Date post: | 19-Feb-2017 |
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10 Assays ~1 Experiment
100 Assays ~Pseudomonas syringae compendium
1000 Assays ~Pseudomonas aeruginosa Compendium
10,000 Assays ~Zebrafish Compendium
100,000 Assays ~Rat Compendium
1,800,000 Assays ~Publicly Available Compendium
~Human Compendium
One Recent Experiment (Macosko et al. Cell. 2015)
Research is to see what everybody else has seen and to think what
nobody else has thought.�Albert Szent-Györgyi
Image by J.W. McGuire/NIH
Image from You Don’t Know Jack. Vol 3.
Unsupervised discovery from large gene expression
compendia with ADAGE
Casey Greene
Assistant Professor Systems Pharmacology and Translational Therapeutics
Image by Lisbeth Salander
If you showed 16,000 computers 10 million images from youtube, what would they see?
Le et al. 2012
Deep Learning from Youtube
Internet Videos
Computing Cluster
Object Detector
pbs.org Le et al. 2012
Google Research
Analysis with Denoising Autoencoders of �Gene Expression (ADAGE)
Tan et al. Pac Sym Bio 2015; Tan et al. In Press.
LeCun, Bengio, and Hinton. Nature 2015.
High-weight Contributors
ADAGE Identifies Genes’ Pathways
Assign Pathway
… and produces useful networks
ADAGE Identifies Strain Differences
Genome Hybridization
ADAGE Identifies Strain Differences
The Transcription Factor Anr Controls P.a. Response to Low O2
Low O2
O2
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O2
O2 O2
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O2
O2
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O2 O2
O2
O2 O2
O2
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O2
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O2 O2 O2
O2 O2
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Anr
CF Lung Epithelium
Node42 reflects Anr Activity
New Experiment Validates Node 42’s Low-O2 Signature
CF lung epithelial cells Jack Hammond
ADAGE complements PCA/ICANode 42 PC4 PC7 IC14 IC49
Cross-platform normalization of microarray and RNA-seq data for machine learning applications
Thompson, Tan, Greene. PeerJ Preprint: https://peerj.com/preprints/1460/ Jeff Thompson
Cross-platform normalization of microarray and RNA-seq data for machine learning applications
Thompson, Tan, Greene. PeerJ Preprint: https://peerj.com/preprints/1460/
ADAGE complements PCA/ICA
Tan et al. In Press. Supplemental Figures 1-3
Node 42 PC4 PC7 IC14 IC49
How do we move from �this to mechanisms?
What “pathways” did my experiment affect?
ADAGE-based Pathway Analysis of Transcriptomic Changes
P19: ADAGE analysis of publicly available gene expression data collections illuminates Pseudomonas aeruginosa-host interactions�bioRxiv: http://dx.doi.org/10.1101/030650
P54: Cross-population analysis of high-grade serous ovarian cancer reveals only two robust subtypes. bioRxiv: http://dx.doi.org/10.1101/030239
Mine Your�
Own Business
Image by DixiePistols
Mine Your�
Own Business
Greene and Troyanskaya, Nucleic Acids Research. 2011
Mine Your�
Own Business
Wong*, Park*, Greene* et al., Nucleic Acids Research. 2012
Mine Your�
Own Business
Greene,* Wong,* Krishnan,* et al. Nature Genetics. 2015.
Mine Your�
Own Business
Zelaya and Greene, In Preparation
ADAGE Webserver coming soon! http://www.greenelab.com
When you’re caught in the data deluge…
Image by Lisbeth Salander
… don’t grab an umbrella…
Image by Lena Vasiljeva
… get a bucket.
Image by SantiMB.Photos
Greene Lab: Jie Tan+ (Grad Student) Gregory Way (Grad Student) René Zelaya (Programmer) Matt Huyck (Programmer) Kathy Chen (Undergrad) Mulin Xiong (Undergrad) Jeff Thompson (Marsit Lab/Dartmouth) Data: All investigators who publicly release their gene expression data. Images: Artists who release their work under a Creative Commons license. Funding: G&B Moore Investigator in Data-Driven Discovery National Science Foundation Cystic Fibrosis Foundation Norris Cotton Cancer Center Prouty Grant American Cancer Society Dartmouth SYNERGY +Neukom Institute Graduate Fellowship Find us online: http://www.greenelab.com Twitter: @GreeneScientist