UCSD / DBMI seminar 2015-02-6
Transcript of UCSD / DBMI seminar 2015-02-6
Crowdsourcing and
Citizen Science for
Biology
Andrew Su, Ph.D.@andrewsu
http://sulab.org
February 6, 2015
UCSD
Slides: slideshare.net/andrewsu
Few genes are well annotated…2
Data: NCBI, February 2013
41%
65%
CTNNB1
VEGFA
SIRT1
FGFR2
TGFB1
TP53
MEF2C
BMP4
LEF1
WNT5A
TNF
20,473
protein-
coding
genes
Genes, sorted by decreasing counts
GO
An
no
tati
on
Co
un
ts
… because the literature is sparsely curated?3
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1983 1988 1993 1998 2003 2008 2013
Number of new PubMed-indexed articles
… because the literature is sparsely curated?4
0
10
20
30
40
1983 1988 1993 1998 2003 2008 2013
Average capacity of human scientist
6
0
Sooner or later, the
research community will
need to be involved in the
annotation effort to scale
up to the rate of data
generation.
The Long Tail is a prolific source of content7
Short
Head
Long Tail
Content
produced
Contributors (sorted)
News :
Video:
Product reviews:
Food reviews:
Talent judging:
Newspapers
TV/Hollywood
Consumer reports
Food critics
Olympics
Blogs
YouTube
Amazon reviews
Yelp
American Idol
Wikipedia has breadth and depth9
http://en.wikipedia.org/wiki/Wikipedia:Size_comparisons, July 2008
Articles
Words(millions)
Wikipedia Britannica
Online
10
We can harness the
Long Tail of scientists
to directly participate in
the gene annotation
process.
Wiki success depends on a positive feedback14
Gene wiki page utility
Number of
users
Number of
contributors
1001
2002
10,000 gene “stubs” within Wikipedia15
Protein structure
Symbols and
identifiers
Tissue expression
pattern
Gene Ontology
annotations
Links to structured
databases
Gene
summary
Protein
interactions
Linked
references
Huss, PLoS Biol, 2008
Utility
Users
Contributors
Gene Wiki has a critical mass of readers16
Total: 4.0 million views / month
Huss, PLoS Biol, 2008; Good, NAR, 2011
Utility
Users
Contributors
Gene Wiki has a critical mass of editors17
Increase of ~10,000 words / month from >1,000 edits
Currently 1.42 million words
Approximately equal to 230 full-length articles
Good, NAR, 2011
Utility
Users
Contributors
Editor
count Editors
Edits Edit c
ount
A review article for every gene is powerful18
References to the literature
Hyperlinks to related conceptsReelin: 98 editors, 703 edits since July 2002
Heparin: 358 editors, 654 edits since June 2003
AMPK: 109 editors, 203 edits since March 2004
RNAi: 394 editors, 994 edits since October 2002
Making the Gene Wiki more computable20
Structured annotationsFree text
Analyses
Text-mininghttp://fiehnlab.ucdavis.edu/projects/rice_metabolome/
Centralizing key data storage26
Source: http://commons.wikimedia.org/wiki/File:Wikidata_slides_Magnus_Manske,_Cambridge,_2014-02-27.pdf
Wikidata for biology31
is a
regulates
Interacts
with
Protein
Glycoprotein
Neural
development
VLDL receptor
Amyloid
precursor
protein
Property:P31
Property:P128
Property:P129
Q8054
Q187126
Q1345738
Q1979313
Q423510
Q414043
Reelin
http://www.wikidata.org/wiki/Q414043
Wikidata for biology32
Property:P31
Property:P128
Property:P129
Q8054
Q187126
Q1345738
Q1979313
Q423510
Q414043
http://wikidata.org/w/api.php?action=wbgetentities&ids=Q414043&languages=en
Current progress
• All human and mouse genes and
proteins loaded
• All diseases (Human Disease Ontology)
loaded
• Dataset of all drugs in preparation
• Datasets for gene-disease, drug-
disease, and drug-protein relationships
in preparation
33
The biomedical literature is growing fast…36
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1983 1988 1993 1998 2003 2008 2013
Number of new PubMed-indexed articles
… but it is very hard to query and compute38
Imatinib
Crizotinib
Erlotinib
Gefitinib
Sorafenib
Lapatinib
Dasatinib
…
Acute myeloid leukemia
Acute lymphoblastic leukemia
Chronic myelogenous leukemia
Chronic lymphocytic leukemia
Hodgkin lymphoma
Non-Hodgkin lymphoma
Myeloma
…
AND
Information Extraction39
1. Find mentions of high level concepts in
text
2. Map mentions to specific terms in
ontologies
3. Identify relationships between concepts
Disease mentions in PubMed abstracts40
NCBI Disease corpus
• 793 PubMed abstracts
• (100 development, 593 training, 100 test)
• 12 expert annotators (2 annotate each abstract)
6,900 “disease” mentions
Doğan, Rezarta, and Zhiyong Lu. "An improved corpus of disease mentions in
PubMed citations." Proceedings of the 2012 Workshop on Biomedical Natural
Language Processing. Association for Computational Linguistics.
Question: Can a group of non-scientists
collectively perform concept recognition in
biomedical texts?
