Casey Greene's Keynote for Rocky 2015
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Transcript of Casey Greene's Keynote for Rocky 2015
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supermarketnews.com
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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)
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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
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Image from You Don’t Know Jack. Vol 3.
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Unsupervised discovery from large gene expression
compendia with ADAGE
Casey Greene
Assistant Professor Systems Pharmacology and Translational Therapeutics
Image by Lisbeth Salander
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If you showed 16,000 computers 10 million images from youtube, what would they see?
Le et al. 2012
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Deep Learning from Youtube
Internet Videos
Computing Cluster
Object Detector
pbs.org Le et al. 2012
Google Research
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Analysis with Denoising Autoencoders of �Gene Expression (ADAGE)
Tan et al. Pac Sym Bio 2015; Tan et al. In Press.
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LeCun, Bengio, and Hinton. Nature 2015.
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High-weight Contributors
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ADAGE Identifies Genes’ Pathways
Assign Pathway
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… and produces useful networks
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ADAGE Identifies Strain Differences
Genome Hybridization
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ADAGE Identifies Strain Differences
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The Transcription Factor Anr Controls P.a. Response to Low O2
Low O2
O2
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O2 O2
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O2 O2 O2
O2 O2
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O2
Anr
CF Lung Epithelium
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Node42 reflects Anr Activity
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New Experiment Validates Node 42’s Low-O2 Signature
CF lung epithelial cells Jack Hammond
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ADAGE complements PCA/ICANode 42 PC4 PC7 IC14 IC49
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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
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Cross-platform normalization of microarray and RNA-seq data for machine learning applications
Thompson, Tan, Greene. PeerJ Preprint: https://peerj.com/preprints/1460/
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ADAGE complements PCA/ICA
Tan et al. In Press. Supplemental Figures 1-3
Node 42 PC4 PC7 IC14 IC49
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How do we move from �this to mechanisms?
What “pathways” did my experiment affect?
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ADAGE-based Pathway Analysis of Transcriptomic Changes
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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
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Mine Your�
Own Business
Image by DixiePistols
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Mine Your�
Own Business
Greene and Troyanskaya, Nucleic Acids Research. 2011
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Mine Your�
Own Business
Wong*, Park*, Greene* et al., Nucleic Acids Research. 2012
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Mine Your�
Own Business
Greene,* Wong,* Krishnan,* et al. Nature Genetics. 2015.
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Mine Your�
Own Business
Zelaya and Greene, In Preparation
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ADAGE Webserver coming soon! http://www.greenelab.com
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When you’re caught in the data deluge…
Image by Lisbeth Salander
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… don’t grab an umbrella…
Image by Lena Vasiljeva
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… get a bucket.
Image by SantiMB.Photos
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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