AMC Graduate School Introduction e-Science course Scale of - - PowerPoint PPT Presentation

DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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AMC Graduate School e-Science course

Barbera van Schaik

Bioinformatics Laboratory, KEBB Academic Medical Center b.d.vanschaik@amc.uva.nl

April 15, 2015 Since: 1999 @ AMC Position: bioinformatician, junior researcher Projects: DNA sequence analysis

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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DNA data analysis on many infrastructures

In this session

You will get an indication about the scale of DNA sequence data, how this is processed on different type of infrastructures, and I will show you a few examples Questions during and after the presentation

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

Question round

What is bioinformatics?

Extraction of biological knowledge from complex data

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

Question round

What is bioinformatics?

... one of the results *might* be a tool you can use

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

Question round

Manual and automated sequencing

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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Next generation sequencing

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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Sequencers around the world

http://omicsmaps.com/ 7 / 22

DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

Question round

Big data

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

Question round

DNA sequencing rate

http://www.wellcome.ac.uk/Education-resources/Education-and-learning/big-picture/ all-issues/genes-genomes-and-health/wtdv027167.htm 9 / 22

DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

Question round

Analysis on PCs and small servers

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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In-house cluster (centralized model)

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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Dutch life science grid (distributed model)

http://surfsara.nl/

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

Question round

Cloud computing

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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And more

Super computer Hadoop GPU cluster

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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Examples

1 Data sharing 2 Speed up analysis 3 Education environment 4 Immunology data flow

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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Sharing research data

e-mail Dropbox Hard drives

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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Sharing research data

Beehub Grid

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

Question round

Grid to speed up analysis

Very rare syndrome: Nicolaides Baraitser Found de novo mutations in the SMARCA2 gene Reviewers: Are these mutations specific for the disease? Needed to check this mutation in a large cohort

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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Check mutations in GoNL data

http://www.dutchgenomeproject.com/ To do: annotate all variants of 500 Dutch genomes Two weeks to finish the analysis 19 / 22

DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

Question round

Cloud for education

2nd yr bachelor course - Genomics of disease 150 students perform DNA analysis at the same time Temporary need of extra compute power (2 weeks per year)

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DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

Question round

Immunology data flow

Analysis pipeline runs on cloud Data is stored and shared via beehub Manual steps: data transfers, annotation, notify eachother by e-mail Need proper data management and provenance. Automation is a bonus. 21 / 22

DNA and e-science Barbera van Schaik Introduction Scale of sequence data Infrastructures Examples

Data sharing Grid to speed up analysis Cloud for education Cloud and Beehub

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Question round

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