]}]", + ] + (10..10+5*3).step(3) do |i| + feature_names += [ + "#{csv[6][i]} [#{csv[11][i]}]", + "#{csv[6][i+1]} #{csv[8][i+1]} [#{csv[11][i+1]}]", + "#{csv[6][i+2]} #{csv[8][i+2]}", + ] + end + feature_names += [ + "#{csv[6][28]}", + "#{csv[6][29]} #{csv[8][29]}", + "#{csv[6][30]} #{csv[8][30]}", + ] + (31..34).each do |i| + feature_names << "#{csv[6][i]} #{csv[8][i]} [#{csv[11][i]}]" + end + (35..36).each do |i| + feature_names << "#{csv[6][i]} #{csv[8][i]} #{csv[10][i]} [#{csv[11][i]}]" + end + data = {} + csv.drop(12).each do |row| + id = row.first + data[id] = {} + row.each_with_index do |col,i| + if i == 0 + data[id][:composition] = {} + elsif i < 5 + data[id][:composition][feature_names[i]] = col + elsif i < 7 + data[id][:tox] ||= {} + data[id][:tox][feature_names[i]] = col + else + data[id][:physchem] ||= {} + data[id][:physchem][feature_names[i]] = col + end + end + end + File.open("data.json","w+"){|f| f.puts data.to_json} + data +end + +#puts data.to_yaml +=begin +R.assign "endpoint", endpoint +(0..data[0].size).each do |c| + if data.collect{|r| r[c]}.uniq.size > 1 + begin + R.assign "feature", data.collect{|r| r[c]} + R.eval "r <- cor(-log(endpoint),-log(feature),use='complete')" + r = R.eval("r").to_ruby + p "#{c}: #{r}" if r > 0.3 or r < -0.3 + rescue + end + end +end + + +csv[0..13].each do |row| + row.each_with_index do |col,i| + features[i] = features[i].to_s+", "+col.to_s + end +end + +puts features.select{|f| f.match(/Mean/)}.to_yaml + + #n+=1 + #p n,row.first unless row.first.match /^[G|S]/ +=end -- cgit v1.2.3 From a63e80ccfd1c6747169e79ab610d719435be8557 Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Wed, 20 Jan 2016 13:43:15 +0100 Subject: Sinatra app skeleton with predictions --- application.rb | 20 +++++++++---------- data.json | 2 +- protein_corona.rb | 57 +++++++++++++++++++++++++++++++++++++++++-------------- 3 files changed, 54 insertions(+), 25 deletions(-) diff --git a/application.rb b/application.rb index add7646..1cb0e13 100644 --- a/application.rb +++ b/application.rb @@ -4,18 +4,18 @@ require_relative 'protein_corona.rb' also_reload './protein_corona.rb' get '/?' do - @data = JSON.parse(File.read("./data.json")).select{|id,features| features["composition"]["Core composition"] == '[Au]'} # Silver has too may missing values + @data = JSON.parse(File.read("./data.json")) @example = @data[@data.keys.sample]["physchem"] - content_type :json - JSON.pretty_generate(@example) + # create a data entry form with @example as default values + #content_type :json + #JSON.pretty_generate(@example) end -get '/predict/?' do -end - -post '/predict/?' do - @features = params - @neighbors = neighbors params - @features[@endpoint_name] = prediction @neighbors +post '/?' do @prediction = predict params + # display prediction with + # query + prediction (or match if available) + # neighbors: id, composition, physchem, tox, similarity + #content_type :json + #JSON.pretty_generate(@example) end diff --git a/data.json b/data.json index 1b0658f..5d38cc4 100644 --- a/data.json +++ b/data.json @@ -1 +1 @@ -{"G15.AC":{"composition":{"Core composition":"[Au]","Surface modifier1":"N-Acetyl-L-cysteine","Surface modifier2":null,"Classification":"Anionic"},"tox":{"Cell.association (Net cell association [mL/ug(Mg)])":0.02751,"Cell.association (Log2 transformed)":-5.184},"physchem":{"Core size [nm]":14.9,"Density [g/cm^3]":19.1,"MW [g/mol]":197.0,"Z-Average Hydrodynamic Diameter [nm]":22.36,"Z-Average Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":57.53,"Z-Average Hydrodynamic Diameter Change":35.1667,"Volume Mean Hydrodynamic Diameter [nm]":21.94,"Volume Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":21.75,"Volume Mean Hydrodynamic Diameter Change":-0.1854,"Number Mean Hydrodynamic Diameter [nm]":23.49,"Number Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":18.38,"Number Mean Hydrodynamic Diameter Change":-5.117,"Intensity Mean Hydrodynamic Diameter [nm]":23.49,"Intensity Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":70.97,"Intensity Mean Hydrodynamic Diameter Change":47.4778,"Polydispersity index [nm]":0.084,"Polydispersity index Human serum (Sigma #H4522) [nm]":0.27,"Polydispersity index Change":0.1867,"ZETA POTENTIAL [mV]":-21.78,"ZETA POTENTIAL Human serum (Sigma #H4522) [mV]":-9.11,"ZETA POTENTIAL Change":12.6717,"Localized Surface Plasmon Resonance (LSPR) index":0.182530253,"Localized Surface Plasmon Resonance (LSPR) index Human serum (Sigma #H4522)":0.454404195,"Localized Surface Plasmon Resonance (LSPR) index Change":0.2719,"LSPR peak position (nm) [nm]":518.77,"Total protein (BCA assay) Human serum (Sigma #H4522) [ug]":2.927,"Autot (ICP-AES) Human serum (Sigma #H4522) [nmol]":255.4430266,"Total surface area (SAtot) Human serum (Sigma #H4522) [cm^2]":11.0,"Protein density Human serum (Sigma #H4522) Mean [ug/cm^2]":0.0,"Protein density Human serum (Sigma #H4522) SEM [ug/cm^2]":0.026465833}},"G15.AHT":{"composition":{"Core composition":"[Au]","Surface modifier1":"6-Amino-1-hexanethiol","Surface modifier2":null,"Classification":"Cationic"},"tox":{"Cell.association (Net cell association [mL/ug(Mg)])":0.49705,"Cell.association (Log2 transformed)":-1.009},"physchem":{"Core size [nm]":14.9,"Density [g/cm^3]":19.1,"MW [g/mol]":197.0,"Z-Average Hydrodynamic Diameter [nm]":30.95,"Z-Average Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":90.06,"Z-Average Hydrodynamic Diameter Change":59.1089,"Volume Mean Hydrodynamic Diameter [nm]":11.76,"Volume Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":67.79,"Volume Mean Hydrodynamic Diameter Change":56.032,"Number Mean Hydrodynamic Diameter [nm]":47.5,"Number Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":53.87,"Number Mean Hydrodynamic Diameter Change":6.3667,"Intensity Mean Hydrodynamic Diameter [nm]":47.5,"Intensity Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":106.7,"Intensity Mean Hydrodynamic Diameter Change":59.2033,"Polydispersity index [nm]":0.399,"Polydispersity index Human serum (Sigma #H4522) [nm]":0.215,"Polydispersity index Change":-0.1837,"ZETA POTENTIAL 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Resonance (LSPR) index":0.26103318,"Localized Surface Plasmon Resonance (LSPR) index Human serum (Sigma #H4522)":0.363008062,"Localized Surface Plasmon Resonance (LSPR) index Change":0.102,"LSPR peak position (nm) [nm]":540.1,"Total protein (BCA assay) Human serum (Sigma #H4522) [ug]":3.02,"Autot (ICP-AES) Human serum (Sigma #H4522) [nmol]":948.9179405,"Total surface area (SAtot) Human serum (Sigma #H4522) [cm^2]":10.0,"Protein density Human serum (Sigma #H4522) Mean [ug/cm^2]":0.0,"Protein density Human serum (Sigma #H4522) SEM [ug/cm^2]":0.034421709}}} diff --git a/protein_corona.rb b/protein_corona.rb index 35970dc..890b3ca 100644 --- a/protein_corona.rb +++ b/protein_corona.rb @@ -1,8 +1,35 @@ require 'json' require 'yaml' require 'csv' -#require_relative "../lazar/lib/lazar.rb" -#include OpenTox + +ENDPOINT = "Cell.association (Net cell association [mL/ug(Mg)])" + +def predict params + neighbors = [] + sim_sum = 0 + weighted_sum = 0 + match = nil + JSON.parse(File.read("./data.json")).each do |id,categories| + if params.values == categories["physchem"].values + match = {:id => categories} + else + sim = cosine_similarity(params.values,categories["physchem"].values) + neighbor = categories + neighbor["similarity"] = sim + neighbor["id"] = id + sim_sum += sim + weighted_sum += sim*Math.log(categories["tox"][ENDPOINT]) + neighbors << neighbor + end + end + neighbors.sort!