www.elixir-europe.org

ELIXIRUpdate on ELIXIR - TraIT pilot

Sanne Abeln (VU / ELIXIR Netherland)

Dylan Spalding (EMBL-EBI)

ELIXIR Human Data Implementation Study 2016

Project / Study Partners Comment

ELIXIR / GA4GH Beacons

Leads: Jordi Rambla & Ilkka

Lappalainen

CRG (ES), EMBL-EBI, FR, BE,

SE, FI, NL

Implement Beacons in ELIXIR

Nodes (12M)

ELIXIR / GA4GH Metadata API

Leads: Michael Baudis & Helen

Parkinson

SIB (CH), EMBL-EBI, FR Reference implementation of

meta-data API (12M)

ELIXIR / IMI Oncotrack

Lead: Susanna Repo, David

Henderson & Dylan Spalding

Hub, EMBL-EBI, CRG (ES) Scoping study on long term data

management (6M)

ELIXIR / TrAIT: EGA backend for

TranSMART

Leads: Sanne Abeln & Dylan

Spalding

NL, EMBL-EBI, CRG (ES) Provide EGA connector for data

submission/retrieval (12PM) [June

2015-December 2016]

ELIXIR Human Data Implementation Study 2016

Project / Study Partners Comment

ELIXIR / GA4GH Beacons

Leads: Jordi Rambla & Ilkka

Lappalainen

CRG (ES), EMBL-EBI, FR, BE,

SE, FI, NL

Implement Beacons in ELIXIR

Nodes (12M)

ELIXIR / GA4GH Metadata API

Leads: Michael Baudis & Helen

Parkinson

SIB (CH), EMBL-EBI, FR Reference implementation of

meta-data API (12M)

ELIXIR / IMI Oncotrack

Lead: Susanna Repo, David

Henderson & Dylan Spalding

Hub, EMBL-EBI, CRG (ES) Scoping study on long term data

management (6M)

ELIXIR / TrAIT: EGA backend for

TranSMART

Leads: Sanne Abeln & Dylan

Spalding

NL, EMBL-EBI, CRG (ES) Provide EGA connector for data

submission/retrieval (12M)

Types of (Big) Data in Health and Disease

Clinical Data Imaging

High throughput molecular profilingNon-high throughput diagnostics

Size of the (raw) data

DNA sequence data is doubling every 6-8 months over the last 3 years and looks to continue for this decade

Privacy & Ethical Issues: Snyderome use case

• triangle indicates average expected risk (given age, sex, etc)

• yellow line indicates risk given SNV profiles

high cholesterol

diabetes

skin cancer

Human data: experimental molecular profiling

Molecular Profiling Data (TraIT)

raw data

processed data

computational

workflows

Aim of pilot: ELIXIR-TraIT

processed data

computational

workflows

raw data

TraIT

Aim: “The CTMM Translational Research IT (TraIT) project is

developing and implementing a long-lasting IT infrastructure for

translational research projects in the Netherlands that will

facilitate the collection, storage, analysis, and archiving of data

generated in the biomedical research projects.”

• no research

• end-user driven

CTMM-TraIT

Five data

generation work

packages

Integration and

analysis across

the platforms

7

Five data

generation

work

packages

Integration and

analysis across the

platforms

TraIT - Structure

CTMM-TraIT

Five data

generation work

packages

Integration and

analysis across

the platforms

7

TraIT - Structure

wet-lab-person

tech-operator

(bio)informatician

PI / (end)user

PI / (end)user

Scientific Output

Participant/patient enters

IntellectualProperty

ImprovedHealthcare

Experimentaldata

Downstreamanalysis

Clinical/Biobank Procedures

Imaging Samples ExperimentsQuestionnaire

EHR

DataIntegration

External data

Image database& analysis

Biobankdatabase

Phenotypedatabase

ParticipantInteraction

TraIT - Infrastructure

Scientific Output

Participant/patient enters

IntellectualProperty

ImprovedHealthcare

Experimentaldata

Downstreamanalysis

Clinical/Biobank Procedures

Imaging Samples ExperimentsQuestionnaire

EHR

DataIntegration

External data

Image database& analysis

Biobankdatabase

Phenotypedatabase

ParticipantInteraction

TraIT workflow Mostly open source IT tools

supported by international

public and private communities

8

25

26

77

TraIT Experimental data flow

9

Molecular profiling workflow

raw data processed data

TraIT Infrastructure

29

TraIT WP4: experimental data

management and analysis

Molecular profiling computation pipelines

(Bioinformatics)

