Scott Edmunds: GigaScience - a journal or a database? Lessons learned from the Genomics Tsunami

Scott Edmunds

(Lessons learned from the Genomics “Tsunami”)

www.gigasciencejournal.com

: a Journal or a Database?

HUPO Congress 2011, Geneva

BGI Introduction

• Formerly known as Beijing Genomics Institute• Founded in 1999• Now the largest genomic organization in the

world• Goal

– Use genomics technology to impact the society– Make leading edge genomics highly accessible to the global research community

Sequencers137 Illumina/HiSeq 200027 LifeTech/SOLiD 416 AB/3730xl + 110 MegaBACEs2 Illumina iScan

Largest Sequencing Capacity in the World

Data Production 5.6 Tb / day

> 1500X of human genome / day

Multiple Supercomputing Centers 157 TB Flops

20 TB Memory

12.6 PB Storage

Mass spectrometry at BGI QTRAP 5500 Orbitrap velos maXis ultrafleXtreme™

Producer AB SCIEX Thermo Scientific Bruker Bruker

Source-Analyzer ESI-Triplequadrupole-LIT

ESI-LTQ-Orbitrap ESI-UHR-Q-TOF-MS MALDI-TOF/TOF

Application MRM • High accuracy• Label-free quantitation

• iTRAQ quantitation

• QC• MS image

QTRAP 5500, AB SCIEX Orbitrap velos, Thermo Scientific maXis Q-TOF, Bruker ultraflex, Bruker

Products and Services Offered to Collaborators

• Protein Profiling for any species (tying in with 1000 PARGP)

• Techniques:– Quantitative analysis– Post-translational modification– Target Proteomics– Metabolomics

“Trans-Omics”

• Genomics • Transcriptomics• Proteomics • Metabolomics

Objective to integrate data from:

BGI Proteomics Dept Focus:

• RAW MS data storage and analysis• Upstream analysis • “Large-scale” screening/quantitative analysis• Working on: Automatic analysis pipelines/tools

Industrial usage/standards

Lessons Learned:

What went right?

Bill Clinton: “We are here to celebrate the completion of the first survey of the entire human genome. Without a doubt, this is the most important, most wondrous map ever produced by human kind. “

“Today we are learning the language in which God created life.”

Lessons Learned: 1. having a cool project helps…

Lessons Learned: 2. Reproducibility is important…

Helped by stability of:

1. Platforms

2. Infrastructure

3. Standards

1st Gen 2nd Gen

Lessons Learned: 3. Sharing is important…

V


V


1. Automatic release of sequence assemblies within 24 hours.2. Immediate publication of finished annotated sequences.3. Aim to make the entire sequence freely available in the public domain for both

research and development in order to maximise benefits to society.

Bermuda Accords 1996/1997/1998:

1. Sequence traces from whole genome shotgun projects are to be deposited in a trace archive within one week of production.

2. Whole genome assemblies are to be deposited in a public nucleotide sequence database as soon as possible after the assembled sequence has met a set of quality evaluation criteria.

Fort Lauderdale Agreement, 2003:

The goal was to reaffirm and refine, where needed, the policies related to the early release of genomic data, and to extend, if possible, similar data release policies to other types of large biological datasets – whether from proteomics, biobanking or metabolite research.

Toronto International data release workshop, 2009:

Benefits of Data-sharing

Piwowar HA, Day RS, Fridsma DB (2007) PLoS ONE 2(3): e308. doi:10.1371/journal.pone.0000308

Sharing Detailed Research Data Is Associated with Increased Citation Rate.

Every 10 datasets collected contributes to at least 4 papers in the following 3-years.Piwowar, HA, Vision, TJ, & Whitlock, MC (2011). Data archiving is a good investment Nature, 473 (7347), 285-285 DOI: 10.1038/473285a

19961997

19981999

20002001

20022003

20042005

20062007

20080

100

200

300

400

500

600

700rice wheat

Rice v Wheat: consequences of publically available genome data.

Duplicated genes most responsive to ecological challenges

The Ecoresponsive Genome of Daphnia pulex Colbourne et al., Science 4 February 2011:

200Mb Genome, 30,907 genes

wFleabase: Mar 2006Genome release: July 2007

Genome Published: Feb 2011

Daphnia Genome Consortium

>58 companion papershttps://daphnia.cgb.indiana.edu/Publications

Problems?

Flickr cc: opensourceway

Thomas Michael Dexter (Wellcome trust): “Mapping the human genome has been compared with putting a man on the moon, but I believe it is more than that. This is the outstanding achievement not only of our lifetime, but in terms of human history”

Lessons Learned: 4. Need to manage expectations…

June 2000

Lessons Learned: 4. Need to manage expectations…

June 2010

~100,000X

Moore’s Law

Sequencing

Source: E Lander/Broad

Sequencing cost ($ per Mbp)

Lessons Learned: 5. Data, data, data

Data

Moore’s/Kryders Law

Storage

Sequencing Output Lessons Learned: 5. Data, data, data

Data

Dissemination?

Publication

Sequencing Output Lessons Learned: 5. Data, data, data


Can we keep up?Lessons Learned: 5. Data, data, data


Do we have models for long term funding?


Human Gene Mutation Database

?

Kyoto Encyclopedia of Genes and Genomes

Growing/widening user base.


?

3rd Gen sequencers: “Democratizing sequencing”


?

Curation, curation, curation?