{|a,b| b["similarity"] <=> a["similarity"]} + { + :query => params, + :match => match, + :prediction => {ENDPOINT => 10**(weighted_sum/sim_sum)}, + :neighbors => neighbors + } +end class Object def numeric? @@ -70,18 +97,20 @@ def csv2json data = {} csv.drop(12).each do |row| id = row.first - data[id] = {} - row.each_with_index do |col,i| - if i == 0 - data[id][:composition] = {} - elsif i < 5 - data[id][:composition][feature_names[i]] = col - elsif i < 7 - data[id][:tox] ||= {} - data[id][:tox][feature_names[i]] = col - else - data[id][:physchem] ||= {} - data[id][:physchem][feature_names[i]] = col + if id.match /^G/ # skip Ag, too many missing values + data[id] = {} + row.each_with_index do |col,i| + if i == 0 + data[id][:composition] = {} + elsif i < 5 + data[id][:composition][feature_names[i]] = col + elsif i == 5 + data[id][:tox] ||= {} + data[id][:tox][feature_names[i]] = col + elsif i > 6 + data[id][:physchem] ||= {} + data[id][:physchem][feature_names[i]] = col + end end end end -- cgit v1.2.3 From 6bc457aa0a10898a53480f8031609ac2a9b96db8 Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Wed, 20 Jan 2016 13:50:29 +0100 Subject: old lib, data removed --- .gitignore | 1 + data/marina.json | 3282 ---- data/multi-walled-nano-tubes.json | 430 - data/nanowiki.json | 30302 ------------------------------------ data/protein-corona.json | 20614 ------------------------ lib/nano-lazar.rb | 1 - lib/nanoparticle.rb | 9 - nano-lazar.gemspec | 22 - 8 files changed, 1 insertion(+), 54660 deletions(-) delete mode 100644 data/marina.json delete mode 100644 data/multi-walled-nano-tubes.json delete mode 100644 data/nanowiki.json delete mode 100644 data/protein-corona.json delete mode 100644 lib/nano-lazar.rb delete mode 100644 lib/nanoparticle.rb delete mode 100644 nano-lazar.gemspec diff --git a/.gitignore b/.gitignore index 59e48cf..43ce16a 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ +lib data papers *tmp diff --git a/data/marina.json b/data/marina.json deleted file mode 100644 index a615f42..0000000 --- a/data/marina.json +++ /dev/null @@ -1,3282 +0,0 @@ -{ -"query": { - "summary":"query" -}, -"dataEntry":[ - { - "compound":{ - "URI":"https://apps.ideaconsult.net/enanomapper/substance/XLSX-7011cea0-1011-3f8b-9e8a-b3289fed836a", - "structype":"NA", - "metric":null, - "name":"", - "cas":"", - "einecs":"" - - }, - "values":{ - "https://apps.ideaconsult.net/enanomapper/identifier/name":"Titanium Dioxide", - "https://apps.ideaconsult.net/enanomapper/identifier/tradename":"NM-103 (TiO2)", - 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-"https://apps.ideaconsult.net/enanomapper/feature/http%3A%2F%2Fwww.opentox.org%2Fapi%2F1.1%23IUCLID5_UUIDDefault":{ - - "type":"Feature", - "title":"IUCLID 5 Reference substance UUID", - "units":"", - "isNominal":false, - "isNumeric":false, - "isMultiValue":false, - "sameAs":"http://www.opentox.org/api/1.1#IUCLID5_UUID", - "isModelPredictionFeature":false, - "creator":"http://ambit.sourceforge.net", - "order":0, - "source":{ - "URI":"https://apps.ideaconsult.net/enanomapper/dataset/Default", - "type":"Dataset" - }, - "annotation":[] - -}, -"https://apps.ideaconsult.net/enanomapper/feature/http%3A%2F%2Fwww.opentox.org%2Fapi%2F1.1%23ChemicalNameDefault":{ - - "type":"Feature", - "title":"Names", - "units":"", - "isNominal":false, - "isNumeric":false, - "isMultiValue":false, - "sameAs":"http://www.opentox.org/api/1.1#ChemicalName", - "isModelPredictionFeature":false, - "creator":"http://ambit.sourceforge.net", - "order":0, - "source":{ - "URI":"https://apps.ideaconsult.net/enanomapper/dataset/Default", - "type":"Dataset" - }, - "annotation":[] - -}, -"https://apps.ideaconsult.net/enanomapper/feature/http%3A%2F%2Fwww.opentox.org%2Fapi%2F1.1%23CASRNDefault":{ - - "type":"Feature", - "title":"CasRN", - "units":"", - "isNominal":false, - "isNumeric":false, - "isMultiValue":false, - "sameAs":"http://www.opentox.org/api/1.1#CASRN", - "isModelPredictionFeature":false, - "creator":"http://ambit.sourceforge.net", - "order":0, - "source":{ - "URI":"https://apps.ideaconsult.net/enanomapper/dataset/Default", - "type":"Dataset" - }, - "annotation":[] - -}} -} diff --git a/lib/nano-lazar.rb b/lib/nano-lazar.rb deleted file mode 100644 index 718133c..0000000 --- a/lib/nano-lazar.rb +++ /dev/null @@ -1 +0,0 @@ -Dir[File.join(File.dirname(__FILE__),"*")].each {|f| require_relative f} diff --git a/lib/nanoparticle.rb b/lib/nanoparticle.rb deleted file mode 100644 index 0ec29a3..0000000 --- a/lib/nanoparticle.rb +++ /dev/null @@ -1,9 +0,0 @@ -module OpenTox - - class Nanoparticle - include OpenTox - - attr_accessor :name, :uri, :tox, :p_chem, :core, :coating - - end -end diff --git a/nano-lazar.gemspec b/nano-lazar.gemspec deleted file mode 100644 index 2e40218..0000000 --- a/nano-lazar.gemspec +++ /dev/null @@ -1,22 +0,0 @@ -# -*- encoding: utf-8 -*- -$:.push File.expand_path("../lib", __FILE__) - -Gem::Specification.new do |s| - s.name = "lazar" - s.version = File.read("./VERSION").strip - s.authors = ["Christoph Helma, Micha Rautenberg, David Vorgrimmler, Denis Gebele"] - s.email = ["helma@in-silico.ch"] - s.homepage = "http://github.com/opentox/nano-lazar" - s.summary = %q{Lazar nanotoxicity framework} - s.description = %q{Libraries for nanoparticle lazy structure-activity relationships and read-across.} - s.license = 'GPL-3' - - s.rubyforge_project = "lazar" - s.files = `git ls-files`.split("\n") - s.test_files = `git ls-files -- {test,spec,features}/*`.split("\n") - s.require_paths = ["lib"] - - # specify any dependencies here; for example: - s.add_runtime_dependency "bundler" - s.add_runtime_dependency "lazar" -end -- cgit v1.2.3 From 9546c589f6852942ed85f8da1e12c351fb92e0f0 Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Wed, 20 Jan 2016 13:53:22 +0100 Subject: enm import removed --- .gitignore | 1 + application.rb | 4 +- import.rb | 153 ------------------------------------------------------ nanoparticles.rb | 147 +++++++++++++++++++++++++++++++++++++++++++++++++++ protein_corona.rb | 147 --------------------------------------------------- 5 files changed, 150 insertions(+), 302 deletions(-) delete mode 100644 import.rb create mode 100644 nanoparticles.rb delete mode 100644 protein_corona.rb diff --git a/.gitignore b/.gitignore index 43ce16a..e73632d 100644 --- a/.gitignore +++ b/.gitignore @@ -3,3 +3,4 @@ data papers *tmp *swp +enm-import.rb diff --git a/application.rb b/application.rb index 1cb0e13..703932f 100644 --- a/application.rb +++ b/application.rb @@ -1,7 +1,7 @@ require 'sinatra' require "sinatra/reloader" if development? -require_relative 'protein_corona.rb' -also_reload './protein_corona.rb' +require_relative 'nanoparticles.rb' +also_reload './nanoparticles.rb' get '/?' do @data = JSON.parse(File.read("./data.json")) diff --git a/import.rb b/import.rb deleted file mode 100644 index 63d8a08..0000000 --- a/import.rb +++ /dev/null @@ -1,153 +0,0 @@ -# TODO: missing data for protein corona silver particles -require 'json' -require 'yaml' -require 'csv' -require_relative "lib/nano-lazar.rb" -include OpenTox - -def feature_name uri - f = @features[uri] - name = f['title'] - annotations = f['annotation'].collect{|a| "#{a['p']}: #{a['o']}"}.uniq.join ", " - name << " (#{annotations})" unless annotations.empty? - name << " [#{f['units']}]" if f['units'] and !f['units'].empty? - name -end - -nanomaterials = [] -feature_names = {} -@features = {} - -["nanowiki.json", "protein-corona.json", "marina.json"].each do |f| - bundle = JSON.parse(File.read(File.join("data",f))) - @features.merge! bundle["feature"] - bundle["dataEntry"].each do |substance| - nm = Nanoparticle.new - nm.uri = substance["compound"]["URI"] - nm.name = substance["values"]["https://apps.ideaconsult.net/enanomapper/identifier/name"] if substance["values"] - if substance["composition"] - nr_cores = substance["composition"].select{|c| c["relation"] == "HAS_CORE"}.size - puts "#{substance["compound"]["URI"]} has #{nr_cores} cores" if nr_cores !