DisGeNETCytoscapeApp

IBI Lab [2021]

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USERGUIDE©2010-2021,IntegrativeBiomedicalInformaticsIntegrativeBiomedicalInformaticsLaboratoryResearchGrouponBiomedicalInformatics(GRIB)IMIM-HospitaldelMarMedicalResearchInstituteUniversitatPompeuFabra(UPF)PRBBDr.Aiguader88,E-08003Barcelona(SPAIN)

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TheDisGeNETappisdistributedundertheGNUGPL3.0license.MoredetailsabouttheGNUGeneralPublicLicense3.0isavailablehere.

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DisGeNETCytoscapeAppUserGuide(version7.0.x)

1. Installationguide.........................................................................................................................5a. DownloadandinstalltheDisGeNETCytoscapeApp...............................................5

2. BriefdescriptionofDisGeNET...............................................................................................8a. Originaldatasources.............................................................................................................8b. RepresentingDisGeNETdatausingnetworks...........................................................8c. Vocabularymapping..............................................................................................................8d. DisGeNETgene-diseaseassociationtypeontology.................................................9

3. Tutorial..........................................................................................................................................10a. Basicfunctions......................................................................................................................10i. Generategene-diseasenetworks.............................................................................10ii. Generatevariant-diseasenetworks........................................................................11iii. CreatenetworksbyDisGeNETassociationtype..........................................12iv. Createnetworksbydiseaseclass............................................................................12v. Createnetworksbygene,disease,orvariant.....................................................14vi. MultipleentitysearchintheDisGeNETApp.......................................................14

b. Advancedfunctions............................................................................................................19i. Colouringnodesbydiseaseclass.............................................................................19ii. DisGeNETexpand...........................................................................................................20iii. DisGeNETLinkouts...................................................................................................22iv. AnnotatingforeignnetworkswithDisGeNETdata..........................................23

c. DisGeNETautomation.......................................................................................................29i. UsingtheDisGeNETautomationinR.....................................................................31ii. UsingtheDisGeNETautomationinpython.........................................................32

4. TheSQLitedatabase................................................................................................................335. ThenodeandedgetablesintheCytoscapeTablePanel.........................................346. Annexes.........................................................................................................................................367. Citation..........................................................................................................................................418. References...................................................................................................................................429. Contact...........................................................................................................................................4310. Funding....................................................................................................................................4411. License......................................................................................................................................4512. Aboutthisdocument..........................................................................................................45

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1. Installationguide

a. DownloadandinstalltheDisGeNETCytoscapeApp

Equipment:apersonalcomputerwithInternetaccessandanInternetbrowser.OperatingSystem:TheDisGeNETAppandCytoscapearesupportedonWindows(Windows7,Windows8,Windows10),MacandLinux.Java standard edition: Version 1.8 or higher is required (available athttp://www.java.com/).CytoscapeversionDisGeNETiscompatiblewiththeCytoscape3.xversions.WerecommendCytoscapeversions(3.6.x)orlater.Thestepsfordownloadingandinstalling the latest version of Cytoscape are described athttp://www.cytoscape.org/.Appversion:7.xTheDisGeNETappneedstobeinstalledfromtheCytoscapeAppStore.● GotoAppsintheCytoscapemenu● ClickonAppManager● typedisgenetonthesearchbox● clickontheresult,andthenclickinstall(Figure1)●

Figure1:InstallingtheDisGeNETappfromtheCytoscapeAppStore

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Then, go again to Apps in the Cytoscapemenu, and click on DisGeNET-> StartDisGeNET(Figure2).

Figure2:StartingtheDisGeNETapp

ThefirsttimethattheDisGeNETappisstarted,itwillaskforthedirectoryofthedatabasefile.Ifthedatabasefiledoesnotexistinthedirectory,itwillproceedtoautomatically download it. Choose a directory where the database will bedownloadedandunpacked(disgenet_2020.db~1.3Gb).Forexample,Downloads(Figure3).Foradetaileddescriptionofthedatabase,seesection4.

Figure3:ConfigureDisGeNETappforthefirstrun

Amessageof“Databasefiledoesnotexist.Goingtodownloadit”willappear(Figure4).

Figure4:ConfigureDisGeNETdatabaseforthefirstrun

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Thedownloadmighttakeseveralminutes.Please,bepatient.Whenit finishes,anew message will appear “Database downloaded correctly.” The app will startafterwards.Thisalsotakesacoupleofminutes.TheappisreadytobeusedwhentheDisGeNETControlPanelappears(Figure5).

Figure5:TheDisGeNETappcontrolpanel

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2. BriefdescriptionofDisGeNETDisGeNETisadiscoveryplatformthatintegrateshumangeneandvariant-diseaseassociations fromvarious expert curateddatabases and the scientific literature,and includes Mendelian, rare, complex and environmental diseases, as well asabnormalphenotypesandtraits(1–3).

a. OriginaldatasourcesInDisGeNET,theGDAsaregroupedaccordingtotheirtypeandlevelofcuration:CURATED(containinggene-diseaseassociationsfromhumanexpertcurateddatasources), ANIMAL MODELS (containing gene-disease associations from animalmodelrepositories), INFERRED(containinggene-diseaseassociationsfromHPO,GWASDB and GWASCAT), and ALL (including CURATED, ANIMAL MODELS,INFERRED,anddataderivedfromtextminingthebiomedicalliterature).DisGeNETVDAs are grouped according to their type and level of curation: CURATED(containingvariant-diseaseassociationsfromhumanexpertcurateddatasources),and ALL (including CURATED data and data derived from text mining thebiomedical literature). For the up-to-date list and description of data sourcesavailable inDisGeNET,pleasevisit theDisGeNETDiscoveryPlatformWebsiteathttp://disgenet.org/dbinfo,section“OriginalDataSources”.

