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Junyan Lu2017Nov.,Heidelberg

Update on WP1:Tools and methods for high-throughput perturbation assays and integrative analysis

5th SOUNDmeeting,2017 2

Primarylymphomacells

(CLL,AML,BL…)

Project design

Transcriptome Metabolism

DNASequencing Methylome SNParray

ClinicaldataDrugresponse

Multi-omicsprofilingofbloodcancerpatients

Clinicaltranslation

Integrativedataanalysis

5th SOUNDmeeting,2017 3

Datagatheredin2017:Ø EMBLscreen(408compoundson135patientsamples)Ø CPS1000:(64compoundson732patientsamples)Ø AdditionalRNAseq dataon29patientsamplesØ AdditionalWGSdataon88patientsamples

Multi-omicsdatasets(summarizedin2016)

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Challenges

• Datamanagement

• Standardizeddataprocessing

• Datavisualizationandsharing

• Integrativeanalysis

AimsofWP1:

Ø Tacklingaboveproblemsbydesignamodular,end-to-endchainoftoolstoperformfirst-lineanalysistasks,includingdataimport,metadatamanagement,qualityassessment,visualizationandsoon.

Ø Developnovelintegrativeanalysestoolsandapplyingthemtopersonalizedmedicinestudies.

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Outline• Introduction

• Tools and platforms

ØData management

ØPipeline for high-throughput perturbation data analysis

ØTools for integrative multi-omics analysis

• Application on biological questions

5

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P0004

15PB0111

12PB0042

Aliquot1

Aliquot1

Aliquot1

+

Patients Samples Aliquots Multi-omicsdata

Datamanagement

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patientsample aliquotdiagnosis

project

aliquotused

tumorbankCopy

RMySQLpackageTumorbank

(Accessdatabase)

Jennifer Huellein

Relationaldatabaseforsamplemanagement

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http://mozi.embl.de/patientExplorer/

Shinyappforvisualizingsampleandpatientinformation

Jennifer Huellein

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Ex-vivodrugscreening

Rpackagefordatastorageandintegration

drugScreenExplorertidyverse

RNAsequencing

STARHTSeqDESeq2

Clinicaldata

RMySQLShiny

… …

PrimaryBloodCancerCellEncyclopedia(PACE):

Multi-omicsdatasets(before2016),PACE2.0isontheway.

Functionsforquery,transformationandplotting

Datapackage

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Rawdataprocessing Qualityassessment

Postprocessing Report Visualization

andsharing

PlateReader:Envision

Pipelineforhigh-throughputperturbationdataanalysis

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Rawmeasurement(txtformat)

readPlate()toreadrawdataforeachplate

Step1.Dataimport

sampleannotationfile(csvfile)

platelayoutfile(csvfile)

readScreen()

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StrictlyStandardizedMeanDifference(SSMD)