=1 - substance["composition"].each do |composition| - component = composition["component"] - if component - name = component["values"]["https://apps.ideaconsult.net/enanomapper/feature/http%3A%2F%2Fwww.opentox.org%2Fapi%2F1.1%23ChemicalNameDefault"] - #names << name - if composition["relation"] == "HAS_CORE" - nm.core = name - elsif composition["relation"] == "HAS_COATING" - nm.coating ||= [] - nm.coating << name - end - else - #puts substance.to_yaml - end - end - else - #puts substance.to_yaml - end - substance["values"].each do |k,v| - property = nil - if k.match(/TOX/) - nm.tox ||= [] - property = "tox" - elsif k.match(/P-CHEM/) - nm.p_chem ||= [] - property = "p_chem" - end - if property - v.each do |val| - if val.keys == ["loValue"] - nm.tox << {k => val["loValue"]} if property == "tox" - nm.p_chem << {k => val["loValue"]} if property == "p_chem" - elsif val.keys == ["loQualifier", "loValue"] and val["loQualifier"] == "mean" - nm.tox << {k => val["loValue"]} if property == "tox" - nm.p_chem << {k => val["loValue"]} if property == "p_chem" - elsif val.keys == ["loQualifier", "loValue", "upQualifier", "upValue" ] - nm.tox << {k => (val["loValue"]+val["upValue"])/2} if property == "tox" - nm.p_chem << {k => (val["loValue"]+val["upValue"])/2} if property == "p_chem" - elsif val.keys == ["loQualifier", "loValue"] and val["loQualifier"] == ">=" - else - p val - end - end - else - #p k,v - end - end - nm.tox.uniq! if nm.tox - nm.p_chem.uniq! if nm.p_chem - nanomaterials << nm - end -end - -puts "Total imported: #{nanomaterials.size}" -puts "With nanoparticle characterisation: #{nanomaterials.select{|n| n.p_chem}.size}" -modelling_data = nanomaterials.select{|n| n.tox and n.p_chem} -puts "With TOX data: #{nanomaterials.select{|n| n.tox}.size}" -puts "With TOX data and particle characterisation: #{modelling_data.size}" -endpoints = modelling_data.collect{|n| n.tox.collect{|t| t.keys}}.flatten.compact.uniq -puts -puts "Endpoints: #{endpoints.size}" - -single_value_endpoints = [] -endpoint_values = {} - -endpoints.each do |e| - i = 0 - values = [] - modelling_data.each do |n| - n.tox.each do |t| - if t[e] - i += 1 - values << t[e] - end - end - end - single_value_endpoints << e if values.uniq.size == 1 - endpoint_values[e] = values.size unless values.uniq.size == 1 -end - -endpoints -= single_value_endpoints -puts "Endpoints with more than one measurement value: #{endpoints.size}" -endpoint_values.select!{|k,v| v > 10} -puts "Endpoints with more than 10 measurements: #{endpoint_values.size}" -endpoints = endpoint_values.keys -puts -puts endpoint_values.sort{|a,b| b[1] <=> a[1]}.collect{|e,v| "#{feature_names[e]}: #{v}"}.join("\n") - -endpoint = "https://apps.ideaconsult.net/enanomapper/property/TOX/UNKNOWN_TOXICITY_SECTION/Log2+transformed/94D664CFE4929A0F400A5AD8CA733B52E049A688/E/3ed642f9-1b42-387a-9966-dea5b91e5f8a" -nanomaterials.select!{|nm| nm.tox and nm.tox.collect{|t| t.keys}.flatten.include? endpoint} -p nanomaterials.size - -feature_values = {} -nanomaterials.each do |nm| - (nm.p_chem + nm.tox).each do |f| - feature_names[f] = feature_name f # avoid appending annotations/units with each function call, unclear why it happens - p f unless f.size == 1 - k = f.keys.first - unless f[k].is_a? String - feature_values[k] ||= [] - feature_values[k] << f[k] - end - end -end - -# remove empty values -feature_values.select!{|f,vals| vals.uniq.size > 2} -tox_descriptors = feature_values.select{|f,vals| f.match 'TOX'}.keys -p_chem_descriptors = feature_values.select{|f,vals| f.match 'P-CHEM'}.keys - -#puts @features.to_yaml - -column_names = ["Nanoparticle"] + p_chem_descriptors.collect{|d| feature_names[d]} + tox_descriptors.collect{|d| feature_names[d]} -table = [] -CSV.open(File.join(File.dirname(__FILE__),"data","protein_corona_extract.csv"),"w+") do |csv| - csv << column_names - nanomaterials.each do |nm| - if nm.tox and nm.tox.collect{|t| t.keys}.flatten.include? endpoint - #table << [] - csv << [nm.name] + p_chem_descriptors.collect{|p| nm.p_chem.collect{|pchem| pchem[p]}.compact.first} + tox_descriptors.collect{|p| nm.p_chem.collect{|pchem| pchem[p]}.compact.first} - end - end -end diff --git a/nanoparticles.rb b/nanoparticles.rb new file mode 100644 index 0000000..890b3ca --- /dev/null +++ b/nanoparticles.rb @@ -0,0 +1,147 @@ +require 'json' +require 'yaml' +require 'csv' + +ENDPOINT = "Cell.association (Net cell association [mL/ug(Mg)])" + +def predict params + neighbors = [] + sim_sum = 0 + weighted_sum = 0 + match = nil + JSON.parse(File.read("./data.json")).each do |id,categories| + if params.values == categories["physchem"].values + match = {:id => categories} + else + sim = cosine_similarity(params.values,categories["physchem"].values) + neighbor = categories + neighbor["similarity"] = sim + neighbor["id"] = id + sim_sum += sim + weighted_sum += sim*Math.log(categories["tox"][ENDPOINT]) + neighbors << neighbor + end + end + neighbors.sort!{|a,b| b["similarity"] <=> a["similarity"]} + { + :query => params, + :match => match, + :prediction => {ENDPOINT => 10**(weighted_sum/sim_sum)}, + :neighbors => neighbors + } +end + +class Object + def numeric? + true if Float(self) rescue false + end +end + +def euclidean_distance(a, b) + sq = a.zip(b).map{|a,b| (a - b) ** 2} + Math.sqrt(sq.inject(0) {|s,c| s + c}) +end + +def dot_product(a, b) + products = a.zip(b).map{|a, b| a * b} + products.inject(0) {|s,p| s + p} +end + +def magnitude(point) + squares = point.map{|x| x ** 2} + Math.sqrt(squares.inject(0) {|s, c| s + c}) +end + +def cosine_similarity(a, b) + dot_product(a, b) / (magnitude(a) * magnitude(b)) +end + +#@endpoint = @data.collect{|r| r[5]} + +def neighbors query +end + +def csv2json + csv = CSV.read("data/MergedSheets_edit.csv") + csv.collect!