b. RepresentingDisGeNETdatausingnetworks

Gene-disease associations (GDAs), and variant-disease associations (VDAs) arecollectedfromseveralsources.Thesourcedatabasesusedifferentvocabularies.InordertomergeallGDAandVDAsandtopresenttheminonecomprehensivegene-disease,orvariant-diseasenetwork,we(i)mappedgeneidentifierstoNCBIEntrezGeneidentifiersifnecessary,(ii)mappeddiseasevocabularytermstotheUnifiedMedicalLanguageSystem® (UMLS®)ConceptUnique Identifiers (CUIs), and (iii)integratedassociationsthroughtheDisGeNETgene-diseaseassociationontology(seesection2.4).The data contained in DisGeNET is represented using bipartite graphs. TheDisGeNETbipartitegraphhastwotypesofvertices(genesorvariantsanddiseases)andtheedgesconnecttheverticesofdifferenttypes(e.g.agenewithadisease).Thesebipartitegraphsaremultigraphsinwhichtwoverticesmightbeconnectedbymore than one edge. Thesemultiple edges represent themultiple evidencesreportingtheGDAorVDA.

c. VocabularymappingFortheup-to-datedescriptionofthediseaseandgenevocabularymappingsused

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in DisGeNET please visit the DisGeNET Discovery Platform Website at:http://disgenet.org/dbinfo,section“DataAttributes”.

d. DisGeNETgene-diseaseassociationtypeontology

We have developed the DisGeNET gene-disease association type ontology torepresent inauniformandstructuredwaythetypesofrelationsbetweengenesanddiseases found intheoriginaldatasources(Figure6).Forthedetailsof theontologyusedtodescribegene-diseaseassociationsinDisGeNETpleasevisittheDisGeNET Discovery Platform Website at: http://disgenet.org/dbinfo, sectionDisGeNETgene-diseaseassociationtypeontology.

Figure6:DisGeNETgene-diseaseassociationtypeontology

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3. TutorialTheDisGeNETCytoscapeappisdesignedtovisualize,queryandanalyseanetworkrepresentationofthegene-diseaseandthevariant-diseaseassociationscontainedinDisGeNET.Theappusesthecurrentversion(v7.0)oftheDisGeNETthatcontains1,134,942 gene-disease associations (GDAs), between 21,671 genes and 30,170diseases, disorders, traits, and clinical or abnormal human phenotypes, and369,554 variant-disease associations (VDAs), between 194,515 variants and14,155diseases,traits,andphenotypes.TheDisGeNETapp(versions5.1orlater)includestheDisGeNETCytoscapestyleby default. Additionally, the style can be downloaded fromhttp://disgenet.org/app,section“Additionalfiles”.

a. BasicfunctionsTheDisGeNETAppControlPanel(Figure5)allowsadjustingtheparametersofthequeriesinordertocreatedifferenttypesofnetworks.ThepanelcontainstwotabstogeneratetheGeneDiseaseNetwork,andtheVariantDiseaseNetwork.TheGeneDiseaseNetwork tab isdisplayedbydefault. In this tab, differentGDAnetworkscanbegeneratedbyselectingdifferentdataSources,AssociationTypesand/orDiseaseClassesfromtheirrespectivedrop-downmenus.TheGDAnetworksmaybealsofilteredusingacut-offvalueoftheDisGeNETscore,and/orEvidenceIndex(EI)andEvidenceLevel(EL).Inaddition,GDAnetworkscanbebuiltaroundspecificdisease(s)orgene(s)of interestusing theSearch boxesprovided in thepanel.Using theVariant-DiseaseNetwork,differentVDAnetworkscanbegeneratedbyselectingdifferentdataSources,AssociationTypesand/orDiseaseClassesfromtheirrespectivedrop-downmenus.TheVDAnetworksmaybealsofilteredusingacut-off value of the DisGeNET score, and/or Evidence Index (EI). In addition, VDAnetworkscanbebuiltaroundspecificdisease(s),gene(s),orvariant(s)ofinterestusingtheSearchboxesprovidedinthepanel.

i. Generategene-diseasenetworksIn order to obtain aGDAnetwork containingdata fromone specific source, forexample, CURATED data, which includes information from all expert curateddatabasesinourdatabase(CGI,ClinGen,GenomicsEngland,UniProt,CTD_human,PsyGeNET,andOrphanet),selecttheSourceofinterest(CURATED),andpressthebuttonCreateNetwork.TheGDAnetworkcontains20,884nodesand151,277edges.ApplyaCytoscapelayoutalgorithmtogeneratetheviewofchoice,e.g.selectthelayoutOrganic.Formore information on the layout styles, seehttp://apps.cytoscape.org/apps/yfileslayoutalgorithms. Once the network isobtained,specificinformationonthenodesandtheirrelationshipscanbeexplored

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usingtheCytoscapeTablePanel(atthebottom,right)(Figure7).

Figure7:TheCURATEDGDAnetwork

ii. Generatevariant-diseasenetworksToobtainaVDAnetworkcontainingdatafromonespecificsource,forexample,theGeneticAssociationDatabase,selecttheVariantDiseaseNetworktab,thesourceofinterest(UNIPROT),andpressthebuttonCreateNetwork.TheresultsareshowninFigure8.Thenetworkiscomposedof26,145nodesand182,304edges.

Figure8:TheUNIPROTVDAnetwork

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iii. CreatenetworksbyDisGeNETassociationtypeThe DisGeNET App allows searching by different categories of gene-diseaseassociationtypes,asdescribedbytheDisGeNETassociationtypeontology(Figure6).TocreateaGDAnetworkfromCURATEDdatarestrictedtoassociationtype“CausalMutation”,selecttheSource,(forinstanceCURATED).ChooseCausalMutation,fromtheAssociationTypedropdownmenu,andpressCreateNetwork.TheGDAnetworkobtainedcontains5876nodesand6560edges(Figure9).Could you find the gene in the network carrying CausalMutations for the largestnumberofdiseases?Hint:ordergenesbythecolumnnrAssociatedDiseases