Step2.Qualityassessmentrawsignaldistribution

PCAplot

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conc.[µM]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48ABC 1 25 1 25 1 25 1 25 1 25 1 25 1 25 1 25 1 25 1 25 1 25 14 38 14 38 14 38 14 38 14 38 14 38 14 38 14 38 14 38 14 38 14 38D 49 73 49 73 49 73 49 73 49 73 49 73 49 73 49 73 49 73 49 73 49 73 62 86 62 86 62 86 62 86 62 86 62 86 62 86 62 86 62 86 62 86 62 86E 2 26 2 26 2 26 2 26 2 26 2 26 2 26 2 26 2 26 2 26 2 26 15 39 15 39 15 39 15 39 15 39 15 39 15 39 15 39 15 39 15 39 15 39F 50 74 50 74 50 74 50 74 50 74 50 74 50 74 50 74 50 74 50 74 50 74 63 87 63 87 63 87 63 87 63 87 63 87 63 87 63 87 63 87 63 87 63 87G 3 27 3 27 3 27 3 27 3 27 3 27 3 27 3 27 3 27 3 27 3 27 16 40 16 40 16 40 16 40 16 40 16 40 16 40 16 40 16 40 16 40 16 40H 51 75 51 75 51 75 51 75 51 75 51 75 51 75 51 75 51 75 51 75 51 75 64 88 64 88 64 88 64 88 64 88 64 88 64 88 64 88 64 88 64 88 64 88I 4 28 4 28 4 28 4 28 4 28 4 28 4 28 4 28 4 28 4 28 4 28 17 41 17 41 17 41 17 41 17 41 17 41 17 41 17 41 17 41 17 41 17 41J 52 76 52 76 52 76 52 76 52 76 52 76 52 76 52 76 52 76 52 76 52 76 65 89 65 89 65 89 65 89 65 89 65 89 65 89 65 89 65 89 65 89 65 89K 5 29 5 29 5 29 5 29 5 29 5 29 5 29 5 29 5 29 5 29 5 29 18 42 18 42 18 42 18 42 18 42 18 42 18 42 18 42 18 42 18 42 18 42L 53 77 53 77 53 77 53 77 53 77 53 77 53 77 53 77 53 77 53 77 53 77 66 90 66 90 66 90 66 90 66 90 66 90 66 90 66 90 66 90 66 90 66 90M 6 30 6 30 6 30 6 30 6 30 6 30 6 30 6 30 6 30 6 30 6 30 19 43 19 43 19 43 19 43 19 43 19 43 19 43 19 43 19 43 19 43 19 43N 54 78 54 78 54 78 54 78 54 78 54 78 54 78 54 78 54 78 54 78 54 78 67 91 67 91 67 91 67 91 67 91 67 91 67 91 67 91 67 91 67 91 67 91O 7 31 7 31 7 31 7 31 7 31 7 31 7 31 7 31 7 31 7 31 7 31P 55 79 55 79 55 79 55 79 55 79 55 79 55 79 55 79 55 79 55 79 55 79Q 8 32 8 32 8 32 8 32 8 32 8 32 8 32 8 32 8 32 8 32 8 32R 56 80 56 80 56 80 56 80 56 80 56 80 56 80 56 80 56 80 56 80 56 80S 9 33 9 33 9 33 9 33 9 33 9 33 9 33 9 33 9 33 9 33 9 33 20 44 20 44 20 44 20 44 20 44 20 44 20 44 20 44 20 44 20 44 20 44T 57 81 57 81 57 81 57 81 57 81 57 81 57 81 57 81 57 81 57 81 57 81 68 92 68 92 68 92 68 92 68 92 68 92 68 92 68 92 68 92 68 92 68 92U 10 34 10 34 10 34 10 34 10 34 10 34 10 34 10 34 10 34 10 34 10 34 21 45 21 45 21 45 21 45 21 45 21 45 21 45 21 45 21 45 21 45 21 45V 58 82 58 82 58 82 58 82 58 82 58 82 58 82 58 82 58 82 58 82 58 82 69 93 69 93 69 93 69 93 69 93 69 93 69 93 69 93 69 93 69 93 69 93W 11 35 11 35 11 35 11 35 11 35 11 35 11 35 11 35 11 35 11 35 11 35 22 46 22 46 22 46 22 46 22 46 22 46 22 46 22 46 22 46 22 46 22 46X 59 83 59 83 59 83 59 83 59 83 59 83 59 83 59 83 59 83 59 83 59 83 70 94 70 94 70 94 70 94 70 94 70 94 70 94 70 94 70 94 70 94 70 94Y 12 36 12 36 12 36 12 36 12 36 12 36 12 36 12 36 12 36 12 36 12 36 23 47 23 47 23 47 23 47 23 47 23 47 23 47 23 47 23 47 23 47 23 47Z 60 84 60 84 60 84 60 84 60 84 60 84 60 84 60 84 60 84 60 84 60 84 71 95 71 95 71 95 71 95 71 95 71 95 71 95 71 95 71 95 71 95 71 95