Galaxy: workflow tool

End user friendly

tranSMART: data explorationclinical data + processed data

study centric

cohort / sample selection

13

tranSMART: data exploration

TraIT: ongoing effort to make tranSMART ready for processedmolecular profiling data

14

Allows “onco print” like view in tranSMART

24

EGA

European Genome-phenome Archive (EGA)

•

•

Structural variants

Open & public archives

European Nucleotide Archive

EVAEuropean Variation Archive

BioSamples

Database of Genomic Variants archive

Controlled access archive

About the EGA: What is controlled access data?

• Human, personally identifiable data types (‘raw’, processed, phenotypic)

• Affiliated to bio-medical research or consortium projects

• Informed consents specify controlled release requirements

• Access by formal application procedure to Data Access Committee (DAC)

About the EGA: What is controlled access data?

• Launched 14th July 2008

• Role: Secure archive for controlled distribution of consented genetic & phenotypic data

• 7500+ users with access; 360+ submission accounts

• Over 3.3PB archived; ~1800 datasets; 1.6PB distributed over the last year

• +200 contacts to Helpdesk/month

About the EGA: Context and metrics

About the EGA: Archived data growth

About the EGA: Distributed data volumes

About the EGA: Studies at the EGA

About the EGA: consortia data archived at the EGA

https://icgc.org/

PUBMED: 25529582

PUBMED: 25529582

https://www.sanger.ac.uk/

http://www.hipsci.org/

http://www.uk10k.org/

http://rd-connect.eu/

http://www.icr.ac.uk/

http://www.wtccc.org.uk/

About the EGA: Accessing data

About the EGA: Accessing data

About the EGA: Distribution model for controlled access

~1800 datasets

EGA Download streamer

About the EGA: Distribution model for controlled access

About the EGA: Distribution model for controlled access

The EGA data access life cycle

1.•

•

•

2.•

•

3.•

•

Source: https://wiki.galaxyproject.org/Events/GCC2015?action=AttachFile&do=get&target=S1_T2_Hoogstrate_TraIT.pdf

Paul Flicek Arcadi Navarro

Helen Parkinson

Dylan SpaldingJordi Rambla

Angel Carreno

Jeff Almeida-King

Sabela de la Torre

Saif Ur Rehman

Oscar Martinez

Pablo Garcia Mario Alberich Alexander Senf Alfred Gil Giselle Kerry

Mauricio Moldes

Jag Kandasamy Audald Lloret

Aim of pilot: ELIXIR-TraIT

processed data

computational

workflows

raw data

human data

clinical data

experimental

profiling data

processing

workflows

sequencing

workflow

arrays

workflow

Proteomics

workflow

clinical and

processed data

archival storage

workflows &

analysis

Galaxy

transSMART

raw data storage

retrieve raw data

workflow provenance

Reference to raw data

EGA

reference workflows

human data

clinical data

experimental

profiling data

processing

workflows

sequencing

workflow

arrays

workflow

Proteomics

workflow

clinical and

processed data

...

archival storage

EGA

local storage

workflows &

analysis

Galaxy

transSMART

raw data storage

retrieve raw data

workflow provenance

Reference to raw data

Demo: TraIT - Cell Line Use Case

• Non-privacy sensitive data (cell lines)

• Test and develop workflows

• Demo and training of workflows

1. User creates cohort subsets in TranSMART

2. Explores the data by

viewing summary

statistics or generating

Geneprints.

1

3. The user can perform TranSMARTs built-in analyses.1

4. As built-in analyses allow very little flexibility the user is able

to export the data to his workstation or to Galaxy.

Here there will be options to export raw data to the TraIT Galaxy.

2

Link to EGA in tranSMART

F1000Research 2015 - DRAFT ARTICLE (PRE-SUBMISSION)

ced : RNA_seq_CACO2 pred : f i l e_e

ga_l oc ? f i l e .