Figure9:TheCURATEDGDAnetworkforCausalMutations

iv. CreatenetworksbydiseaseclassNetworkscanalsobecreatedbyrestrictingtoaspecifictypeofMeSHdiseaseclass.ThediseaseclassificationisbasedontheDiseasesbranch(C)andthreecategories(F01, F02, and F03) of the Psychiatry and Psychology Branch (F) of the MeSHhierarchy.TogenerateanetworkofANIMALMODELSdata,containingonlyNutritionalandMetabolicDiseases,SelecttheSource(ANIMAL_MODELS),andchoosetheDiseaseClass(NutritionalandMetabolicDiseases)fromtheDiseaseClassdropdownmenu.Then,press thebuttonCreateNetwork (Figure10).ThisGDAnetworkhas1510nodesand3087edges.Which is thediseasewith the largestnumberofassociatedgenes in thisnetwork?(Hint:usethenetworkanalyzerutilityfromCytoscapeToolsMainMenu)

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Figure10:TheGDAnetworkforNutritionalandMetabolicDiseasesinanimalmodelsofdisease

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v. Createnetworksbygene,disease,orvariantThe Search option included in the DisGeNET control panel can also be used togenerate different types of networks for a single disease, gene, or variant. ThissearchmayalsobefilteredbySource,AssociationType,DiseaseClass,andScore.Forexample,thefigure15showstheresultsforthesearchbyasinglegene,themethyl-CpGbindingprotein2gene(MECP),filteringbydiseaseclassMentalDisordersinthecurateddatainDisGeNET(Figure11).

Figure11:GDAnetworkcontainingthemetabolicdiseasesassociatedwiththemethyl-CpGbindingprotein2

gene(MECP2)inDisGeNETCURATED.

vi. MultipleentitysearchintheDisGeNETAppTheSearchoptioncanalsobeusedto:● Generateanetworkaroundagroupofdiseasesorgenes,matchingakeyword● Generate a network for a list of genes, diseases or variants, and their

combinations

a. SearchbyadiseasematchingakeywordTobuildaGDAnetworkcontainingDisGeNETdatafromCTD(humandata)forallthetypesofAlzheimerDiseaseinthisdatabase,selecttheSource,CTD_humanandwrite in the disease Search box ‘*alzheimer*’ to create a network based on thiskeywordinthediseasename.Then,pressCreateNetwork(Figure12).HowmanydifferentsubtypesofAlzheimer’sDiseaseareincludedinDisGeNET(CTDhumandata)?HowmanygenesareassociatedwithAlzheimer'sDisease(C0002395)?

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Figure12:GDAnetworkcontainingallsubtypesofAlzheimerDiseaseinCTD,humandata

Thisnetworkcanbefurtherfilteredbygene.Forexample,togeneratethenetworkofalltheAlzheimersubtypes,andtheamyloidbetaprecursorprotein(APP)gene,typeAPPintheGeneSearchBox,andpressCreateNetwork(Figure13).AnetworkwithallsubtypesofAlzheimerassociatedtotheAPPgeneiscreated.Each edge in the GDANetwork represents the supporting evidence for a gene-diseaseassociationuniquelydefinedbythesource,oneassociationtype,andonepublication. The colour of each edge distinguishes the association type.Use theEdgeTableintheTablePaneltoexploretheevidenceforeachassociation.WhatisthescoreoftheAPP-Alzheimer’sDiseaseassociation?

Figure13:TheGDAnetworkfortheamyloidbetaprecursorprotein(APP)andallsubtypesofAlzheimerDisease

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b. SearchbyalistofgenesTobuildaGDAnetworkassociatedwithalistofgenes,enterintheGeneSearchBoxthelistofgenesseparatedby“;”andpressCreateNetwork.Figure14showstheresults of querying DisGeNET CURATED data for a list of potassium channels:KCNE1;KCNE2;KCNH2;KCNG1.Howmanygenesappearinthenetwork?

Figure14:TheCURATEDGDAnetworkforthegenesKCNE1;KCNE2;KCNH2

c. Searchbyalistofvariants

AsimilarprocedurecanbefollowedtoqueryDisGeNETforthediseasesassociatedwith a list of variants. Go to the Variant Disease Network tab, select source“CURATED”andtypethevariantsseparatedby“;”intheSearchVariantandthenpressCreateNetwork.Figure15showstheresultsofqueryingthefollowinglistofvariants:rs121907927;rs373661718;rs121907927;rs780356070;rs200015827;rs121907928;rs757259413;rs121907919;rs121907928

Figure15:TheCURATEDVDAnetworkforvariants

rs121907927;rs373661718;rs121907927;rs780356070;rs200015827;rs121907928;rs757259413;rs121907919;rs121907928

Noticethatinthisnetwork,thegenesassociatedwiththevariantscanbedisplayed

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by clickingon thebox “Showassociatedgenes” in theDisGeNET control panel(Figure16).Applytheradiallayouttoobtainasimilarvisualization.

Figure16:TheCURATEDVDAnetworkforvariants

rs121907927;rs373661718;rs121907927;rs780356070;rs200015827;rs121907928;rs757259413;rs121907919;rs121907928andtheirassociatedgenes

d. Searchbyalistofdiseases

Go to theGeneDiseaseNetwork taband in the SearchDiseasebox,enter the listfollowinglistofdiseases:C0268337;C0268342;C0268336;C0268335;C0268338;C0013720.Filterbyscore>0.3,andthenpressCreateNetwork(Figure17).

Figure17:TheGDAfordiseasesC0268337;C0268342;C0268336;C0268335;C0268338;C0013720withscore>=0.4

TheinputtermsintheSearchDiseaseboxcanbecombined,usingUMLSCUIs,diseasenames,oraregularexpression.Forexample,thefollowinglistC0002395;Schizophrenia;*Parkinson*,willretrievetheGDAnetworkforAlzheimer’sDisease,Schizophrenia,andallsubtypesofParkinsondiseaseinDisGeNET.SeetheresultsofthesearchinDisGeNETCURATEDdatainFigure18.

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Figure18:TheCURATEDGDAnetworkfordiseases:C0002395;Schizophrenia;*Parkinson*withscore>=0.5

NoticethattheappreturnsanetworkifatleastoneoftheentitiesinthequeryisincludedinDisGeNETdata.

