Keynote presented at the the Ninth International Biocuration Conference Geneva, Switzerland, April 10-14, 2016 The health of an individual organism results from complex interplay between its genes and environment. Although great strides have been made in standardizing the representation of genetic information for exchange, there are no comparable standards to represent phenotypes (e.g. patient disease features, variation across biodiversity) or environmental factors that may influence such phenotypic outcomes. Phenotypic features of individual organisms are currently described in diverse places and in diverse formats: publications, databases, health records, registries, clinical trials, museum collections, and even social media. In these contexts, biocuration has been pivotal to obtaining a computable representation, but is still deeply challenged by the lack of standardization, accessibility, persistence, and computability among these contexts. How can we help all phenotype data creators contribute to this biocuration effort when the data is so distributed across so many communities, sources, and scales? How can we track contributions and provide proper attribution? How can we leverage phenotypic data from the model organism or biodiversity communities to help diagnose disease or determine evolutionary relatedness? Biocurators unite in a new community effort to address these challenges.

1. Why the world needs PhenoPacketeers,
and how to be one
Melissa Haendel, PhD
April , 2016
Biocuration 2016
@monarchinit @ontowonka
haendel@ohsu.edu

2. What is a phenotype?
@ontowonka

3. Biology central dogma
ADAPTED FROM http://www.xkcd.com/295/
@ontowonka

4. Genes Environment Phenotypes+ =
Biology central dogma
Standards for encoding and exchanging data
must be up to these challenges.
This is where you come in.
@ontowonka

5. Genes Environment Phenotypes+ =
Computable encodings are essential
Base pairs
Variant notation (eg. HGVS)
Human Phenotype
Ontology
Mammalian
Phenotype Ontology
Medical procedure coding
Environment Ontology
@ontowonka

6. Genes Environment Phenotypes
VCF PXFGFF
Standard exchange formats exist for genes …
but for phenotypes? Environment?
BED
@ontowonka

7. The relationships too must be captured
It is not just the bits…
G-P or D (disease)
causes
contributes to
is risk factor for
protects against
correlates with
is marker for
modulates
involved in
increases susceptibility to
G-G (kind of)
regulates
negatively regulates (inhibits)
positively regulates (activates)
directly regulates
interacts with
co-localizes with
co-expressed with
P/D - P/D
part of
results in
co-occurs with
correlates with
hallmark of (P->D)
E-P
contributes to (E->P)
influences (E->P)
exacerbates (E->P)
manifest in (P->E)
G-E (kind of)
expressed in
expressed during
contains
inactivated by

8. The genome is sequenced, but…
…we still don’t know very much about what it does
3,435
OMIM
Mendelian Diseases with
no known genetic basis
?
66,396
ClinVar
Variants with no known
pathogenicity

9. Why we need all the organisms
Model data can provide up to
80% phenotypic coverage of the human coding genome

10. We learn different phenotypes from different organisms

11. B6.Cg-Alms1foz/fox/J
increased weight,
adipose tissue volume,
glucose homeostasis altered
ALSM1(NM_015120.4)
[c.10775delC] + [-]
GENOTYPE
PHENOTYPE
obesity,
diabetes mellitus,
insulin resistance
increased food intake,
hyperglycemia,
insulin resistance
kcnj11c14/c14; insrt143/+(AB)
Can we use model phenotypes to
inform genetic mechanisms of disease?
???

12. CC2.0 European Southern Observatory
https://www.flickr.com/photos/esoastronomy/6923443595
Crossing the language barrier

13. Ulcerated
paws
Palmoplantar
hyperkeratosis
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

14. Semantics serve as a bridge
http://xkcd.com/1406/

15. Challenge: Each database uses their
own vocabulary/ontology
MP
HP
MGI
HPOA

16. Challenge: Each database uses their
own phenotype vocabulary/ontology
ZFA
MP
DPO
WPO
HP
OMIA
VT
FYPO
APO
SNO
MED
…
…
…
WB
PB
FB
OMIA
MGI
RGD
ZFIN
SGD
HPOA
EHR
IMPC
OMIM
…
QTLdb