}

We have the same response:

( r d f l i b . term . L i t er a l ( u ’ EGAR00001352058 ’ ,

dat at ype= r d f l i b . term . URIRef ( u ’ h t t p : / / www

. example . org/ ega# f i l e ’ ) ) , )

We replace pred:file_ega_loc with pred:file_surfsara_loc

to get the PID of the files in Beehub, we have the response:

( r d f l i b . term . URIRef ( u ’ h t t p : / / ep i c3 . st o r a

ge . su r f sar a . n l :8001/ 846/ CACO2_f i l e ’ ) , )

ConclusionThe proposed ontology structure only focuses on the ba-

sic property of the data: CED and data files; which can be

mapped to in all kinds of the data structures and be re-

sistant to the changes in biology experimental techniques

in the future. We deem that this proposed ontology struc-

ture is so flexible and stable that it can be application to

other modules in TraIT. Then, ISA-Tab can be adopted to

make the documenting of the mapping more friendly.

We will finish this paper with a possible user interface de-

sign we have conjured up (Figure 11).

Figure 11. A User Inferface Design in tanSMART: it is

permissable to download the processed data, because

it is easier to handle; for the raw data, the big data

file and the complicated content obviate the down-

loads; the big files will be transferred to GALAXY, so

that users can do the analysis in the web interface,

easier and more intuitive.

Background InformationThis paper is finished by Chao Zhang under the super-

vision and tutelage of Sanne Abeln, Christine Staiger and

Jochem Bijlard as the thesisof Chao Zhang’s major intern-

ship of Bioinformatics Master Program in VU University,

Amsterdam.

Software AvailabilityA python command client that wraps up all the EGA APIs

of uploading has been developed and a demo that con-

nects EGA and Beehub with TranSMART and Visualizes

RDF graph has been given. The sources codes of the

client (including its usage) and the demo can be found

in https:/ / github.com/ cicocn/ TraIT-Demo.

Author Contributions

Competing InterestsNo competing interests were discosed.

Grant Information

AcknowledgementsBesides the authors, many people have also contributed

valuable ideas and suggestions to this project. They are

listed as followed in no particular order.

TheHype: Keesvan Bochove, Ward Weistra, Ruslan Foros-

tianov, Peter Kok

VU: Bas Stringer Luiz Bonino(DTL)

TraIT: Remond Fijneman (NKI), Stef van Lieshout

(VUmc), Mariska Bierkens (NKI), Freek de Bruijn (NKI),

Youri Hoogstrate (EMC), Andrew Stubs (EMC), Christian

Rausch (VUmc), David van Enckevort (UMCG), Gerrit

Meijer (NKI), Jan-Willem Boiten(CTMM)

EGA:Justin Pascal, Ilkka Lappalainen, Jordi Rambla

SURFsara: Irene Nooren, Jan Bot

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Cerami, Chris Sander, and Nikolaus Schultz. Integrative

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[2] Ethan Cerami, Jianjiong Gao, Ugur Dogrusoz, Benjamin E

Gross, Selcuk Onur Sumer, Bülent Arman Aksoy, Anders

Jacobsen, Caitlin J Byrne, Michael L Heuer, Erik Larsson,

Yevgeniy Antipin, Boris Reva, Arthur P Goldberg, Chris

Sander, and Nikolaus Schultz. The cBio cancer genomics

portal: an open platform for exploring multidimensional

cancer genomics data. Cancer discovery, 2(5):401–4, may

2012.

[3] Tracy Hampton. Cancer Genome Atlas. JAMA,

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[5] Erik Roelofs, André Dekker, Elisa Meldolesi, Ruud G P M

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[6] Stefan Klein, Erwin Vast, Johan van Soest, Andre Dekker,

Marcel Koek, and Wiro Niessen. XNAT imaging platform

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Page 8 of 10

2

6. The user will be able to import the data into the Galaxy tool

to start a custom workflow on the raw data.

Through a new connection the data will be visible here.

3

7. The user will then be able to run an existing workflow or

create one with the existing tools.

Workflow input:

2 FASTQ files from

paired end RNA-seq

Workflow output:

QC, feature counts,

snps, indels

4

human data

clinical data

experimental

profiling data

processing

workflows

sequencing

workflow

arrays

workflow

Proteomics

workflow

clinical and

processed data

Sample

Catalogue

archival storage

EGA

local storage

workflows &

analysis

Galaxy

transSMART

raw data storage

retrieve raw data

workflow provenance

reference workflows

Reference to raw data

Try to make a general framework

Today we use: tranSMART, EGA, Galaxy

Tomorrow?