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b. Advancedfunctionsi. Colouringnodesbydiseaseclass

TheDisGeNETappallowscolouringthenodesofanetworkaccordingtotheMeSHdiseaseclassification.Inthecaseofdiseases,thecolouringisbasedonthediseaseclassannotationofthediseasenode.Diseasesbelongingtomorethanonediseaseclasswillappearwithmorethanonecolour.Inthecaseofgenesandvariants,theMeSHdiseaseclassisassignedfromthedisease(s)associatedtothem.Forexample,intheGeneDiseaseNetworktab,searchforINSR;INS;LEP;LEPRinthegenesearchbox,usingthesourceANIMALMODELS,AnyassociationtypeandAnyDiseaseClass,andscore>=0.Press“CreateNetwork”(Figure19).

Figure19:GDAnetworkforINSR;INS;LEP;LEPRinanimalmodels(score≥0).

Oncethenetworkiscreated,clickonColournodeswithdiseaseclass,andallthenodesofthediseasesinthenetworkwillbecolouredaccordingtotheirMeSHdiseaseclasses,whilethegeneswillbecolouredaccordingtotheclassesoftheirassociateddiseases.ThecolourforeachdiseaseclassisdisplayedintheDiseaseClassLegendshownattherightside.Theborderofthenodeskeepstheoriginalcolourindicatingifitrepresentsadisease,ageneoravariant.NoticethatifsomediseasesdonothaveMeSHdiseaseclass,theywillbecolouredingray(Figure20).

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Figure20:GDAnetworkforINSR;INS;LEP;LEPR,inanimalmodels,colouredaccordingtoMeSHdiseaseclasses.

ii. DisGeNETexpandTheDisGeNETexpandfunctionallowstoretrieveallthedataavailableforaspecificnodeinanetwork.Theexpandfunctionisparticularlyusefulwhenaninitialsearchonasingledatabase(e.g.UniProt)isperformed,andoncethenetworkisobtained,youwanttoknowifthereareotherassociationsinthewholeDisGeNETdatabase(namelyALLdataset).ThefunctioncanbeusedtocreateanewDisGeNETnetworkusingtheselectednode(s)forthequeryortoexpandtheexistingnetworkwithnodesandedgesfoundinDisGeNETALL.Currently,thefunctionoffersthefollowingoptions:

- OnaGDAnetwork,appliedtoagene,itwillretrievethediseasesassociatedwiththegenefromALLdata.

- OnaGDAnetwork,appliedtoadisease,itwillretrievethegenesassociatedwiththediseasefromALLdata.

- OnaVDAnetwork,appliedtoavariant,itwillretrievethediseasesassociatedwiththevariantfromALLdata.

- OnaVDAnetwork,appliedtoadisease,itwillretrievethevariantsassociatedwiththediseasefromALLdata.

- OnaVDAnetwork,appliedtoageneassociatedwithavariant,itwillcreateanewGDAnetworkwiththediseasesassociatedwiththegenefromALLdata.

ForanexampleonhowtoapplytheDisGeNETexpandfunctiontotheGDAnetworkforgeneAlzheimer’sDiseaseandAPOEfromCURATEDdata,seeFigure25.Right-clickonthenodeofinterest,inthiscasetheAPOEnode,andgoto“Apps->DisGeNET->Expand”.Youhavethentoselecteither“Expandcurrentnet”or“Createnewnet”.The“SetParameters”boxwillappeartoselectthedatabase(Figure21).

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Figure21:Theexpandfunctionmenu,onthenodeviewcontextmenuforthegeneAPOEandAlzheimer’s

Disease.

The“SetParameters”boxallowsfilteringtheexpandednetworkbydatasource,byscore,andbyattributessuchasthediseaseclass,andtheassociationtype.Selectthedatabase“CURATED”,forexample,andDiseaseclassequalto“NervousSystemDiseases”.TheresultsareshowninFigure22.

Figure22:TheSetParametersBoxassociatedtotheexpandfunction

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Figure23:TheexpandednetworkforgeneAPOE(CURATEDdata),anddiseaseclass“NervousSystemDiseases”,

displayedusingtheorganiclayout.

iii. DisGeNETLinkouts

1. LinkOutsforthenodesInordertogetmoreinformationaboutaspecificgene,diseaseorvariantfromaDisGeNETnetwork,youcanusetheLinkOutfunctiontothereferencedatabases(NCBIforGenes,LinkedLifeDataforUMLSCUIsanddbSNPforSNPs).TheLinkOutfunctionisavailableinthenodecontextmenu,whichcanbeaccessedbyright-clickingaselectednode(Figure24Figure23).Theavailablelinkoutsarespecifictothenodetype.

Figure24:TheLinkOutfunctionmenu,onthenodeviewcontextmenu,forthegeneAPOE.

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2. LinkOutsfortheedgesTheusercanalsoexplorethepublicationsupportingtheGDA,orVDA,byclickingontheedgeconnectingthepairofinterest,andaccessingtheLinkOuttoNCBIPubmed(Figure25)

Figure25:TheLinkOutfunctionmenu,ontheedgeviewcontextmenu,fortheassociationbetweenAlzheimer’s

DiseaseandthegeneAPOE.

iv. AnnotatingforeignnetworkswithDisGeNETdata

TheDisGeNETCytoscapeAppalsoallowsannotatingnetworksgeneratedbyotherapplicationsoruploadedbytheuser.Toaccessthefunction,rightclickonanemptyspaceofthenetworkview,toopenthenetworkcontextmenu.Goto"App->DisGeNET"andselectthedesiredfunction:

AnnotateforeignproteinnetworkswithDisGeNETdiseasesItispossibletoannotateaforeignnetworkcontaininggenesusingoneofthefollowinggeneidentifiers:

- GeneNCBIidentifier- Genesymbol

Toannotateanexternalnetwork,wewilluseasanexampleoneofthenetworksintheCytoscapeStarterPanel.TodisplaytheStarterPanel,gotothemainCytoscapemenu,andclick"View->showStarterPanel".Clickonthenetwork"TCGAColorectalCancer"toopenthesession.Chooseasetofnodesofthenetwork(intheexampleweselectedthefirstneighborsofthegenePLK1)andgenerateanewnetwork("File->New->Network->FromSelectednodes,alledges").Thisisdonetoreducethesizeoftheresultingnetwork.Afterthenewnetworkiscreated,rightclickonanemptyspaceofthenetworkview,toopenthenetworkcontextmenu.Goto"App->DisGeNET->AnnotategeneswithDisGeNET->Genes->Annotategeneswithdiseasesfromtheselectedsource"(Figure26).Thatwilldisplaythe"SetParameters"Box(Figure27).