{|row| row[0..36].collect{|c| c.numeric? ? c.to_f : c } }.compact + feature_names = [ + "ID", + csv[0][1], + csv[0][2], + csv[0][3], + csv[6][4], + "#{csv[0][5]} (#{csv[6][5]} [#{csv[11][5]}])", # endpoint + "#{csv[0][6]} (#{csv[6][6]})", # endpoint + "#{csv[6][7]} [#{csv[11][7]}]", + "#{csv[6][8]} [#{csv[11][8]}]", + "#{csv[6][9]} [#{csv[11][9]}]", + ] + (10..10+5*3).step(3) do |i| + feature_names += [ + "#{csv[6][i]} [#{csv[11][i]}]", + "#{csv[6][i+1]} #{csv[8][i+1]} [#{csv[11][i+1]}]", + "#{csv[6][i+2]} #{csv[8][i+2]}", + ] + end + feature_names += [ + "#{csv[6][28]}", + "#{csv[6][29]} #{csv[8][29]}", + "#{csv[6][30]} #{csv[8][30]}", + ] + (31..34).each do |i| + feature_names << "#{csv[6][i]} #{csv[8][i]} [#{csv[11][i]}]" + end + (35..36).each do |i| + feature_names << "#{csv[6][i]} #{csv[8][i]} #{csv[10][i]} [#{csv[11][i]}]" + end + data = {} + csv.drop(12).each do |row| + id = row.first + if id.match /^G/ # skip Ag, too many missing values + data[id] = {} + row.each_with_index do |col,i| + if i == 0 + data[id][:composition] = {} + elsif i < 5 + data[id][:composition][feature_names[i]] = col + elsif i == 5 + data[id][:tox] ||= {} + data[id][:tox][feature_names[i]] = col + elsif i > 6 + data[id][:physchem] ||= {} + data[id][:physchem][feature_names[i]] = col + end + end + end + end + File.open("data.json","w+"){|f| f.puts data.to_json} + data +end + +#puts data.to_yaml +=begin +R.assign "endpoint", endpoint +(0..data[0].size).each do |c| + if data.collect{|r| r[c]}.uniq.size > 1 + begin + R.assign "feature", data.collect{|r| r[c]} + R.eval "r <- cor(-log(endpoint),-log(feature),use='complete')" + r = R.eval("r").to_ruby + p "#{c}: #{r}" if r > 0.3 or r < -0.3 + rescue + end + end +end + + +csv[0..13].each do |row| + row.each_with_index do |col,i| + features[i] = features[i].to_s+", "+col.to_s + end +end + +puts features.select{|f| f.match(/Mean/)}.to_yaml + + #n+=1 + #p n,row.first unless row.first.match /^[G|S]/ +=end diff --git a/protein_corona.rb b/protein_corona.rb deleted file mode 100644 index 890b3ca..0000000 --- a/protein_corona.rb +++ /dev/null @@ -1,147 +0,0 @@ -require 'json' -require 'yaml' -require 'csv' - -ENDPOINT = "Cell.association (Net cell association [mL/ug(Mg)])" - -def predict params - neighbors = [] - sim_sum = 0 - weighted_sum = 0 - match = nil - JSON.parse(File.read("./data.json")).each do |id,categories| - if params.values == categories["physchem"].values - match = {:id => categories} - else - sim = cosine_similarity(params.values,categories["physchem"].values) - neighbor = categories - neighbor["similarity"] = sim - neighbor["id"] = id - sim_sum += sim - weighted_sum += sim*Math.log(categories["tox"][ENDPOINT]) - neighbors << neighbor - end - end - neighbors.sort!{|a,b| b["similarity"] <=> a["similarity"]} - { - :query => params, - :match => match, - :prediction => {ENDPOINT => 10**(weighted_sum/sim_sum)}, - :neighbors => neighbors - } -end - -class Object - def numeric? - true if Float(self) rescue false - end -end - -def euclidean_distance(a, b) - sq = a.zip(b).map{|a,b| (a - b) ** 2} - Math.sqrt(sq.inject(0) {|s,c| s + c}) -end - -def dot_product(a, b) - products = a.zip(b).map{|a, b| a * b} - products.inject(0) {|s,p| s + p} -end - -def magnitude(point) - squares = point.map{|x| x ** 2} - Math.sqrt(squares.inject(0) {|s, c| s + c}) -end - -def cosine_similarity(a, b) - dot_product(a, b) / (magnitude(a) * magnitude(b)) -end - -#@endpoint = @data.collect{|r| r[5]} - -def neighbors query -end - -def csv2json - csv = CSV.read("data/MergedSheets_edit.csv") - csv.collect!{|row| row[0..36].collect{|c| c.numeric? ? c.to_f : c } }.compact - feature_names = [ - "ID", - csv[0][1], - csv[0][2], - csv[0][3], - csv[6][4], - "#{csv[0][5]} (#{csv[6][5]} [#{csv[11][5]}])", # endpoint - "#{csv[0][6]} (#{csv[6][6]})", # endpoint - "#{csv[6][7]} [#{csv[11][7]}]", - "#{csv[6][8]} [#{csv[11][8]}]", - "#{csv[6][9]} [#{csv[11][9]}]", - ] - (10..10+5*3).step(3) do |i| - feature_names += [ - "#{csv[6][i]} [#{csv[11][i]}]", - "#{csv[6][i+1]} #{csv[8][i+1]} [#{csv[11][i+1]}]", - "#{csv[6][i+2]} #{csv[8][i+2]}", - ] - end - feature_names += [ - "#{csv[6][28]}", - "#{csv[6][29]} #{csv[8][29]}", - "#{csv[6][30]} #{csv[8][30]}", - ] - (31..34).each do |i| - feature_names << "#{csv[6][i]} #{csv[8][i]} [#{csv[11][i]}]" - end - (35..36).each do |i| - feature_names << "#{csv[6][i]} #{csv[8][i]} #{csv[10][i]} [#{csv[11][i]}]" - end - data = {} - csv.drop(12).each do |row| - id = row.first - if id.match /^G/ # skip Ag, too many missing values - data[id] = {} - row.each_with_index do |col,i| - if i == 0 - data[id][:composition] = {} - elsif i < 5 - data[id][:composition][feature_names[i]] = col - elsif i == 5 - data[id][:tox] ||= {} - data[id][:tox][feature_names[i]] = col - elsif i > 6 - data[id][:physchem] ||= {} - data[id][:physchem][feature_names[i]] = col - end - end - end - end - File.open("data.json","w+"){|f| f.puts data.to_json} - data -end - -#puts data.to_yaml -=begin -R.assign "endpoint", endpoint -(0..data[0].size).each do |c| - if data.collect{|r| r[c]}.uniq.size > 1 - begin - R.assign "feature", data.collect{|r| r[c]} - R.eval "r <- cor(-log(endpoint),-log(feature),use='complete')" - r = R.eval("r").to_ruby - p "#{c}: #{r}" if r > 0.3 or r < -0.3 - rescue - end - end -end - - -csv[0..13].each do |row| - row.each_with_index do |col,i| - features[i] = features[i].to_s+", "+col.to_s - end -end - -puts features.select{|f| f.match(/Mean/)}.to_yaml - - #n+=1 - #p n,row.first unless row.first.match /^[G|S]/ -=end -- cgit v1.2.3 From d8f1e75ba45cb770f421fa950861c6ff502d64dd Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Thu, 21 Jan 2016 19:26:48 +0100 Subject: feature selection added --- feature-filter.rb | 36 ++++++++++++++++++++++++++++++++++++ nanoparticles.rb | 43 +++++++++++++++++++++++++++++++++---------- relevant-features.json | 1 + test/predict.rb | 9 +++++++++ 4 files changed, 79 insertions(+), 10 deletions(-) create mode 100644 feature-filter.rb create mode 100644 relevant-features.json create mode 100644 test/predict.rb diff --git a/feature-filter.rb b/feature-filter.rb new file mode 100644 index 0000000..3765842 --- /dev/null +++ b/feature-filter.rb @@ -0,0 +1,36 @@ +require 'rserve' +require 'json' +require 'yaml' +require 'csv' + +R = Rserve::Connection.new +ENDPOINT = "Cell.association (Net cell association [mL/ug(Mg)])" + +def feature_filter + data = JSON.parse(File.read("./data.json")) + features = data["G15.AC"]["physchem"].keys + R.assign "tox", data.collect{|id,cats| cats["tox"][ENDPOINT]} + filtered_features = {} + features.each do |feature| + R.assign "feature", data.collect{|id,cats| cats["physchem"][feature]} + begin + #R.eval "cor <- cor.test(-log(tox),-log(feature),use='complete')" + R.eval "cor <- cor.test(tox,feature,method = 'pearson',use='complete')" + pvalue = R.eval("cor$p.value").to_ruby + if pvalue <= 0.05 + r = R.eval("cor$estimate").to_ruby + filtered_features[feature] = {} + filtered_features[feature]["pvalue"] = pvalue + filtered_features[feature]["r"] = r + end + rescue + f = data.collect{|id,cats| cats["physchem"][feature]} + f = R.eval("feature").to_ruby + p f.collect{|f| p f; Math.log f} + p R.eval("log(feature)").to_ruby + end + end + filtered_features.sort{|a,b| a[1]["pvalue"] <=> b[1]["pvalue"]}.to_h +end + +puts feature_filter.to_json diff --git a/nanoparticles.rb b/nanoparticles.rb index 890b3ca..e34e509 100644 --- a/nanoparticles.rb +++ b/nanoparticles.rb @@ -1,3 +1,4 @@ +require 'rserve' require 'json' require 'yaml' require 'csv' @@ -9,24 +10,32 @@ def predict params sim_sum = 0 weighted_sum = 0 match = nil + relevant_features = JSON.parse(File.read("./relevant-features.json")) + weights = relevant_features.values.collect{|v| v["r"]} JSON.parse(File.read("./data.json")).each do |id,categories| - if params.values == categories["physchem"].values - match = {:id => categories} + neighbor_values = categories["physchem"].select{|f,v| params.keys.include? f}.values + if params.values == neighbor_values + match = {id => categories} else - sim = cosine_similarity(params.values,categories["physchem"].values) - neighbor = categories - neighbor["similarity"] = sim - neighbor["id"] = id - sim_sum += sim - weighted_sum += sim*Math.log(categories["tox"][ENDPOINT]) - neighbors << neighbor + sim = weighted_cosine_similarity(params.values,neighbor_values,weights) + if sim > 0.95 + neighbor = categories + neighbor["similarity"] = sim + neighbor["sim"] = cosine_similarity(params.values,neighbor_values) + neighbor["id"] = id + sim_sum += sim + weighted_sum += sim*Math.log10(categories["tox"][ENDPOINT]) + #weighted_sum += sim*categories["tox"][ENDPOINT] + neighbors << neighbor + end end end neighbors.sort!