@monarchinit @ontowonka “Not everyone can become a great artist, but a great artist can come from anywhere” Anton Ego, Ratatouille, 2007, Dixsney/Pixar Envisioning a world where everyone helps solve disease Melissa Haendel SWAT4LS 2015 Cambridge, England
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Envisioning a world where everyone helps solve disease
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@monarchinit@ontowonka
“Not everyone can become a great artist, but a great artist
can come from anywhere” Anton Ego, Ratatouille, 2007, Dixsney/Pixar
Envisioning a world where everyone helps solve disease
Melissa HaendelSWAT4LS 2015
Cambridge, England
Faith-based research
“I believe that my work on some obscure cell type in some obscure organism will matter to mankind one day”
Well, it can, and it does.
Four things it takes to solve an undiagnosed disease
1. Deep phenotyping the human organism
2. Crossing the language barrier
3. A lot of data from a lot of places
4. Very many people (who have faith)
1. DEEP PHENOTYPING THE HUMAN ORGANISM
PatientGenom
e/Exome
Filter
****
** ***** ****
Genomic data
Diagnosis,treatment
ATCTTAGCACGTTAC
ATCTTAGCACGTGACATCTTATCACGTTACATCTTAGCACGTTAC
What do all those variations do?
We only know the phenotypic consequences of mutation of <20% of the human coding genome
Patient
Genome
/Exome
Diagnosis,treatment
Filter
****
** ***** ****
Genomic data
Phenotype
Gene-Phenotype
Data
Environment
We have a common language for sequence data…. ATCTTAGCACGTTAC… ….not so much for phenotypes
CC2.0 European Southern Observatory https://www.flickr.com/photos/esoastronomy/6923443595
Can we help machines understand phenotypes?
“Palmoplantar
hyperkeratosis”
Human phenotype I have absolutely no
idea what that means
???
Image credits:
"HandsEBS" by James Heilman, MD - Own work. Licensed under CC BY-SA 3.0 via Commons – https://commons.wikimedia.org/wiki/File:HandsEBS.JPG#/media/File:HandsEBS.JPG
Marcin Wichary [CC BY 2.0 (http://creativecommons.org/licenses/by/2.0)], via Wikimedia Commons
A disease is a collection of phenotypes
Patient
Disease XDifferential diagnosis with similar but non-matching phenotypes is difficult
Flat back of head Hypotonia
Abnormal skull morphology Decreased muscle mass
Do we *really* need yet another clinical vocabulary?
Once OMIM is rendered computable, are we done yet?
Free text -> HPO enables phenotype semantic similarity matching
Mendelian disease integrationMerges sources together using: equivalence and subclass axioms derived from xrefs string matching manual efforts to fill gaps based on phenotypes and
Model data can provide up to 80% phenotypic coverage of the human coding genome
We learn different things from different organisms
2. CROSSING THE LANGUAGE BARRIER
Ulcerated paws
Palmoplantar hyperkeratos
is
Thick hand skin
Image credits:
"HandsEBS" by James Heilman, MD - Own work. Licensed under CC BY-SA 3.0 via Commons – https://commons.wikimedia.org/wiki/File:HandsEBS.JPG#/media/File:HandsEBS.JPG
http://www.guinealynx.info/pododermatitis.html
Challenge: Each database uses their own vocabulary/ontology
MPHP
MGIHPOA
Image credits:
"HandsEBS" by James Heilman, MD - Own work. Licensed under CC BY-SA 3.0 via Commons – https://commons.wikimedia.org/wiki/File:HandsEBS.JPG#/media/File:HandsEBS.JPG
http://www.guinealynx.info/pododermatitis.html
Challenge: Each database uses their own vocabulary/ontology
ZFA
MPDPO
WPO
HP
OMIA
VT
FYPO APOSNOMED
………
WB
PB
FB
OMIA
MGI
RGD
ZFIN
SGD
HPOAIMPC
OMIM
ICDQTLd
b
EHR
Image credits:
"HandsEBS" by James Heilman, MD - Own work. Licensed under CC BY-SA 3.0 via Commons – https://commons.wikimedia.org/wiki/File:HandsEBS.JPG#/media/File:HandsEBS.JPG
http://www.guinealynx.info/pododermatitis.html
Decomposition of complex concepts allows interoperability
Mungall, C. J., Gkoutos, G., Smith, C., Haendel, M., Lewis, S., & Ashburner, M. (2010). Integrating phenotype ontologies across multiple species. Genome Biology, 11(1), R2. doi:10.1186/gb-2010-11-1-r2
“Palmoplantar
hyperkeratosis”
increased
Stratum corneum
layer of skin
=Human phenotype
PATO
Uberon
Species neutral ontologies, homologous concepts
Autopod
keratinization
GO
Cross-species ontology integration
3. A LOT OF DATA FROM A LOT OF PLACES
Graph Views
DiverseG2P/D
source data
Source Ontologies Owl Loader
Graph Views
Monarch App
FacetedBrowsing
Phenotype
Matching
.ttl
.ttl
Input OutputPipeline
Putting it Together: Data + Ontologies
https://github.com/SciGraph/SciGraph
Data Integrated in SciGraph>25 sources>100 species
51M triples4M curated
associations2.2M G-P / G-D
associations
Genotype-phenotype integration
One sourceTwo sources3 or more
9%
91% of our 2.2 Million G2P associations required integrating 2 or more data sources (this number does not even include orthology (Panther))
Thomas MarkelloDong ChenJustin Y. Kwan Iren Horkayne-Szakaly Alan Morrison Olga Simakova Irina Maric Jay Lozier Andrew R. Cullinane Tatjana Kilo Lynn Meister Kourosh PakzadSanjay Chainani Roxanne Fischer Camilo Toro James G. White David AdamsCornelius BoerkoelWilliam A. Gahl Cynthia J. Tifft Meral Gunay-Aygun
Elizabeth Lee Amanda LinksWill Bone Murat SincanDamian SmedleyJules JacobsonNicole WashingtonElise FlynnSebastian KohlerOrion BuskeMarta GirdeaMichael Brudno Jeremy Band
Hans GoebleKaren BalbachNadine PfeiferSandra WernerChristian Linden
Clinical/care Pathology Ontologist CS/informatics Curator Basic research
Tracking Evidence and Provenance of G2P Associations
Evidence is a collection of information that is used to support a scientific claim or association
Provenance is a history of what processes led to the claim being made, what entities participated in these processes
Value of Evidence and Provenance Metadata context to evaluate credibility/confidence support filtering and analysis of data detailed history for attribution
Evidence and Provenance for a Variant-Phenotype Association
HP:0000252Pref Label: MicrocephalySynonyms: Decreased Head Circumference; Reduced Head Circumference; Small head circumferenceSuggested Synonyms : Small Head; Little Head; Small Skull; Little Skull; Small Cranium…