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Figure26:SubNetworkextractedfromtheexamplesessionAfinityPurification.cys

Noticethatinthiscase,"SetParameters"Boxincludesanewfield,toselectthenameofthecolumncontainingthegeneidentifier(NCBIidentifierorSymbol).Additionally,youmightselectthesourceoftheannotation,arangeofscore,orthediseaseclass.Intheexample,weusedCURATEDand“Neoplasms”.

Figure27:TheSetParametersBoxassociatedtotheAnnotateexternalnetworksfunction

AnewGDAnetworkwillbecreatedwiththediseasesassociatedwiththegenesinthenetworkaccordingtotheselectedsource(intheexample,datafromCURATEDsources).TheresultsareshowninFigure28.

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Figure28:TheCURATEDGDAnetworkforthegenesfromtheexternalnetwork

AnnotateforeignvariantnetworkswithDisGeNETdiseasesSimilarly,anetworkcontainingvariantsidentifiedbythedbSNPidentifierscanbeannotated.Forexample,copythetableinAnnexes,containingthevariantswiththeirchromosomes,takenfromtheSupplementarytable4fromreference(5),apublicationdescribingaGWASthatidentified143riskvariantsfortype2diabetes.Saveitasatxtfileinadocument.Inordertouncoverwhichofthereportedvariantshavealreadybeenassociatedtoothertraits,forexampleintheGWASCatalog,followthesesteps:CreateanewnetworkfromthefilebyclickinginthemainmenuofCytoscape“File->Import->Network->file”.TheresultshouldbeanetworkliketheoneinFigure29.Then,rightclickonanemptyspaceofthenetworkview,toopenthenetworkcontextmenu.Goto"App->DisGeNET->Variants->Annotatevariantswithdiseasesfromtheselectedsource".The“Setparameters”Boxwillbeshown,toselectthenameofthecolumnwiththedbSNPidentifier,andthesourceofthedata.TheresultsoftheannotationusingGWAScatalogdataareshowninFigure16.

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Figure29:TheannotatedVDAnetworkfromDisGeNETAllsources

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Annotatingadrug-targetnetworkwithDisGeNETdiseasesTheDisGeNETCytoscapeAppalsoallowsannotatingnetworksgeneratedbyotherapplicationsoruploadedbytheuser.Wewillgenerateadrug-targetnetworkforthedrug5-fluorouracilfromtheSTITCHdatabaseandannotatethetargetswithdiseaseinformation.

1. GototheSTITCHdatabase(http://stitch.embl.de/)andsearchthetargetsof5-fluorouracilinhumans.

2. Retrievethenetworkofdrugtargetsselectingthesources:“Experiments”,“Databases”.Thisshouldresultinanetworkof5-FUand10proteins.

3. DownloadthenetworkfileinTSVformatandimportitinCytoscapeasadrug-targetnetwork.Thenetworkfileshouldlooklikethis,withoneinteractionperrowofthetable:

node1 node2 combined_score

CASP8 CASP3 0.998 DPYD 5-fluorouracil 0.995 BAX TP53 0.993 UPP1 5-fluorouracil 0.992 UPP2 5-fluorouracil 0.963 TYMS 5-fluorouracil 0.960 BAX 5-fluorouracil 0.900 CYP2A6 5-fluorouracil 0.900 TP53 5-fluorouracil 0.900 CASP8 5-fluorouracil 0.900 CASP3 5-fluorouracil 0.900 DHFR 5-fluorouracil 0.900 UPP1 CYP2A6 0.899 UPP2 DPYD 0.899 DPYD UPP1 0.899 DHFR TYMS 0.899 DPYD CYP2A6 0.899 UPP2 CYP2A6 0.899 DHFR TP53 0.575 CASP3 BAX 0.569 CASP8 TP53 0.569 CASP8 BAX 0.569

ImportthenetworkbyclickingonFile→Import→Network→File.Note:becarefultoselectthepropercolumnsasnodesandedgesinyournetwork.OncethedatahasbeenimportedinCytoscape,adrug-targetnetworkfor5-FUwillbeobtainedanddisplayedinCytoscape(Figure30):

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Figure30:Importednetworkrepresentingthedrugtargetsof5-FU

Questions:

● Howmanytargetsareinthe5-FUnetwork?● Whatisthedegreeofthe5-FUnode?

Next,annotatethetargets(genes)withcurateddiseaseinformationfromDisGeNET.Toaccesstheannotatefunction,rightclickonanemptyspaceofthenetworkview,toopenthenetworkcontextmenu.Goto"App->DisGeNET->Genes->Annotategeneswithdiseasesfromtheselectedsource"(Figure31).

Figure31:Annotatingexternalnetworkswithdiseases

Then, inthe"SetParameters"Boxchoosethecolumn“name”.Asaresult,anewGDAnetworkforthetargetsof5-FUwillbegenerated(Figure32).