17. Can we help machines understand
phenotype terms?
“Palmoplantar
hyperkeratosis”
Human phenotype
I have
absolutely no
idea what that
means

18. 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

19. Harmonizing diseases, phenotypes, anatomy, and genotypes

20. Current weighted features
• Breadth of phenotypic coverage
• Depth/specificity of phenotypic coverage
• Rarity
Planned algorithmic features:
• Disease and phenotype staging
• Age of onset
• Asserted absence of phenotypes
Fuzzy phenotype profile matching:
Patients  Diseases  Models
www.owlsim.org

21. Diagnosing an undiagnosed disease

22. Why model organisms matter to patients

23. The prevailing clinical diagnosis pipelines leverage
only a tiny fraction of the available data
PATIENT EXOME
/ GENOME
PATIENT PHENOTYPES
PATIENT ENVIRONMENT
PUBLIC GENOMIC DATA
PUBLIC PHENOTYPE,
DISEASE DATA
PUBLIC ENVIRONMENT,
DISEASE DATA
POSSIBLE DISEASES
DIAGNOSIS & TREATMENT
Under-utilized data

24. It takes an interoperable village to diagnose
a rare platelet syndrome
http://bit.ly/stim1paper
Phenotypic
profile
Genes
Heterozygous,
missense mutation
STIM-1
MGI mouse
N/A
Heterozygous,
missense mutation
STIM-1
N/A
Ranked STIM-1 variant maximally pathogenic
based on cross-species G2P data,
in the absence of traditional data sources
http://bit.ly/exomiser
Stim1Sax/Sax

25. Introducing PhenoPackets
It’s exactly what you think it is:
a packet of phenotype data to be used
anywhere, written by anyone

26. If it is alive, it can be PhenoPackaged
Some biodiversity images adapted from http://i.vimeocdn.com/video/417366050_1280x720.jpg
Model Organisms
Biodiversity Crops Domestic Animals
Disease vectors
Epidemiological
Monitoring
Drug discovery
& Development
Rare Disease
Diagnosis
Personalized
Medicine
Environmental
Monitoring
Patients & Cohorts
Genetic
Engineering
Mechanistic
Discovery

27. What is in a PhenoPacket?
This is “Maru”,
a 4-year-old, male
cat of the Scottish
Fold breed
abnormal
sheltering behavior
[MP:0014039]
(onset at birth)
Biography
Phenotypes
&qualifiers
youtube.com/user
/mugumogu
Weighs 6kg
Measurements
Source

28. title: "age of onset example"
persons:
- id: "#1"
label: "Donald Trump"
sex: "M"
phenotype_profile:
- entity: "person#1"
phenotype:
types:
- id: "HP:0200055"
label: "Small hands"
onset:
description: "during development"
types:
- id: "HP:0003577"
label: "Congenital onset"
evidence:
- types:
- id: "ECO:0000033"
label: ”Traceable Author Statement"
source:
- id: "PMID:1"
Image credits: upi.com
What does a PhenoPacket look like?
Canonical JSON format

29. title: "measurement example, taken from genenetwork.org"
organisms:
- id: "#1"
label: "BXD mouse population”
taxon: NCBITaxon:10090
phenotype_profile:
- entity: "#1"
phenotype:
description: "cerebellum weight"
types:
- id: "PATO:0000128"
label: "weight"
measurements:
- unit: mg
value: 61.400
property_values:
- property: standard_error
filler: 2.38
attribute_of:
types:
- id: "UBERON:0002037"
label: "cerebellum"
onset:
description: "measured in adults"
types:
- id: "MmusDv:0000061"
label: "early adult"
Ontology of
Statistical
properties
We can represent
population
phenotypes too
attribute
For non-abnormal
phenotypes we can
use a trait ontology,
or a building block
approach, with
• PATO
• Uberon
Measured entity
UO
How does it handle measurements?

