MongoDB and the Connectivity Map: Making Connections Between Genetics and Disease
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Transcript of MongoDB and the Connectivity Map: Making Connections Between Genetics and Disease
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making connections between genetics and diseaseMongoDB and the Connectivity Map
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Corey Rajiv
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a common languageGene Expression
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~7,000 experiments Over 19,000 registered users
Cited by over 1,200 scientific reports
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2006
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2014
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CMap-LINCS dataset 1.4 million gene expression profiles
3,800 Genes (shRNA & cDNA) • Targets/pathways of approved drugs • Candidate disease genes • Community nominations
15 Cell types • Banked primary cell types • Cancer cell lines • Primary hTERT-immortalized • Patient-derived iPS cells • Community nominated
12,488 Compounds • FDA approved drugs • Bioactive tool compounds • Screening hits
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• Diverse use-cases
• Users with varying technical expertise
• Annotations are complex and incomplete
• Frequent updates
CMap Data!Easy to describe, tough to Model
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Store just what’s needed
Refactor frequently
Test and use daily
Data Model!An agile philosophy keeps the model tractable
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Data Model!An inventory of signatures
siginfo
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Data Model!Shared fields as separate collections
siginfo
cellinfo
pertinfo
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Data Model!Add computed fields and external meta-data
siginfo cellinfo
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Data Model!Duplicate data to optimize lookups
siginfo pertinfo
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APIs!Are awesome, we need more of them
Picked functionality over convention!/siginfo?q={“cell”:”A”} vs /siginfo/cell/A
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API!MongoDB inspired a rich query syntax
Function Example
Query /siginfo?q={“cell:”A”,”name”:”B”}
Field selection /siginfo?q={}&f={“name”:1}
Document count /siginfo?q={}&c=true
Document limit /siginfo?q={}&l=10
Skip documents /siginfo?q={}&l=10&sk=10
Sort order /siginfo?q={}&s={“name”:-‐1,”cell”:1}
Distinct values /siginfo?q={}&d=name
Aggregation /siginfo?q={}&g=name
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API!Node and Mongoose enable easy API creation
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Language Bindings!JSON as a universal format
Javascript
Python
R
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Analytic Tools!A compute API liberates command line scripts
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Compute API!Messaging handled via a capped collection
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Input Validation!JSON Schema simplifies validation
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GCTX : A binary format based on HDF5 Cross platform
Multi-language support Efficient I/O
Storage size for 30 billion data points is 110 Gb
Numeric Matrix Data!HDF5 offers efficient storage for large matrices
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Sign up at lincscloud.org
Lincscloud!A platform for easy access to perturbational data
Free for academic use
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Predicting Drug Function!Diverse structures, common activities
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Predicting Drug Function!Diverse structures, common activities
VEGFR inhibitor
PPARG agonist
PI3K/MTOR inhibitor
ROCK inhibitor
Estrogen agonist
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Finding Novel Drug Targets!Repurposing failed drugs
Original target
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Finding Novel Drug Targets!Repurposing failed drugs
Original target
Failed in Phase 2 clinical trial due to lack of efficacy
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Finding Novel Drug Targets!Repurposing failed drugs
Original target
Novel Target A
Novel Target B
Novel Target C
Novel Target D
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Acknowledgements Todd Golub
Core Team: Analysis & Software Arvind Subramanian Jacob Asiedu Larson Hogstrom Ian Smith David Lahr Aravind Subramanian Josh Gould Ted Natoli David Wadden !Core Team: Lab John Davis David Peck Xiaodong Lu Melanie Donahue Daniel Lam Jackie Rosains (Project Manager)
Collaborators Bang Wong Steven Corsello (Golub lab) Jake Jaffe (Proteomics) David Takeda (Hahn lab) Pablo Tamayo !Chemistry & Therapeutics Lucienne Ronco Josh Bittker Arthur Liberzon Mathias Wawer Paul Clemons !Genetic Perturbation Platform John Doench Federica Piccioni David Root