{|a,b| b["similarity"] <=> a["similarity"]} + sim_sum == 0 ? prediction = nil : prediction = 10**(weighted_sum/sim_sum) { :query => params, :match => match, - :prediction => {ENDPOINT => 10**(weighted_sum/sim_sum)}, + :prediction => {ENDPOINT => prediction}, :neighbors => neighbors } end @@ -52,10 +61,24 @@ def magnitude(point) Math.sqrt(squares.inject(0) {|s, c| s + c}) end +# http://stackoverflow.com/questions/1838806/euclidean-distance-vs-pearson-correlation-vs-cosine-similarity def cosine_similarity(a, b) dot_product(a, b) / (magnitude(a) * magnitude(b)) end +def weighted_cosine_similarity(a, b, w) + dot_product = 0 + magnitude_a = 0 + magnitude_b = 0 + (0..a.size-1).each do |i| + dot_product += w[i].abs*a[i]*b[i] + magnitude_a += w[i].abs*a[i]**2 + magnitude_b += w[i].abs*b[i]**2 + end + dot_product/Math.sqrt(magnitude_a*magnitude_b) + +end + #@endpoint = @data.collect{|r| r[5]} def neighbors query diff --git a/relevant-features.json b/relevant-features.json new file mode 100644 index 0000000..8da5f0a --- /dev/null +++ b/relevant-features.json @@ -0,0 +1 @@ +{"Localized Surface Plasmon Resonance (LSPR) index Human serum (Sigma #H4522)":{"pvalue":2.7781332789800217e-10,"r":0.5673665177300351},"ZETA POTENTIAL Change":{"pvalue":2.071052722262855e-09,"r":-0.5435850485069125},"ZETA POTENTIAL [mV]":{"pvalue":2.025461243171378e-08,"r":0.5141366184476799},"Intensity Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":{"pvalue":7.296459421546331e-06,"r":0.4220954992507819},"Volume Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":{"pvalue":0.00014304093718453537,"r":0.3627394229575142},"Z-Average Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":{"pvalue":0.0013415551974216289,"r":0.3089691292079323},"Localized Surface Plasmon Resonance (LSPR) index Change":{"pvalue":0.0020134808685383643,"r":0.2980672974262308},"Total surface area (SAtot) Human serum (Sigma #H4522) [cm^2]":{"pvalue":0.009242146870015556,"r":-0.2529069909205578},"Localized Surface Plasmon Resonance (LSPR) index":{"pvalue":0.010019903744117542,"r":0.2502907155942361},"Volume Mean Hydrodynamic Diameter Change":{"pvalue":0.013109585368169974,"r":0.24139711318406543},"Polydispersity index Change":{"pvalue":0.020454612521909568,"r":-0.22597482832068308},"Volume Mean Hydrodynamic Diameter [nm]":{"pvalue":0.033722917694600785,"r":0.20744306643756433},"Polydispersity index [nm]":{"pvalue":0.04433575298419301,"r":0.19667713971723438},"Number Mean Hydrodynamic Diameter Human serum (Sigma #H4522) [nm]":{"pvalue":0.04474107346052025,"r":0.19631065152636545}} diff --git a/test/predict.rb b/test/predict.rb new file mode 100644 index 0000000..9aed5e2 --- /dev/null +++ b/test/predict.rb @@ -0,0 +1,9 @@ +require_relative "../nanoparticles.rb" +data = JSON.parse(File.read("./data.json")) +relevant_features = JSON.parse(File.read("./relevant-features.json")) +example = data[data.keys.sample]["physchem"].select{|f,v| relevant_features.keys.include? f} +#data.collect +puts predict(example)[:match].collect{|id,v| v["tox"]}.first +puts predict(example)[:prediction] +#puts predict(example)[:neighbors].size + -- cgit v1.2.3 From 8ebb209d00fd11ccdc86bc1e695f4bb9b9300f33 Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Fri, 22 Jan 2016 11:13:41 +0100 Subject: example with relevant features only --- application.rb | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/application.rb b/application.rb index 703932f..7ff09be 100644 --- a/application.rb +++ b/application.rb @@ -4,11 +4,10 @@ require_relative 'nanoparticles.rb' also_reload './nanoparticles.rb' get '/?' do - @data = JSON.parse(File.read("./data.json")) - @example = @data[@data.keys.sample]["physchem"] + data = JSON.parse(File.read("./data.json")) + relevant_features = JSON.parse(File.read("./relevant-features.json")) + @example = data[data.keys.sample]["physchem"].select{|f,v| relevant_features.keys.include? f} # create a data entry form with @example as default values - #content_type :json - #JSON.pretty_generate(@example) end post '/?' do @@ -16,6 +15,4 @@ post '/?' do # display prediction with # query + prediction (or match if available) # neighbors: id, composition, physchem, tox, similarity - #content_type :json - #JSON.pretty_generate(@example) end -- cgit v1.2.3 From 7da754f80a414810a8c4721e1e4ed9b4c2d706d7 Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Fri, 22 Jan 2016 13:36:01 +0100 Subject: workshop presentation, enm source data added again --- .gitignore | 3 +- data/marina.json | 3282 ++++ data/multi-walled-nano-tubes.json | 430 + data/nanowiki.json | 30302 ++++++++++++++++++++++++++++++++++++ data/protein-corona.json | 20614 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imported: 464 +Nanoparticles with particle characterisation: 394 +Nanoparticles with toxicity data: 167 +Nanoparticles with toxicity data and particle characterisation: 160 + +# eNanoMapper toxicity endpoints + +.. alles ohne falsch? zugewiesene protein corona tox endpoints +Toxicity endpoints: 41 +Toxicity endpoints with more than one measurement value: 22 +Toxicity endpoints with more than 10 measurements: 2 + +# Selected data + +Protein corona dataset Au particles (106 particles) +Toxicity endpoint: + +# Read across procedure + +- Identify relevant fragments (significant correlation with toxicity) + TODO list of fragments, number +- Calculate similarities (weighted cosine similarity, correlation coefficients = weights) +- Identify neighbors (particles with more than 0.95 similarity) +- Calculate prediction (weighted average from neighbors, similarities = weights) + +# Future development + +- Validation of predictions +- Applicability domain/reliability of predictions + +- Accuracy improvements: + - additional data + - feature selection + - similarity calculation + - predictions (local regression models) + +- Usability improvements: + - additional data (extension of applicability domain, additional endpoints and chemistries) + - inclusion of ontologies + - Descriptor calculation directly from core and coating chemistries + +# Webinterface + +Your recommendations? + +# Source code + +https://github.com/opentox/nano-lazar -- cgit v1.2.3 From fbc7ec1f342767052e23d6430ea94f0ae7c8d27f Mon Sep 17 00:00:00 2001 From: Christoph Helma Date: Fri, 22 Jan 2016 16:55:39 +0100 Subject: rendered workshop presentation --- presentation/enm-workshop.html | 445 ++++++++++++++++++++++++ presentation/enm-workshop.rst | 70 ++-- presentation/ui/small-white/blank.gif | Bin 0 -> 49 bytes presentation/ui/small-white/framing.css | 24 ++ presentation/ui/small-white/iepngfix.htc | 42 +++ presentation/ui/small-white/opera.css | 8 + presentation/ui/small-white/outline.css | 16 + 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b/presentation/enm-workshop.html new file mode 100644 index 0000000..f0c6781 --- /dev/null +++ b/presentation/enm-workshop.html @@ -0,0 +1,445 @@ + + + + + + + +Read across toxicity predictions with nano-lazar + + + + + + + + + + + + + + +
+
+
+ + +
+
+
+