30. Phenopackets for laypersons
Image credits: ngly1.org
• Dry eyes
• Developmental delay
• Elevated liver function
phenotype_profile:
- entity: ”patient16"
phenotype:
types:
- id: "HP:0000522"
label: ”Alacrima"
onset:
description: ”at birth"
types:
- id: "HP:0003577"
label: "Congenital onset"
evidence:
- types:
- id: "ECO:0000033"
label: ”Traceable Author Statement"
source:
- id: ”
https://twitter.com/examplepatient/status/1
• Patient registries
• Social media

31. Human Phenotype Ontology, now with 6,200
plain language synonyms
for patients, families, and non-experts
http://bit.ly/hpo-biocuration

32. Phenopackets for journals
Each article can be
associated with a
phenopacket
Robinson, P. N., Mungall, C. J., & Haendel, M. (2015). Capturing phenotypes for precision
medicine. Molecular Case Studies, 1(1), a000372. doi:10.1101/mcs.a000372
Each phenopacket
can be shared via
DOI in any repository
outside paywall (eg.
Figshare, Zenodo,
etc)

33. So, do you expect us to put these together
ourselves?
Emerging tool: WebPhenote
(based on Phenote)
create.monarchinitiative.org

34. WebPhenote
Form-based Graph-based
Noctua / LEGO inside

35. PhenoPacket formats
CSV JSON RDF OWL
Export phenopacket to

36. Example of export
https://monarchinitiative.org/variant/ClinVarVariant:88756

37. Example of export

38. The PhenoPackets ecosystem
Mechanistic discovery
Improved
searchability
Integrated Data Landscape
Tool/algorithm creation
Cohort
identification
Patient
registries
Databases,
Web tools,
AlgorithmsPhenopacket
Registry
JournalsDiagnostic
screening
programs Clinical
trials
Phenopacket
flow
Primarybenefits
tostakeholders
Patients/
Families
Physicians
Patient
matchmaking
Diagnosis speed/accuracy
Organismal
biologist
www.phenopackets.org
https://github.com/phenopackets/

39. PHENOTYPING ISN’T FREE;
SO HOW MUCH IS ENOUGH?
bit.ly/annotationsufficiency
Enlarged ears
Dark hair
Blue skin
Pointy ears
Hair on head
Horns
Enlarged lip
Increased skin pigmentation
yes
no
!

40. THE MORE PHENOTYPE DATA WE HAVE,
THE BETTER ABLE WE ARE
TO ANSWER THAT QUESTION
bit.ly/annotationsufficiency
• Depth/specificity of phenotypic coverage
• Rarity
• Breadth of phenotypic coverage

41. Which phenotypes
(and sets of phenotypes)
enable precision recall and matching
Enlarged ears (2)Dark hair (6) Female (4)
Male (4)
Blue skin (1)
Pointy ears (1)
Hair absent on head (1)
Horns present (1)
Hair present
on head (7)
Enlarged lip (2)
Increased skin
pigmentation (3)

42. PhenoPackets make phenotype data:
Findable
Accessible outside paywalls and private data sources
Attributable
Interoperable and Computable,
Reusable, exchangeable across contexts and disciplines
FAIR++

43. Sign up below to receive updates
Or to provide feedback and requirements
http://bit.ly/biocuration2016
Thank you!
Live Long and Phenotype

44. Acknowledgements
Lawrence Berkeley
Chris Mungall
Suzanna Lewis
Jeremy Nguyen
Seth Carbon
Charité
Peter Robinson
Sebastian Kohler
RTI
Jim Balhoff
Cyverse
Ramona Walls
U of Pittsburgh
Harry Hochheiser
OHSU
Matt Brush
Kent Shefchek
Julie McMurry
Tom Conlin
Nicole Vasilevsky
Queen Mary College
London
Damian Smedley
Jules Jacobson
Garvan
Tudor Groza
Alfred Wegener
Pier Buttigieg
FUNDING: NIH Office of Director: 1R24OD011883; NIH-UDP: HHSN268201300036C,
HHSN268201400093P, Phenotype Ontology Research Coordination Network (NSF-DEB-0956049)
With special thanks to Julie McMurry for excellent graphic design