The long tail of new “big-data” producers?


?

Are there now too many hurdles?


?

Are there now too many hurdles?Technical: too large volumes

too heterogeneous no home for many data typestoo time consuming

Economic: too expensive, no long-term funding

Cultural: inertiano incentives to share unaware of how

Potential solutions?

Potential solutions: Better handling of data, data, data

Cloud?

Potential solutions: Better handling of data, data, data

• What to save/what to throw away?

• Better Compression?

Potential solutions: Better handling of metadata…

Cloud solutions?

Better tools for assessing data quality…

Potential Solutions:

?

New incentives/creditCredit where credit is overdue:“One option would be to provide researchers who release data to public repositories with a means of accreditation.”“An ability to search the literature for all online papers that used a particular data set would enable appropriate attribution for those who share. “Nature Biotechnology 27, 579 (2009)

Prepublication data sharing (Toronto International Data Release Workshop)“Data producers benefit from creating a citable reference, as it can later be used to reflect impact of the data sets.” Nature 461, 168-170 (2009)

Datacitation: Datacite and DOIs

Digital Object Identifiers (DOIs) offer a solution

Mostly widely used identifier for scientific articles

Researchers, authors, publishers know how to use them

Put datasets on the same playing field as articles

DatasetYancheva et al (2007). Analyses on sediment of Lake Maar. PANGAEA.doi:10.1594/PANGAEA.587840

http://dx.doi.org/10.1594/PANGAEA.587840

Datacitation: Datacite and DOIs

>1 million DOIs since Dec 2009

Central metadata repository to link with WoS/ISI

- finally can track and credit use!

How can we combine these?

Journals Databases?


Large-Scale Data Journal/Database

Editor-in-Chief: Laurie Goodman, PhDEditor: Scott Edmunds, PhDAssistant Editor: Alexandra Basford, PhD

In conjunction with:

Now taking submissions…


Criteria and Focus of Journal/DatabaseReproducibility/ReuseUtility/UsabilityStandards/Searchability/Scale/SharingData publishing/DOI


Data publishing/DOIData hosting will follow standard funding agency and community guidelines.DOI assignment available for submitted data to allow ease of finding and citing datasets, as well as for citation tracking.Datasets tracked by WOS/ISI allowing additional metrics/credit for use.


Reproducibility/Reuse BGI Cloud Computing resources for handling and analyzing large-scale data.Integrated tools to promote more widespread access, viewing, and analysis of data.Encourage and aid use of workflow systems for methods (e.g. submission of Galaxy XML files).


Special Series/Hub for cloud-based toolsTechnical notes: test tools in the BGI-Cloud.Tools + Test Data (BGI or user) in one place.Aids reproducibility. Aids reviewers (free)Aids authors: visibility (pubmed, etc.)

hosting (included/free offers)

–contact us: [email protected]

Oledoe flickr cc

mailto:[email protected]



Standards/Searchability/Sharing ISA-Tab compatibility to aid and promote best practice in metadata reporting.All supporting data must be publically available.Ask for MIBBI compliance and use of reporting checklists.Part of the Biosharing network.

To maximize its utility to the research community and aid those fighting the current epidemic, genomic data is released here into the public domain under a CC0 license. Until the publication of research papers on the assembly and whole-genome analysis of this isolate we would ask you to cite this dataset as:

Li, D; Xi, F; Zhao, M; Liang, Y; Chen, W; Cao, S; Xu, R; Wang, G; Wang, J; Zhang, Z; Li, Y; Cui, Y; Chang, C; Cui, C; Luo, Y; Qin, J; Li, S; Li, J; Peng, Y; Pu, F; Sun, Y; Chen,Y; Zong, Y; Ma, X; Yang, X; Cen, Z; Zhao, X; Chen, F; Yin, X; Song,Y ; Rohde, H; Li, Y; Wang, J; Wang, J and the Escherichia coli O104:H4 TY-2482 isolate genome sequencing consortium (2011) Genomic data from Escherichia coli O104:H4 isolate TY-2482. BGI Shenzhen. doi:10.5524/100001 http://dx.doi.org/10.5524/100001

Our first DOI:

To the extent possible under law, BGI Shenzhen has waived all copyright and related or neighboring rights to Genomic Data from the 2011 E. coli outbreak. This work is published from: China.

http://dx.doi.org/10.5524/100001

http://dx.doi.org/10.5524/100001

“The way that the genetic data of the 2011 E. coli strain were disseminated globally suggests a more effective approach for tackling public health problems. Both groups put their sequencing data on the Internet, so scientists the world over could immediately begin their own analysis of the bug's makeup. BGI scientists also are using Twitter to communicate their latest findings.”

“German scientists and their colleagues at the Beijing Genomics Institute in China have been working on uncovering secrets of the outbreak. BGI scientists revised their draft genetic sequence of the E. coli strain and have been sharing their data with dozens of scientists around the world as a way to "crowdsource" this data. By publishing their data publicy and freely, these other scientists can have a look at the genetic structure, and try to sort it out for themselves.”

G10K Genomes Get DOI®s

doi:10.5524/100004


We want your data!

[email protected]

[email protected]

@gigascience




Scott Edmunds: GigaScience - a journal or a database? Lessons learned from the Genomics Tsunami

Technology

tb flops

tb day

largest genomic organization

largest sequencing capacity

ab sciexorbitrap velos

thermo scientificmaxis

collaboratorsprotein

global research community