Read across toxicity predictions with nano-lazar

+ +

Christoph Helma

+

in silico toxicology gmbh

+http://www.enanomapper.net/sites/all/themes/theme807/logo.png + +
+
+

Requirements

+
    +
  • Nanoparticle characterisation
    • +
  • Toxicity measurements
    • +
+
+
+

eNanoMapper data import

+
    +
  • Nanoparticles imported: 464
    • +
  • Nanoparticles with particle characterisation: 394
    • +
  • Nanoparticles with toxicity data: 167
    • +
  • Nanoparticles with toxicity data and particle characterisation: 160
    • +
+
+
+

eNanoMapper toxicity endpoints

+
    +
  • Toxicity endpoints: 41
    • +
  • Toxicity endpoints with more than one measurement value: 22
    • +
  • Toxicity endpoints with more than 10 measurements: 2
    • +
+
+
+

Selected data

+

Protein corona dataset Au particles (106 particles) +Toxicity endpoint:

+
+
+

Read across procedure

+
    +
  • Identify relevant fragments (significant correlation with toxicity) +TODO list of fragments, number
    • +
  • Calculate similarities (weighted cosine similarity, correlation coefficients = weights)
    • +
  • Identify neighbors (particles with more than 0.95 similarity)
    • +
  • Calculate prediction (weighted average from neighbors, similarities = weights)
    • +
+
+
+

Future development

+
    +
  • Validation of predictions
    • +
  • Applicability domain/reliability of predictions
    • +
  • Accuracy improvements: +- additional data +- feature selection +- similarity calculation +- predictions (local regression models)
    • +
  • Usability improvements: +- additional data (extension of applicability domain, additional endpoints and chemistries) +- inclusion of ontologies +- descriptor calculation directly from core and coating chemistries
    • +
+
+
+

Webinterface

+

https://nano-lazar.in-silico.ch/predict

+

Your recommendations?