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Figure32:GDAnetworkofthetargetsof5-FU

Generateasub-networkofGDAsforTYMS,onethe5-FUtargets.Questions:

● WhatisthedegreeofTYMSintheGDAnetwork?● Whatclassesofdiseasesarerepresented intheTYMSGDAnetwork?Tip:

inspect theMeSH disease classes in the Node Table or by colouring thenetworkbydiseaseclass

c. DisGeNETautomationTheCytoscapeAutomationisasetoftoolsthatallowsuserstocreateworkflowsexecutedentirelywithinCytoscapeorbyexternaltools(suchasRStudioorJupyter).TheDisGeNETAutomationAPIallowsqueryingtheCytoscapeDisGeNETappfromanexternalenvironmentsuchasR,andPython,usingRESTcalls.TheDisGeNETappincludesanautomationmodulewithasetofRESTendpoints.ThedocumentationoftheendpointsisavailableattheSwaggerpageofCytoscapethatcanbeaccessedbygoingtotheCytoscapemenuandclicking“Help->Automation->CyRestAPI”.TheAPIisaccessibledirectlythroughtheSwaggeruserinterfacewithinCytoscapeorbyusinganyREST-enabledclient.Figure33showsalltheavailableendpoints,includingthoseavailablebydefaultthroughCytoscape,andtheoneprovidedbytheCytoscapeappsintheuserinstallationofCytoscape.Weprovideexamplesofscriptsathttp://disgenet.org/app.

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Figure33:TheswaggerinterfacepagefortheCyRestAPI.

ExpandingtheDisGeNET-AutomationmenuwillshowtheRESTendpointscorrespondingtoDisGeNET(¡Error!Noseencuentraelorigendelareferencia.)

Figure34:TheavailableDisGeNETRESTendpoints.

Important:Inordertoruntheautomationscripts,youfirstneedtolaunchCytoscape.

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i. UsingtheDisGeNETautomationinRTousetheDisGeNETautomationinR,weprovideanRscriptthatcanbefoundathttp://www.disgenet.org/static/disgenet_ap1/files/current/disGeNETAutomation.RTogenerateaVDAnetwork,youcanusethefollowingRline:variantDisResult<-disgenetRestCall("variant-disease-net",variantDisParams)Previously,youneedtodefinetheparametersofyoursearch,forexample:

variantDisParams<-list(source="UNIPROT",assocType="GeneticVariation",diseaseClass="Neoplasms",diseaseSearch="",geneSearch="",variantSearch="",initialScoreValue="0.0",finalScoreValue="1.0",showGenes="true"

)ByexecutingthedisgenetRestCallfunction,theresultsofthequerywillbedisplayedinCytoscape.ThefunctiondisgenetRestCall(netType,params)createstheurlusingthefunctiondisgenetRestUrlandexecutestheRESTcalltothedesiredRESTpointandwiththenetworkparametersprovidedbytheuser,thefunctionreturnstheresultsinalistcontainingamessagewiththeresultoftheoperation,andalistcontaininginformationofthenetwork.

- netType:oneofthefollowing:gene-disease-netorvariant-disease-net- netParams:theonlyrequiredfieldisthesource.(seeexamplebelow)

ExampleofnetParamslistforthegene-diseasenetwork.

geneDisParams<-list(source="UNIPROT",assocType="GeneticVariation",diseaseClass="Neoplasms",diseaseSearch="",geneSearch="",initialScoreValue="0.0",finalScoreValue="1.0"

)ThefunctiondisgenetRestUrl(netType,host,port,version)createstheRESTurlusingthefollowingparameters:

- netType:oneofthefollowing:gene-disease-netorvariant-disease-net- host:thehost/ipwheretheRESTpointisplaced(bydefault,localhost).- port:theportinwhichtheRESTpointislistening(bydefault,1234).- version:theversionoftheRESTpoint,shouldmatchtheversionofyour

DisGeNETApp(bydefault,thelatestversion).ThisfunctionisreadytobeusedwiththedefaultCytoscapeautomationsetup

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insidethedisgenetRestCallfunction.

ii. UsingtheDisGeNETautomationinpython

TousetheDisGeNETautomationinPython,anexampleofscriptcanbefoundathttp://www.disgenet.org/static/disgenet_ap1/files/current/disgenet-automation.pyThescriptcontainsfourfunctionsthatallowcallingtheautomationmodule,andsimplifytheaccessofthedata.ThefunctiondisgenetRestUrl(netType,host,port,version)createstheRESTurlusingthefollowingparameters:

- netType:oneofthefollowing:gene-disease-netorvariant-disease-net- host:thehost/ipwheretheRESTpointisplaced(bydefault,localhost).- port:theportinwhichtheRESTpointislistening(bydefault,1234).- version:theversionoftheRESTpoint,shouldmatchtheversionofyour

DisGeNETApp(bydefault,thelatestversion).ThisfunctionisreadytobeusedwiththedefaultCytoscapeautomationsetupinsidethedisgenetRestCallfunction.ThefunctiondisgenetRestCall(netType,params)createstheurlusingthefunctionaboveandexecutestheRESTcalltothedesiredRESTpointandwiththegivennetparameters,thefunctionreturnstheresultsinalistcontainingamessagewiththeresultoftheoperation,andalistcontaininginformationofthenetwork.

- netType:oneofthefollowing:gene-disease-netorvariant-disease-net- netParams:theonlyrequiredfieldisthesource.(seeexamplebelow)

ExampleofnetParamsforthegene-diseasenetwork.

geneDisParams={ "source":"UNIPROT", "assocType":"GeneticVariation", "diseaseClass":"Neoplasms", "diseaseSearch":"", "geneSearch":"", "initialScoreValue":"0.0", "finalScoreValue":"1.0"}

ForfunctionsprintHashandprintOperationResultseethefunctiondocumentationtogetmoreinformation.

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4. TheSQLitedatabaseTheDisGeNETappqueriesalocalversionofDisGeNETdatathatisdownloadedasanSQLitedatabase.EachversionoftheAppcorrespondstoaspecificversionoftheSQLitedatabase.ThediagramofthedatacontainedintheSQLitedatabase(version7.0)correspondingtothecurrentversionoftheApp(7.x),canbeexploredinFigure35.

