POMAStatisticalanalysistoolfortargetedmetabolomicdataPolCastellano-EscuderJul11,2019|useR!2019|Toulouse

1.Context

2.Motivation&Aims

3.Results

4.Conclusions

5.FutureWork

Outline

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CONTEXT

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What’sMetabolomics?"Metabolomicsistheidentificationandquantificationofthesmallmoleculemetabolicproducts(themetabolome)ofabiologicalsystem.MassspectrometryandNMRspectroscopyarethetechniquesmostoftenusedformetabolomeprofiling"1

"TheOmicsCascade"

2

[1]https://www.nature.com/subjects/metabolomics

[2]NaradP.,KirthanashriS.V.(2018)IntroductiontoOmics.In:ArivaradarajanP.,MisraG.(eds)OmicsApproaches,TechnologiesAndApplications.Springer,Singapore

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Thedata

Targetedanduntargetedmetabolomics

Targetedmetabolomics:weknowthemassofthemetabolitesthatwewanttoquantifyBEFOREtheanalysis(hundreds)

Untargetedmetabolomics:allmetaboliteswillbeacquired,butwewillnotknowexactlywhichonesaresomeofthem(thousands)

Howisthedatathatwewillanalize?Standard(Omics)matrix:Samplesinrowsandmetabolites(variables)incolumns

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WebAppsthatallowsuserstoperformastatisticalanalysis3

Workflow4metabolomicsGalaxy-MXCMSOnlineMetaboAnalyst

FreelyAvailableExistingTools

[3]Spicer,R.,Salek,R.M.,Moreno,P.,Cañueto,D.,&Steinbeck,C.(2017).Navigatingfreely-availablesoftwaretoolsformetabolomicsanalysis.Metabolomics,13(9),106.

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MOTIVATION&AIMS

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Motivation&Aims

MotivationBiologicalinterpretationoftheresultsisoneofthehardpointsandhighknowledgeofstatisticalanalysisandcomputationalprogrammingisusuallyrequired

Sometimes,theexistingtoolsdon’taccept"complicated"databases

AimsProvideusersofanEASYUSEtoolthatdon’trequireprogrammingskills

Allowuserstoanalyzealltypesofdata(simpleandcomplex)

Leadtheuserforagoodstatisticalanalysis(Documentation&automaticreports)

MakeacompletelyREPRODUCIBLEanalysis(OpenSource)

OurmainaimisCOMPLETINGtheexistingtoolsandgiveotheroptiontousers,NOTtoCOMPETEwiththeexistingtools

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RESULTS

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POMAShinyApp

http://polcastellano.shinyapps.io/POMA/

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Architecture

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InputDataPanelWehaveusedthe shinydashboard packageforthemainstructureandthe dashboardthemes packageforcustomization

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InputDataPanelWehaveusedthe shinydashboard packageforthemainstructureandthe dashboardthemes packageforcustomization

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VisualizationAllplotsintheapparedesignedusing plotly package.Itmakeallplotsinteractiveallowinguserstozoominorzoomoutinaplots,selectpointstoseetheindividualinformation,hideallpointsofonegroupanddownloadplotsinaeasyway!

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DocumentationTheimplementationof shinyhelper packageallowseachpaneltohaveanindividualhelp

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DocumentationTheimplementationof shinyhelper packageallowseachpaneltohaveanindividualhelp

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StatisticalAnalysisTheaimistooffertotuneasmanyparametersaspossibletoavoidthe"blackbox"effect

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AutomaticStatisticalReport

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CONCLUSIONS

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ConclusionsWehavedevelopedaFAST,FRIENDLYandFREEsoftwarethatiscalledPOMA

POMAisfull-basedinRlanguageandusesaShinysystemtorun

POMAprovidesanaccurateDOCUMENTATION("HELP")ateachstepofanalysisthatcoluldimprovetheresultsandfacilitatetheinterpretationofit

POMAcangeneratetwotypesofAUTOMATICREPORTS:ExploratoryreportandStatisticalreport

POMAisinaconstantdevelopment.Accordingtothis,wearetotallyopentouserbugreportstokeepimprovingourapp

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FutureWork(Inorderofimportance...)

Finishingthedocumentationasaccuratelyaspossible

Makethecodemoreefficient

DevelopapackagewithallPOMAfunctions

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Thankyouall!TotheStatisticsandBioinformaticsResearchGroupandBiomarkersandNutritional&Food

MetabolomicsResearchGroupfromUniversityofBarcelonaforamazingsupport

TotheuseR!2019organizers,forallowingmetoshowthiswork

SlidescreatedviatheRpackagexaringan

polcaes@gmail.compcastellanoescuder.github.io/

@polcastellano_@pcastellanoescuderUniversityofBarcelona

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