+
+ +
+ + diff --git a/presentation/enm-workshop.rst b/presentation/enm-workshop.rst index 7adae46..26a3524 100644 --- a/presentation/enm-workshop.rst +++ b/presentation/enm-workshop.rst @@ -1,30 +1,57 @@ -# Nanoparticle read across toxicity predictions with nano-lazar +.. |date| date:: -# Requirements + + +============================================================= +Read across toxicity predictions with nano-lazar +============================================================= + +.. class:: center + + Christoph Helma + + in silico toxicology gmbh + + .. image:: http://www.enanomapper.net/sites/all/themes/theme807/logo.png + :align: center + +Requirements +============ - Nanoparticle characterisation - Toxicity measurements -# eNanoMapper data import -Nanoparticles imported: 464 -Nanoparticles with particle characterisation: 394 -Nanoparticles with toxicity data: 167 -Nanoparticles with toxicity data and particle characterisation: 160 +eNanoMapper data import +======================= -# eNanoMapper toxicity endpoints +.. class:: incremental -.. alles ohne falsch? zugewiesene protein corona tox endpoints -Toxicity endpoints: 41 -Toxicity endpoints with more than one measurement value: 22 -Toxicity endpoints with more than 10 measurements: 2 + - Nanoparticles imported: 464 + - Nanoparticles with particle characterisation: 394 + - Nanoparticles with toxicity data: 167 + - Nanoparticles with toxicity data and particle characterisation: 160 -# Selected data + +eNanoMapper toxicity endpoints +============================== + +.. class:: incremental + +- Toxicity endpoints: 41 +- Toxicity endpoints with more than one measurement value: 22 +- Toxicity endpoints with more than 10 measurements: 2 + +Selected data +============= Protein corona dataset Au particles (106 particles) -Toxicity endpoint: +Toxicity endpoint: + +Read across procedure +===================== -# Read across procedure +.. class:: incremental - Identify relevant fragments (significant correlation with toxicity) TODO list of fragments, number @@ -32,7 +59,8 @@ Toxicity endpoint: - Identify neighbors (particles with more than 0.95 similarity) - Calculate prediction (weighted average from neighbors, similarities = weights) -# Future development +Future development +================== - Validation of predictions - Applicability domain/reliability of predictions @@ -46,12 +74,16 @@ Toxicity endpoint: - Usability improvements: - additional data (extension of applicability domain, additional endpoints and chemistries) - inclusion of ontologies - - Descriptor calculation directly from core and coating chemistries + - descriptor calculation directly from core and coating chemistries + +Webinterface +============ -# Webinterface +https://nano-lazar.in-silico.ch/predict Your recommendations? -# Source code +Source code +=========== https://github.com/opentox/nano-lazar diff --git a/presentation/ui/small-white/blank.gif b/presentation/ui/small-white/blank.gif new file mode 100644 index 0000000..75b945d Binary files /dev/null and b/presentation/ui/small-white/blank.gif differ diff --git a/presentation/ui/small-white/framing.css b/presentation/ui/small-white/framing.css new file mode 100644 index 0000000..70287dd --- /dev/null +++ b/presentation/ui/small-white/framing.css @@ -0,0 +1,24 @@ +/* This file has been placed in the public domain. */ +/* The following styles size, place, and layer the slide components. + Edit these if you want to change the overall slide layout. + The commented lines can be uncommented (and modified, if necessary) + to help you with the rearrangement process. */ + +/* target = 1024x768 */ + +div#header, div#footer, .slide {width: 100%; top: 0; left: 0;} +div#footer {top: auto; bottom: 0; height: 2.5em; z-index: 5;} +.slide {top: 0; width: 92%; padding: 1em 4% 0 4%; z-index: 2;} +div#controls {left: 50%; bottom: 0; width: 50%; z-index: 100;} +div#controls form {position: absolute; bottom: 0; right: 0; width: 100%; + margin: 0;} +#currentSlide {position: absolute; width: 10%; left: 45%; bottom: 1em; + z-index: 10;} +html>body #currentSlide {position: fixed;} + +/* +div#header {background: #FCC;} +div#footer {background: #CCF;} +div#controls {background: #BBD;} +div#currentSlide {background: #FFC;} +*/ diff --git a/presentation/ui/small-white/iepngfix.htc b/presentation/ui/small-white/iepngfix.htc new file mode 100644 index 0000000..2a44681 --- /dev/null +++ b/presentation/ui/small-white/iepngfix.htc @@ -0,0 +1,42 @@ + + + + + \ No newline at end of file diff --git a/presentation/ui/small-white/opera.css b/presentation/ui/small-white/opera.css new file mode 100644 index 0000000..c9d1148 --- /dev/null +++ b/presentation/ui/small-white/opera.css @@ -0,0 +1,8 @@ +/* This file has been placed in the public domain. */ +/* DO NOT CHANGE THESE unless you really want to break Opera Show */ +.slide { + visibility: visible !important; + position: static !important; + page-break-before: always; +} +#slide0 {page-break-before: avoid;} diff --git a/presentation/ui/small-white/outline.css b/presentation/ui/small-white/outline.css new file mode 100644 index 0000000..fa767e2 --- /dev/null +++ b/presentation/ui/small-white/outline.css @@ -0,0 +1,16 @@ +/* This file has been placed in the public domain. */ +/* Don't change this unless you want the layout stuff to show up in the + outline view! */ + +.layout div, #footer *, #controlForm * {display: none;} +#footer, #controls, #controlForm, #navLinks, #toggle { + display: block; visibility: visible; margin: 0; padding: 0;} +#toggle {float: right; padding: 0.5em;} +html>body #toggle {position: fixed; top: 0; right: 0;} + +/* making the outline look pretty-ish */ + +#slide0 h1, #slide0 h2, #slide0 h3, #slide0 h4 {border: none; margin: 0;} +#toggle {border: 1px solid; border-width: 0 0 1px 1px; background: #FFF;} + +.outline {display: inline ! important;} diff --git a/presentation/ui/small-white/pretty.css b/presentation/ui/small-white/pretty.css new file mode 100644 index 0000000..ba988e1 --- /dev/null +++ b/presentation/ui/small-white/pretty.css @@ -0,0 +1,114 @@ +/* This file has been placed in the public domain. */ +/* Following are the presentation styles -- edit away! */ + +html, body {margin: 0; padding: 0;} +body {background: white; color: black;} +:link, :visited {text-decoration: none; color: #00C;} +#controls :active {color: #888 !important;} +#controls :focus {outline: 1px dotted #222;} +h1, h2, h3, h4 {font-size: 100%; margin: 0; padding: 0; font-weight: inherit;} + +blockquote {padding: 0 2em 0.5em; margin: 0 1.5em 0.5em;} +blockquote p {margin: 0;} + +kbd {font-weight: bold; font-size: 1em;} +sup {font-size: smaller; line-height: 1px;} + +.slide pre {padding: 0; margin-left: 0; margin-right: 0; font-size: 90%;} +.slide ul ul li {list-style: square;} +.slide img.leader {display: block; margin: 0 auto;} +.slide tt {font-size: 90%;} + +div#footer {font-family: sans-serif; color: #444; + font-size: 0.5em; font-weight: bold; padding: 1em 0;} +#footer h1 {display: block; padding: 0 1em;} +#footer h2 {display: block; padding: 0.8em 1em 0;} + +.slide {font-size: 1.2em;} +.slide h1 {padding-top: 0; z-index: 1; margin: 0; font: bold 150% sans-serif;} +.slide h2 {font: bold 120% sans-serif; padding-top: 0.5em;} +.slide h3 {font: bold 100% sans-serif; padding-top: 0.5em;} +h1 abbr {font-variant: small-caps;} + +div#controls {position: absolute; left: 50%; bottom: 0; + width: 50%; text-align: right; font: bold 0.9em sans-serif;} +html>body div#controls {position: fixed; padding: 0 0 1em 0; top: auto;} +div#controls form {position: absolute; bottom: 0; right: 0; width: 100%; + margin: 0; padding: 0;} +#controls #navLinks a {padding: 0; margin: 0 0.5em; + border: none; color: #888; cursor: pointer;} +#controls #navList {height: 1em;} +#controls #navList #jumplist {position: absolute; bottom: 0; right: 0; + background: #DDD; color: #222;} + +#currentSlide {text-align: center; font-size: 0.5em; color: #444; + font-family: sans-serif; font-weight: bold;} + +#slide0 {padding-top: 0em} +#slide0 h1 {position: static; margin: 1em 0 0; padding: 0; + font: bold 2em sans-serif; white-space: normal; background: transparent;} +#slide0 h2 {font: bold italic 1em sans-serif; margin: 0.25em;} +#slide0 h3 {margin-top: 1.5em; font-size: 1.5em;} +#slide0 h4 {margin-top: 0; font-size: 1em;} + +ul.urls {list-style: none; display: inline; margin: 0;} +.urls li {display: inline; margin: 0;} +.external {border-bottom: 1px dotted gray;} +html>body .external {border-bottom: none;} +.external:after {content: " \274F"; font-size: smaller; color: #77B;} + +.incremental, .incremental *, .incremental *:after { + color: white; visibility: visible; border: 0; border: 0;} +img.incremental {visibility: hidden;} +.slide .current {color: green;} + +.slide-display {display: inline ! important;} + +.huge {font-family: sans-serif; font-weight: bold; font-size: 150%;} +.big {font-family: sans-serif; font-weight: bold; font-size: 120%;} +.small {font-size: 75%;} +.tiny {font-size: 50%;} +.huge tt, .big tt, .small tt, .tiny tt {font-size: 115%;} +.huge pre, .big pre, .small pre, .tiny pre {font-size: 115%;} + +.maroon {color: maroon;} +.red {color: red;} +.magenta {color: magenta;} +.fuchsia {color: fuchsia;} +.pink {color: #FAA;} +.orange {color: orange;} +.yellow {color: yellow;} +.lime {color: lime;} +.green {color: green;} +.olive {color: olive;} +.teal {color: teal;} +.cyan {color: cyan;} +.aqua {color: aqua;} +.blue {color: blue;} +.navy {color: navy;} +.purple {color: purple;} +.black {color: black;} +.gray {color: gray;} +.silver {color: silver;} +.white {color: white;} + +.left {text-align: left ! important;} +.center {text-align: center ! important;} +.right {text-align: right ! important;} + +.animation {position: relative; margin: 1em 0; padding: 0;} +.animation img {position: absolute;} + +/* Docutils-specific overrides */ + +.slide table.docinfo {margin: 1em 0 0.5em 2em;} + +pre.literal-block, pre.doctest-block {background-color: white;} + +tt.docutils {background-color: white;} + +/* diagnostics */ +/* +li:after {content: " [" attr(class) "]"; color: #F88;} +div:before {content: "[" attr(class) "]"; color: #F88;} +*/ diff --git a/presentation/ui/small-white/print.css b/presentation/ui/small-white/print.css new file mode 100644 index 0000000..9d057cc --- /dev/null +++ b/presentation/ui/small-white/print.css @@ -0,0 +1,24 @@ +/* This file has been placed in the public domain. */ +/* The following rule is necessary to have all slides appear in print! + DO NOT REMOVE IT! */ +.slide, ul {page-break-inside: avoid; visibility: visible !important;} +h1 {page-break-after: avoid;} + +body {font-size: 12pt; background: white;} +* {color: black;} + +#slide0 h1 {font-size: 200%; border: none; margin: 0.5em 0 0.25em;} +#slide0 h3 {margin: 0; padding: 0;} +#slide0 h4 {margin: 0 0 0.5em; padding: 0;} +#slide0 {margin-bottom: 3em;} + +#header {display: none;} +#footer h1 {margin: 0; border-bottom: 1px solid; color: gray; + font-style: italic;} +#footer h2, #controls {display: none;} + +.print {display: inline ! important;} + +/* The following rule keeps the layout stuff out of print. + Remove at your own risk! */ +.layout, .layout * {display: none !important;} diff --git a/presentation/ui/small-white/s5-core.css