Figure35:TherelationalschemaoftheDisGeNETSQLitedatabase(version7.0)

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5. ThenodeandedgetablesintheCytoscapeTablePanel

Intables1-3,weshowabriefdescriptionofeachfieldinthenodeTable,andedgeTable,inthe"TablePanel"ofCytoscapeforthedifferentnetworksgeneratedbytheDisGeNETapp.Formoreinformation,visithttp://www.disgenet.org/dbinfo.Table 1: Edge attributes in the gene-disease network Name Description

interaction Uniqueidentifierforthisassociation.

source Originaldatabaseinwhichthisgene-diseaseassociationisreported.

associationType AssociationtypeoftheGDAaccordingtotheDisGeNETassociationtypeontology(seesection2.4).

sentence Arepresentativesentencefromthepublicationdescribingtheassociationbetweenthegeneandthedisease(Ifarepresentativesentenceisnotfound,weprovidethetitleofthepaper).

pmid PubMedidentifierofthepublicationsupportingthereportedgene-diseaseassociation,ifavailable.

score TheDisGeNETGDAscorerangesfrom0to1,andtakesintoaccountthenumberandtypeof sources (level of curation, model organisms), and the number of publicationssupportingtheassociation.

EI TheEvidenceIndexfortheGDA,thatindicatestheexistenceofcontradictoryresultsinpublication.

EL TheEvidenceLevelmeasuresthestrengthofevidenceofagene-diseaserelationship

Table 2: Node attributes in the gene-disease network Name Description

name Nameofthenode,correspondingtoNCBIidentifierforgenes,andUMLSCUIsfordiseases

nodeType Thetypeofnode(geneordisease).

diseaseId UMLS®CUIofthedisease.

diseaseName Nameofthedisease.

diseaseClass ListofdiseaseclassidentifiersaccordingtotheMeSHhierarchy.

diseaseClassName ListofdiseaseclassesaccordingtoMeSHhierarchy.

geneId NCBIidentifierofthegene.

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geneName OfficialSymbolofthegene.

GeneDSI TheDiseaseSpecificityIndexofthegene

GeneDPI TheGenePleiotropySpecificityIndexofthegene

GenepLI Theprobabilityofageneofbeingloss-of-functionintolerant

nrAssociatedDiseasesnrAssociatedGenes

Numberofassociateddiseasesorgenes(numberoffirstneighboursofthenode).

styleName Nameofgeneordisease,neededfortheDisGeNETvisualstyle.

styleSize Numberoffirstneighboursofthenode,neededfortheDisGeNETvisualstyle.

Note:IDandcanonicalNameareinternaluniqueidentifiersusedbythesystem. Table 3: Edge attributes in the variant-disease network Name Description

interaction Uniqueidentifierforthisassociation.

source Originaldatabaseinwhichthisgene-diseaseassociationisreported.

associationType AssociationtypeoftheVDAaccordingtotheDisGeNETassociationtypeontology(seesection2.4).

pmid PubMedidentifierofthepublicationsupportingthereportedvariant-diseaseassociation,ifavailable.

sentence Arepresentativesentencefromthepublicationdescribingtheassociationbetweenthegeneandthedisease(Ifarepresentativesentenceisnotfound,weprovidethetitleofthepaper).

score The DisGeNET VDA score ranges from 0 to 1, and takes into account the number ofsources,andthenumberofpublicationssupportingtheassociation.

EI The Evidence Index for the VDA indicates the existence of contradictory results inpublication.

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6. AnnexesTablewiththeexamplevariantstoannotateexternalnetwork

rsid Chromosome

rs9429103 1

rs10890427 1

rs111790575 1

rs1126742 1

rs13375749 1

rs211723 1

rs211710 1

rs7552404 1

rs11161430 1

rs478093 1

rs61817724 1

rs6684114 1

rs1260326 2

rs6719753 2

rs3738848 2

rs10197755 2

rs796419162 2

rs13409366 2

rs10201159 2

rs13384756 2

rs13410232 2

rs13431529 2

rs10189885 2

rs6546869 2

rs6744398 2

rs7601356 2

rs1047891 2

rs715 2

rs887829 2

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rs6742078 2

rs6804368 3

rs6800284 3

rs10010582 4

rs358236 4

rs1843481 4

rs1481012 4

rs141471965 4

rs4253255 4

rs4253328 4

rs37369 5

rs248386 5

rs27044 5

rs11386832 5

rs10075801 5

rs2405522 5

rs1801020 5

rs75077631 5

rs2545801 5

rs1165213 6

rs2817188 6

rs1165153 6

rs1165192 6

rs72939920 6

rs12208357 6

rs662138 6

rs316019 6

rs10242455 7

rs4921913 8

rs35570672 8

rs4873099 8

rs2759009 9

rs36034585 9

rs1171616 10

rs1171615 10

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rs61886778 10

rs603424 10

rs10766469 11

rs174528 11

rs7943728 11

rs174533 11

rs174535 11

rs174536 11

rs61896141 11

rs102274 11

rs174545 11

rs174548 11

rs174549 11

rs174554 11

rs174555 11

rs174560 11

rs174561 11

rs174564 11

rs174566 11

rs5792235 11

rs99780 11

rs174580 11

rs151042642 11

rs113570042 11

rs11820589 11

rs964184 11

rs34265203 12

rs10774021 12

rs11613331 12

rs17329885 12

rs4149056 12

rs11045832 12

rs1871395 12

rs58310495 12

rs59205959 12

39

rs2939302 12

rs1799958 12

rs3916 12

rs7141433 14

rs17101394 14

rs8008068 14

rs11158671 14

rs8014023 14

rs16952714 15

rs80123226 15

rs261290 15

rs2043085 15

rs1532085 15

rs1077835 15

rs1077834 15

rs2070895 15

rs261334 15

rs4775633 15

rs28582913 16

rs7208714 17

rs4330 17

rs4335 17

rs4343 17

rs4362 17

rs1799763 17

rs922442 19

rs8012 19

rs7247977 19

rs62128825 19

rs2547239 19

rs2547237 19

rs212099 19

rs641738 19

rs8736 19

rs2540645 22

40

rs131813 22

rs131793 22

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7. CitationIfyouareusingDisGeNETforyourownresearch,pleasecite:

❖ TheBrowser,andthecurrentversionofthedata:

Janet Piñero, Juan Manuel Ramírez-Anguita, Josep Saüch-Pitarch, FrancescoRonzano,EmilioCenteno,FerranSanz,LauraIFurlong.TheDisGeNETknowledgeplatformfordiseasegenomics:2019update(2019)https://doi.org/10.1093/nar/gkz1021

