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VariantSpark: a library for Genomics
Transformational Bioinformatics | Denis C. Bauer | @allPowerde
Lynn Langit
“Genomical” Big Data
Natalie Twine
Transformational Bioinformatics Team
Transformational Bioinformatics | Denis C. Bauer | @allPowerde
Denis Bauer Oscar Luo Rob Dunne Piotr SzulAidan O’BrienLaurence Wilson
Adrian White
Mia Champion
Gaetan Burgio
Collaborators
David Levy
News
Software
Dan Andrews
Kaitao Lai
Kaylene Simpson
Iva Nikolic
Ian Blair
Kelly Williams
BMC Genomics 2015, 16:1052 PMID: 26651996 (IF=4)
Cited
4
VariantSpark | Denis C. Bauer @allPowerde
Unsupervised ML : K-Means
www.cloudaccess.eu
1000 x 40 Million variants
Matrix *
k-means
Predict super
population
4
14 ethnic groups and
s u p e r
populations
VariantSpark | Denis C. Bauer @allPowerde
* VariantSpark can also process phase 3 data: 3000 individuals and 80 million variants
Comparing k-means to other implementations
0
1000
2000
Python
R
H
adoop
Adam
AD
M
IXTU
R
E
VariantSpark
method
timeinseconds
task
binary−conversion
clustering
pre−processing
103 75 29 28 18 4 min
VariantSpark | Denis C. Bauer @allPowerde
Supervised ML: Wide Random Forests
Transformational Bioinformatics | Denis C. Bauer | @allPowerde
Transformational Bioinformatics | Denis C. Bauer | @allPowerde
Genomic Research Workflow
https://www.projectmine.com/about/
Focus
Performance – Faster and More Accurate
VariantSpark is the only method to scale to 100% of the genome
Transformational Bioinformatics | Denis C. Bauer | @allPowerde
Scaling to 50 M variable and 10 K samples
Transformational Bioinformatics | Denis C. Bauer | @allPowerde
100K trees: 5 – 50h
AWS: ~$215.50
100K trees: 200 – 2000h
AWS: ~ $ 8620.00
• Yarn Cluster (12 workers)
• 16 x Intel Xeon E5-2660@2.20GHz CPU
• 128 GB of RAM
• Spark 1.6.1 on YARN
• 128 executors
• 6GB / executor (0.75TB)
• Synthetic dataset (mtry = 0.25)
Whole Genome
Range
GWAS Range
Databricks &
VariantSpark
via a Jupyter notebook
Solving Important Questions…
Cancer genomics?
DEMO: Who is a Hipster?
• Quickly access a managed Spark cluster - AWS EC2 / spot instances
• Link to your data and perform whole genome analysis in real-time
VariantSpark & Databricks Notebooks
Transformational Bioinformatics | Denis C. Bauer | @allPowerde
Jupyter Notebook
Transformational Bioinformatics | Denis C. Bauer | @allPowerde
Joint-loci association test
Hipster-Index = ((2 + GT[B6]) * (1.5 + GT[R1])) + ((0.5 + GT[C2]) * (1 + GT[B2]))
Label = 1 if Hipster-Index>10
Genomic profile Label
Samples(n=2500)
Transformational Bioinformatics | Denis C. Bauer | @allPowerde
VariantSpark: a library for Genomics
Transformational Bioinformatics | Denis C. Bauer | @allPowerde
Lynn Langit

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VariantSpark a library for genomics by Lynn Langit

  • 1. VariantSpark: a library for Genomics Transformational Bioinformatics | Denis C. Bauer | @allPowerde Lynn Langit
  • 3. Natalie Twine Transformational Bioinformatics Team Transformational Bioinformatics | Denis C. Bauer | @allPowerde Denis Bauer Oscar Luo Rob Dunne Piotr SzulAidan O’BrienLaurence Wilson Adrian White Mia Champion Gaetan Burgio Collaborators David Levy News Software Dan Andrews Kaitao Lai Kaylene Simpson Iva Nikolic Ian Blair Kelly Williams
  • 4. BMC Genomics 2015, 16:1052 PMID: 26651996 (IF=4) Cited 4 VariantSpark | Denis C. Bauer @allPowerde
  • 5. Unsupervised ML : K-Means www.cloudaccess.eu 1000 x 40 Million variants Matrix * k-means Predict super population 4 14 ethnic groups and s u p e r populations VariantSpark | Denis C. Bauer @allPowerde * VariantSpark can also process phase 3 data: 3000 individuals and 80 million variants
  • 6. Comparing k-means to other implementations 0 1000 2000 Python R H adoop Adam AD M IXTU R E VariantSpark method timeinseconds task binary−conversion clustering pre−processing 103 75 29 28 18 4 min VariantSpark | Denis C. Bauer @allPowerde
  • 7. Supervised ML: Wide Random Forests Transformational Bioinformatics | Denis C. Bauer | @allPowerde
  • 8. Transformational Bioinformatics | Denis C. Bauer | @allPowerde Genomic Research Workflow https://www.projectmine.com/about/ Focus
  • 9. Performance – Faster and More Accurate VariantSpark is the only method to scale to 100% of the genome Transformational Bioinformatics | Denis C. Bauer | @allPowerde
  • 10. Scaling to 50 M variable and 10 K samples Transformational Bioinformatics | Denis C. Bauer | @allPowerde 100K trees: 5 – 50h AWS: ~$215.50 100K trees: 200 – 2000h AWS: ~ $ 8620.00 • Yarn Cluster (12 workers) • 16 x Intel Xeon E5-2660@2.20GHz CPU • 128 GB of RAM • Spark 1.6.1 on YARN • 128 executors • 6GB / executor (0.75TB) • Synthetic dataset (mtry = 0.25) Whole Genome Range GWAS Range
  • 11.
  • 14. DEMO: Who is a Hipster?
  • 15. • Quickly access a managed Spark cluster - AWS EC2 / spot instances • Link to your data and perform whole genome analysis in real-time VariantSpark & Databricks Notebooks Transformational Bioinformatics | Denis C. Bauer | @allPowerde Jupyter Notebook Transformational Bioinformatics | Denis C. Bauer | @allPowerde
  • 16. Joint-loci association test Hipster-Index = ((2 + GT[B6]) * (1.5 + GT[R1])) + ((0.5 + GT[C2]) * (1 + GT[B2])) Label = 1 if Hipster-Index>10 Genomic profile Label Samples(n=2500) Transformational Bioinformatics | Denis C. Bauer | @allPowerde
  • 17. VariantSpark: a library for Genomics Transformational Bioinformatics | Denis C. Bauer | @allPowerde Lynn Langit

Editor's Notes

  1. http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002195
  2. http://www.cloudaccess.eu/blog/wp-content/uploads/2014/06/genetic_roots.png
  3. Chromosome 22; VM on Microsoft Azure with A7 Linux instance and 8 cores, 56GB memory running Ubuntu.
  4. https://academics.cloud.databricks.com/#notebook/170398/command/170419