b/presentation/ui/small-white/s5-core.css new file mode 100644 index 0000000..6965f5e --- /dev/null +++ b/presentation/ui/small-white/s5-core.css @@ -0,0 +1,11 @@ +/* This file has been placed in the public domain. */ +/* Do not edit or override these styles! + The system will likely break if you do. */ + +div#header, div#footer, div#controls, .slide {position: absolute;} +html>body div#header, html>body div#footer, + html>body div#controls, html>body .slide {position: fixed;} +.handout {display: none;} +.layout {display: block;} +.slide, .hideme, .incremental {visibility: hidden;} +#slide0 {visibility: visible;} diff --git a/presentation/ui/small-white/slides.css b/presentation/ui/small-white/slides.css new file mode 100644 index 0000000..82bdc0e --- /dev/null +++ b/presentation/ui/small-white/slides.css @@ -0,0 +1,10 @@ +/* This file has been placed in the public domain. */ + +/* required to make the slide show run at all */ +@import url(s5-core.css); + +/* sets basic placement and size of slide components */ +@import url(framing.css); + +/* styles that make the slides look good */ +@import url(pretty.css); diff --git a/presentation/ui/small-white/slides.js b/presentation/ui/small-white/slides.js new file mode 100644 index 0000000..87c30c6 --- /dev/null +++ b/presentation/ui/small-white/slides.js @@ -0,0 +1,558 @@ +// S5 v1.1 slides.js -- released into the Public Domain +// Modified for Docutils (http://docutils.sf.net) by David Goodger +// +// Please see http://www.meyerweb.com/eric/tools/s5/credits.html for +// information about all the wonderful and talented contributors to this code! + +var undef; +var slideCSS = ''; +var snum = 0; +var smax = 1; +var slideIDs = new Array(); +var incpos = 0; +var number = undef; +var s5mode = true; +var defaultView = 'slideshow'; +var controlVis = 'visible'; + +var isIE = navigator.appName == 'Microsoft Internet Explorer' ? 1 : 0; +var isOp = navigator.userAgent.indexOf('Opera') > -1 ? 1 : 0; +var isGe = navigator.userAgent.indexOf('Gecko') > -1 && navigator.userAgent.indexOf('Safari') < 1 ? 1 : 0; + +function hasClass(object, className) { + if (!object.className) return false; + return (object.className.search('(^|\\s)' + className + '(\\s|$)') != -1); +} + +function hasValue(object, value) { + if (!object) return false; + return (object.search('(^|\\s)' + value + '(\\s|$)') != -1); +} + +function removeClass(object,className) { + if (!object) return; + object.className = object.className.replace(new RegExp('(^|\\s)'+className+'(\\s|$)'), RegExp.$1+RegExp.$2); +} + +function addClass(object,className) { + if (!object || hasClass(object, className)) return; + if (object.className) { + object.className += ' '+className; + } else { + object.className = className; + } +} + +function GetElementsWithClassName(elementName,className) { + var allElements = document.getElementsByTagName(elementName); + var elemColl = new Array(); + for (var i = 0; i< allElements.length; i++) { + if (hasClass(allElements[i], className)) { + elemColl[elemColl.length] = allElements[i]; + } + } + return elemColl; +} + +function isParentOrSelf(element, id) { + if (element == null || element.nodeName=='BODY') return false; + else if (element.id == id) return true; + else return isParentOrSelf(element.parentNode, id); +} + +function nodeValue(node) { + var result = ""; + if (node.nodeType == 1) { + var children = node.childNodes; + for (var i = 0; i < children.length; ++i) { + result += nodeValue(children[i]); + } + } + else if (node.nodeType == 3) { + result = node.nodeValue; + } + return(result); +} + +function slideLabel() { + var slideColl = GetElementsWithClassName('*','slide'); + var list = document.getElementById('jumplist'); + smax = slideColl.length; + for (var n = 0; n < smax; n++) { + var obj = slideColl[n]; + + var did = 'slide' + n.toString(); + if (obj.getAttribute('id')) { + slideIDs[n] = obj.getAttribute('id'); + } + else { + obj.setAttribute('id',did); + slideIDs[n] = did; + } + if (isOp) continue; + + var otext = ''; + var menu = obj.firstChild; + if (!menu) continue; // to cope with empty slides + while (menu && menu.nodeType == 3) { + menu = menu.nextSibling; + } + if (!menu) continue; // to cope with slides with only text nodes + + var menunodes = menu.childNodes; + for (var o = 0; o < menunodes.length; o++) { + otext += nodeValue(menunodes[o]); + } + list.options[list.length] = new Option(n + ' : ' + otext, n); + } +} + +function currentSlide() { + var cs; + var footer_nodes; + var vis = 'visible'; + if (document.getElementById) { + cs = document.getElementById('currentSlide'); + footer_nodes = document.getElementById('footer').childNodes; + } else { + cs = document.currentSlide; + footer = document.footer.childNodes; + } + cs.innerHTML = '' + snum + '<\/span> ' + + '\/<\/span> ' + + '' + (smax-1) + '<\/span>'; + if (snum == 0) { + vis = 'hidden'; + } + cs.style.visibility = vis; + for (var i = 0; i < footer_nodes.length; i++) { + if (footer_nodes[i].nodeType == 1) { + footer_nodes[i].style.visibility = vis; + } + } +} + +function go(step) { + if (document.getElementById('slideProj').disabled || step == 0) return; + var jl = document.getElementById('jumplist'); + var cid = slideIDs[snum]; + var ce = document.getElementById(cid); + if (incrementals[snum].length > 0) { + for (var i = 0; i < incrementals[snum].length; i++) { + removeClass(incrementals[snum][i], 'current'); + removeClass(incrementals[snum][i], 'incremental'); + } + } + if (step != 'j') { + snum += step; + lmax = smax - 1; + if (snum > lmax) snum = lmax; + if (snum < 0) snum = 0; + } else + snum = parseInt(jl.value); + var nid = slideIDs[snum]; + var ne = document.getElementById(nid); + if (!ne) { + ne = document.getElementById(slideIDs[0]); + snum = 0; + } + if (step < 0) {incpos = incrementals[snum].length} else {incpos = 0;} + if (incrementals[snum].length > 0 && incpos == 0) { + for (var i = 0; i < incrementals[snum].length; i++) { + if (hasClass(incrementals[snum][i], 'current')) + incpos = i + 1; + else + addClass(incrementals[snum][i], 'incremental'); + } + } + if (incrementals[snum].length > 0 && incpos > 0) + addClass(incrementals[snum][incpos - 1], 'current'); + ce.style.visibility = 'hidden'; + ne.style.visibility = 'visible'; + jl.selectedIndex = snum; + currentSlide(); + number = 0; +} + +function goTo(target) { + if (target >= smax || target == snum) return; + go(target - snum); +} + +function subgo(step) { + if (step > 0) { + removeClass(incrementals[snum][incpos - 1],'current'); + removeClass(incrementals[snum][incpos], 'incremental'); + addClass(incrementals[snum][incpos],'current'); + incpos++; + } else { + incpos--; + removeClass(incrementals[snum][incpos],'current'); + addClass(incrementals[snum][incpos], 'incremental'); + addClass(incrementals[snum][incpos - 1],'current'); + } +} + +function toggle() { + var slideColl = GetElementsWithClassName('*','slide'); + var slides = document.getElementById('slideProj'); + var outline = document.getElementById('outlineStyle'); + if (!slides.disabled) { + slides.disabled = true; + outline.disabled = false; + s5mode = false; + fontSize('1em'); + for (var n = 0; n < smax; n++) { + var slide = slideColl[n]; + slide.style.visibility = 'visible'; + } + } else { + slides.disabled = false; + outline.disabled = true; + s5mode = true; + fontScale(); + for (var n = 0; n < smax; n++) { + var slide = slideColl[n]; + slide.style.visibility = 'hidden'; + } + slideColl[snum].style.visibility = 'visible'; + } +} + +function showHide(action) { + var obj = GetElementsWithClassName('*','hideme')[0]; + switch (action) { + case 's': obj.style.visibility = 'visible'; break; + case 'h': obj.style.visibility = 'hidden'; break; + case 'k': + if (obj.style.visibility != 'visible') { + obj.style.visibility = 'visible'; + } else { + obj.style.visibility = 'hidden'; + } + break; + } +} + +// 'keys' code adapted from MozPoint (http://mozpoint.mozdev.org/) +function keys(key) { + if (!key) { + key = event; + key.which = key.keyCode; + } + if (key.which == 84) { + toggle(); + return; + } + if (s5mode) { + switch (key.which) { + case 10: // return + case 13: // enter + if (window.event && isParentOrSelf(window.event.srcElement, 'controls')) return; + if (key.target && isParentOrSelf(key.target, 'controls')) return; + if(number != undef) { + goTo(number); + break; + } + case 32: // spacebar + case 34: // page down + case 39: // rightkey + case 40: // downkey + if(number != undef) { + go(number); + } else if (!incrementals[snum] || incpos >= incrementals[snum].length) { + go(1); + } else { + subgo(1); + } + break; + case 33: // page up + case 37: // leftkey + case 38: // upkey + if(number != undef) { + go(-1 * number); + } else if (!incrementals[snum] || incpos <= 0) { + go(-1); + } else { + subgo(-1); + } + break; + case 36: // home + goTo(0); + break; + case 35: // end + goTo(smax-1); + break; + case 67: // c + showHide('k'); + break; + } + if (key.which < 48 || key.which > 57) { + number = undef; + } else { + if (window.event && isParentOrSelf(window.event.srcElement, 'controls')) return; + if (key.target && isParentOrSelf(key.target, 'controls')) return; + number = (((number != undef) ? number : 0) * 10) + (key.which - 48); + } + } + return false; +} + +function clicker(e) { + number = undef; + var target; + if (window.event) { + target = window.event.srcElement; + e = window.event; + } else target = e.target; + if (target.href != null || hasValue(target.rel, 'external') || isParentOrSelf(target, 'controls') || isParentOrSelf(target,'embed') || isParentOrSelf(target, 'object')) return true; + if (!e.which || e.which == 1) { + if (!incrementals[snum] || incpos >= incrementals[snum].length) { + go(1); + } else { + subgo(1); + } + } +} + +function findSlide(hash) { + var target = document.getElementById(hash); + if (target) { + for (var i = 0; i < slideIDs.length; i++) { + if (target.id == slideIDs[i]) return i; + } + } + return null; +} + +function slideJump() { + if (window.location.hash == null || window.location.hash == '') { + currentSlide(); + return; + } + if (window.location.hash == null) return; + var dest = null; + dest = findSlide(window.location.hash.slice(1)); + if (dest == null) { + dest = 0; + } + go(dest - snum); +} + +function fixLinks() { + var thisUri = window.location.href; + thisUri = thisUri.slice(0, thisUri.length - window.location.hash.length); + var aelements = document.getElementsByTagName('A'); + for (var i = 0; i < aelements.length; i++) { + var a = aelements[i].href; + var slideID = a.match('\#.+'); + if ((slideID) && (slideID[0].slice(0,1) == '#')) { + var dest = findSlide(slideID[0].slice(1)); + if (dest != null) { + if (aelements[i].addEventListener) { + aelements[i].addEventListener("click", new Function("e", + "if (document.getElementById('slideProj').disabled) return;" + + "go("+dest+" - snum); " + + "if (e.preventDefault) e.preventDefault();"), true); + } else if (aelements[i].attachEvent) { + aelements[i].attachEvent("onclick", new Function("", + "if (document.getElementById('slideProj').disabled) return;" + + "go("+dest+" - snum); " + + "event.returnValue = false;")); + } + } + } + } +} + +function externalLinks() { + if (!document.getElementsByTagName) return; + var anchors = document.getElementsByTagName('a'); + for (var i=0; i' + + '