❖ DisGeNET-RDF:Queralt-Rosinach N, Piñero J, Bravo À, Sanz F, Furlong LI. DisGeNET-RDF:HarnessingtheInnovativePoweroftheSemanticWebtoExploretheGeneticBasis of Diseases. Bioinformatics. Bioinformatics (2016) doi:10.1093/bioinformatics/btw214

❖ TheCytoscapeApp:

PiñeroJ,SaüchJ,SanzF,FurlongLI.TheDisGeNETCytoscapeApp:exploringandvisualizingdiseasegenomicsdata.UnderreviewBauer-MehrenA,RautschkaM,SanzF,FurlongLI.DisGeNET:aCytoscapepluginto visualize, integrate, search and analyze gene-disease networks.Bioinformatics.(2010)doi:10.1093/bioinformatics/btq538Bauer-MehrenA,BundschusM,RautschkaM,MayerMA,SanzF,FurlongLI:Gene-diseasenetworkanalysisrevealsfunctionalmodulesinMendelian,complexandenvironmentaldiseases.PLoSONE(2011)doi:10.1371/journal.pone.0020284.

❖ Tocitespecificdata:

Gene-diseaseassociationdataretrievedfromDisGeNETv7.0(http://www.disgenet.org/),IntegrativeBiomedicalInformaticsGroup,GRIB/IMIM/UPF.[Month,yearofdataretrieval].

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8. References

1. JanetPiñero,JuanManuelRamírez-Anguita,JosepSaüch-Pitarch,

FrancescoRonzano,EmilioCenteno,FerranSanz,LauraIFurlong.TheDisGeNETknowledgeplatformfordiseasegenomics:2019update(2019)https://doi.org/10.1093/nar/gkz1021

2. JanetPiñero,ÀlexBravo,NúriaQueralt-Rosinach,AlbaGutiérrez-Sacristán,JordiDeu-Pons,EmilioCenteno,JavierGarcía-García,FerranSanz,andLauraI.Furlong.(2016)DisGeNET:acomprehensiveplatformintegratinginformationonhumandisease-associatedgenesandvariants.Nucl.AcidsRes.doi:10.1093/nar/gkw943

3. Piñero,J.,Queralt-Rosinach,N.,Bravo,A.,Deu-Pons,J.,Bauer-Mehren,A.,Baron,M.,Sanz,F.andFurlong,L.I.(2015)DisGeNET:adiscoveryplatformforthedynamicalexplorationofhumandiseasesandtheirgenes.Database,2015,bav028–bav028

4. Bauer-Mehren,A.,Rautschka,M.,Sanz,F.andFurlong,L.I.(2010)DisGeNET:aCytoscapeplugintovisualize,integrate,searchandanalyzegene-diseasenetworks.Bioinformatics,26,2924–6

5. Bauer-Mehren,A.,Bundschus,M.,Rautschka,M.,Mayer,M.A.,Sanz,F.andFurlong,L.I.(2011)Gene-DiseaseNetworkAnalysisRevealsFunctionalModulesinMendelian,ComplexandEnvironmentalDiseases.PLoSOne,6,13

6. XueAWuYZhuZZhangFKemperKet.al.(2018)Genome-wideassociationanalysesidentify143riskvariantsandputativeregulatorymechanismsfortype2diabetes.NatureCommunications,vol:9(1)pp:2941

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9. Contact©2010-2021,IntegrativeBiomedicalInformaticsIntegrativeBiomedicalInformaticsGroupResearchUnitonBiomedicalInformatics-GRIBIMIM-HospitaldelMarMedicalResearchInstituteUniversitatPompeuFabra(UPF)Dr.Aiguader8808003Barcelona,Spainphone:+34933160521fax:+34933160550web:http://grib.imim.es/research/integrative-biomedical-informatics/IfyouhavequestionsorcommentsaboutDisGeNETdata,thedatabase,thewebsite,theplugin,thebrowser,theRDFrepresentationorthedownloads,pleasecontactusat:support(at)disgenet(dot)org

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10. FundingIMI-JUresourcesofwhicharecomposedoffinancialcontributionfromthe

EU-FP7[FP7/2007–2013]andEFPIAcompaniesinkindcontribution[116030toTransQST, 777365 to eTRANSAFE], and the EU H2020 Programme 2014–2020[676559 to Elixir-Excelerate.]; Project001-P-001647 - Valorisation of EGA forIndustryandSocietyfundedbytheEuropeanRegionalDevelopmentFund(ERDF)andGeneralitatdeCatalunya;AgènciadeGestiód’AjutsUniversitarisideRecercaGeneralitat de Catalunya [2017SGR00519]. The Research Programme onBiomedicalInformatics(GRIB)isamemberoftheSpanishNationalBioinformaticsInstitute(INB),fundedbyISCIIIandFEDER(PRB2-ISCIII[PT13/0001/0023,ofthePE I+D+i2013–2016]).TheDCEXS isa ‘UnidaddeExcelenciaMaríadeMaeztu’,fundedbytheMINECO[MDM-2014-0370].

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11. LicenseTheDisGeNETappisdistributedundertheGNUGPL3.0license.MoredetailsabouttheGNUGeneralPublicLicense3.0isavailablehere.TheDisGeNETdatabaseismadeavailableundertheAttribution-NonCommercial-ShareAlike4.0InternationalLicensewhosetextcanbefoundhere:https://creativecommons.org/licenses/by-nc-sa/4.0/.IfDisGeNETisincorporatedintootherworks,weaskthatDisGeNETisproperlycited(seethecitationguidelines),andthattheversionnumberofDisGeNETisclearlydisplayed.http://disgenet.org/legal

12. AboutthisdocumentThiswork is licensedunder theCreativeCommonsAttribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visithttp://creativecommons.org/licenses/by-nc-sa/4.0/ or send a letter to CreativeCommons,444CastroStreet,Suite900,MountainView,California,94041,USA.