AA 13 37 13 37 13 37 13 37 13 37 13 37 13 37 13 37 13 37 13 37 13 37 24 48 24 48 24 48 24 48 24 48 24 48 24 48 24 48 24 48 24 48 24 48AB 61 85 61 85 61 85 61 85 61 85 61 85 61 85 61 85 61 85 61 85 61 85 72 96 72 96 72 96 72 96 72 96 72 96 72 96 72 96 72 96 72 96 72 96AC S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2AD S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2 S2AFAG

1 compoundnumberS1 Standard1=190001:03S2 Standard2=190004:03

negativecontrol DMSOinwaterpositivecontrol 30µMDanorubicinin0.3%DMSO/water

poitiveco

ntrol

0.0015 0.0005

water

negativecontrol

negativecontrol

30 10 3.3333 1.1111 0.3704 0.1235 0.0412 0.0137 0.0046 0.0015 0.0005 30 10 3.3333 1.1111 0.3704 0.1235 0.0412 0.0137 0.0046

PlatelayoutforEMBL2016screen idealresults

highnoiseplate edgeeffect

Step2.Qualityassessment

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Edgeeffectcorrectionbasedonlocalregression

Step3.Post-processing

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Normalizedcounts

”defacto”negativecontrols(dmso,PBS,drugswithlowestconcentrations)

Estimatededgeeffect

Applycorrectionbysubstracting background

2DLOESS

span=1

ForCPS1000(384-wellplate)

5th SOUNDmeeting,2017 16Aftercorrection

Beforeco

rrectio

n

rowwise columnwise

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Venetoclax

Panobinostat

5th SOUNDmeeting,2017

Normalizedcounts

”defacto”negativecontrols(dmso,water,empty,drugswith

lowestconcentrations)

2DLOESS

Estimatededgeeffect

Applycorrection

ForEMBL2016(1536well-plate)

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“2D2-tail”sigmoidmodel

surfacefitby2DLOESS

Anewmethodforestimatingedgeeffect

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Edgeeffectcorrectionresults

Beforecorrelction Estimatededgeeffect Estimatededgeeffect

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Ø Percentinhibitionateachconcentration(normalizedbyinnernegativecontrols)

Ø IC50curvesandAUC(by”drc”package)

Ø Averageoverall(orselected)concentrations

Step4.Summarization

5th SOUNDmeeting,2017

Ex-vivodrugscreening:EMBL2016CPS1000…

multi-omicsdata

Step5.Sharingandvisualization

5th SOUNDmeeting,2017

http://mozi.embl.de/drugScreens/

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5th SOUNDmeeting,2017

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MOFA-- MultiOmics FactorAnalysis(unsupervised)

BrittaVelten

Toolsforintegrativemulti-omicsanalysis

5th SOUNDmeeting,2017

SummaryØA SQL and Shiny based platform has been developed for patient

sample management.

ØA streamlined pipeline for the processing, quality control and visualizing of high-throughput perturbation assay has been developed.

ØComputational tools for integrative multi-omics analysis are made.

30

Next step:

Ø Automization and generalization

Ø Integration of multiple tools and platforms

5th SOUNDmeeting,2017

Outline• Introduction

• Tools and platforms

ØData management

ØPipeline for high-throughput perturbation data analysis

ØTools for integrative multi-omics analysis

• Application on biological questions

31

5th SOUNDmeeting,2017 32

1.DrugPerturbationBasedStratificationofBloodCancer

Ø Drugresponsesaremodulatedbynumerousgeneticvariantsinbloodcancers

Ø Bloodcancerpatientscanbestratifiedbytheirdifferentialdrugresponses,whichreflectsunderlyingpathwayactivities

(Dietrich,Oleś andLuetal.,manuscriptaccepted)

5th SOUNDmeeting,2017

Acknowledgement

ThorstenZenz

MichelleLibério

SebastianScheinost

WolfgangHuberGroup

ChemicalBiologyCoreFacility

Sascha Dietrich

SophieRabe

KerstinPutzker JoeLewis

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