Timelines of ELIXIR TraIT pilot

• June – Dec 2015

• Enabling CLUC upload and download (VU)

• First draft of meta-data scheme (VU)

• Jan 2016 – June 2016

• Galaxy import from EGA (EMC)

• Continued upload of CLUC data (The Hyve)

• June 2016 – Dec 2016

• Finish meta-data scheme (EGA + VU + The Hyve)

• tranSMART connection (VU + The Hyve)

continuing support EGA

(EBI & Barcelona)

FAIR principles - interoperable

Paradigm shift needed:

• share data

• interoperable data referencing

• less study centric

Beyond the pilot?

• BBRMI (Sample catalogue)

• Rare disease use case

• Galaxy – tranSMART

• integration (?)

• Workflow referencing

• Meta data / Fair data push, PIDs - EGA

EMBL- EBI

• ‘European Node’

• EMBL-ELIXIR Work Programme agreed, ie, Ensembl, EGA, ENA, PDBe, EuropePMC

• Lead EXCELERATE Use Cases on Rare Diseases, Human Data, Plant Sciences, Marine..

• Involved in several ELIXIR Pilot Actions

36

ELIXIR Netherlands

• Led by DTL

• Exists as a PPP

• Officially launched in 2014

• Run Bring Your Own Data (BYOD) programme

• Large role in interoperability backbone, ie FAIR

37

ELIXIR Spain

• Long history of national collaboration - INB

• ELIXIR Pilot on EGA as a Joint Venture

• Involvement in ENCODE, ICGC, IRDiRC, RD-Connect, tomato genome consortium, various IMI projects

38

EGA Team

Paul Flicek Arcadi

Navarro

Helen

ParkinsonDylan SpaldingJordi Rambla

Angel

Carreno

Jeff Almeida-

King

Sabela de la

TorreSaif Ur

Rehman

Oscar Martinez

Pablo Garcia Mario Alberich Alexander Senf Alfred Gil Giselle Kerry

Mauricio

Moldes

Jag Kandasamy Audald Lloret

TraIT (WP4)

Remond Fijneman

Sanne Abeln

Stef van Lieshout

Mariska Bierkens

Freek de Bruijn

Thang Pham

Youri Hoogstrate

Saskia Hiltemann

TraIT

Gerrit Meijer

Jan-Willem Boiten

Wim van der Linden

Rita Azevedo

Jeroen Beliën

Pieter Neerincx

Jaap Heringa

The Hyve

Kees van Bochove

Ward Weistra

Ruslan Forostianov

Peter Kok

contact: j.bijlard@vu.nl

TraIT –WP4 (NL)

Remond Fijneman (NKI)

Stef van Lieshout (VUmc)

Mariska Bierkens (NKI)

Freek de Bruijn (NKI)

Youri Hoogstrate (EMC)

Saskia Hiltemann (EMC)

Thang Pham (VUmc)

Andrew Stubs (EMC)

Bauke Ylstra (VUmc)

Christian Rausch (NKI)

Connie Jimenez (VUmc)

Guido Jenster (EMC)

Pieter Neerincx (UMCG)

The Hyve (NL)

Kees van Bochove

Ward Weistra

Ruslan Forostianov

Peter Kok

Jochem Bijlard

Wibo Pipping

TraIT (NL)

Gerrit Meijer (NKI)

Jan-Willem Boiten (CTMM)

Wim van der Linden (Philips)

Rita Azevado (eScience/ CTMM)

Jeroen Beliën (VUmc)

Jaap Heringa (VU)

`

ELIXIR – Human Data

Dylan Spalding (EGA, EBI, UK)

Jordi Rambla (EGA, CRG, ES)

Justin Paschall (EGA, EBI, UK)

Alexander Senf (EGA, EBI, UK)

David van Enckevort (BBRMI,UMCG, NL)

Morris Swertz (BBRMI,UMCG, NL)

Luiz Bonino (ELIXIR, DTL, NL)

Susanna Repo (ELIXIR, EBI, UK)

Christine Staiger (SurfSara, NL)

Irene Nooren (SurfSara,NL)

Ilkka Lappalainen(ELIXIR)

Chao Zhang [Cico] (ADS, VU, NL)

www.elixir-europe.org

@ELIXIREurope /company/elixir-europe

THANK YOU!

ELIXIR Track: 50 submissions

3-7 September 2016 http://www.eccb2016.org/