41
Amazon Mechanical Turk (AMT)44
Requester
Amazon
For each task, specify:
• a qualification test
• how many workers per task
• how much we will pay per task
Manages:
• parallel execution of jobs
• worker access to tasks
via qualification tests
• payments
• task advertising
Workers
1. Create tasks
2. Execute
3. Aggregate
Instructions to workers45
• Highlight all diseases and disease abbreviations
• “...are associated with Huntington disease ( HD )... HD patients
received...”
• “The Wiskott-Aldrich syndrome ( WAS ) , an X-linked
immunodeficiency…”
• Highlight the longest span of text specific to a disease
• “... contains the insulin-dependent diabetes mellitus locus …”
• Highlight disease conjunctions as single, long spans.
• “... a significant fraction of familial breast and ovarian cancer , but
undergoes…”
• Highlight symptoms - physical results of having a
disease
– “XFE progeroid syndrome can cause dwarfism, cachexia, and
microcephaly. Patients often display learning disabilities, hearing loss,
and visual impairment.
Qualification test46
Test #1: “Myotonic dystrophy ( DM ) is associated with a ( CTG ) in
trinucleotide repeat expansion in the 3-untranslated region of a protein
kinase-encoding gene , DMPK , which maps to chromosome 19q13 . 3 . ”
Test #2: “Germline mutations in BRCA1 are responsible for most cases of
inherited breast and ovarian cancer . However , the function of the BRCA1
protein has remained elusive . As a regulated secretory protein , BRCA1
appears to function by a mechanism not previously described for tumour
suppressor gene products.”
Test #3: “We report about Dr . Kniest , who first described the condition in
1952 , and his patient , who , at the age of 50 years is severely
handicapped with short stature , restricted joint mobility , and blindness but
is mentally alert and leads an active life . This is in accordance with
molecular findings in other patients with Kniest dysplasia and…”
26 yes / no questions
Experimental design
• Task: Identify the disease mentions in
the 593 abstracts from the NCBI disease
corpus
– $0.06 per Human Intelligence Task (HIT)
– HIT = annotate one abstract from PubMed
– 5 workers annotate each abstract
49
This molecule inhibits the growth of a broad
panel of cancer cell lines, and is particularly
efficacious in leukemia cells, including
orthotopic leukemia preclinical models as
well as in ex vivo acute myeloid leukemia
(AML) and chronic lymphocytic leukemia
(CLL) patient tumor samples. Thus, inhibition
of CDK9 may represent an interesting
approach as a cancer therapeutic target
especially in hematologic malignancies.
This molecule inhibits the growth of a broad
panel of cancer cell lines, and is particularly
efficacious in leukemia cells, including
orthotopic leukemia preclinical models as
well as in ex vivo acute myeloid leukemia
(AML) and chronic lymphocytic leukemia
(CLL) patient tumor samples. Thus, inhibition
of CDK9 may represent an interesting
approach as a cancer therapeutic target
especially in hematologic malignancies.
Aggregation function based on simple voting50
5
0
1 or more votes (K=1)This molecule inhibits the growth of a broad
panel of cancer cell lines, and is particularly
efficacious in leukemia cells, including
orthotopic leukemia preclinical models as
well as in ex vivo acute myeloid leukemia
(AML) and chronic lymphocytic leukemia
(CLL) patient tumor samples. Thus, inhibition
of CDK9 may represent an interesting
approach as a cancer therapeutic target
especially in hematologic malignancies.
K=2
K=3 K=4
This molecule inhibits the growth of a broad
panel of cancer cell lines, and is particularly
efficacious in leukemia cells, including
orthotopic leukemia preclinical models as
well as in ex vivo acute myeloid leukemia
(AML) and chronic lymphocytic leukemia
(CLL) patient tumor samples. Thus, inhibition
of CDK9 may represent an interesting
approach as a cancer therapeutic target
especially in hematologic malignancies.
Comparison to gold standard51
F = 0.81, k = 2
• 593 documents
• 5 users / doc
• 7 days
• $192.90PrecisionRecall
Comparison to gold standard52
F = 0.87, k = 6
• 593 documents
• 15 users / doc
• 9 days
• $630.96
Precision
Recall
Comparison to gold standard53
0 1614121086420
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Workers per document
Maxim
um
F-s
core
Comparisons to text-mining algorithms54
F s
core
Text-mining
BA
NN
ER
NC
BO
Annota
tor
Mechanical
Turk
Comparisons to human annotators55
Average level of
agreement
between expert
annotators
(stage 1)
F = 0.76
Comparisons to human annotators56
F = 0.76F = 0.87
Average level of
agreement
between expert
annotators
(stage 2)
57
In aggregate, our worker
ensemble is faster, cheaper
and as accurate as a single
expert annotator for disease
concept recognition.
Information Extraction58
1. Find mentions of high level concepts in
text
2. Map mentions to specific terms in
ontologies
3. Identify relationships between concepts
Annotating the relationships59
This molecule inhibits the growth of a broad
panel of cancer cell lines, and is particularly
efficacious in leukemia cells, including
orthotopic leukemia preclinical models as
well as in ex vivo acute myeloid leukemia
(AML) and chronic lymphocytic leukemia
(CLL) patient tumor samples. Thus, inhibition
of CDK9 may represent an interesting
approach as a cancer therapeutic target
especially in hematologic malignancies.
therapeutic target
subjectpredicate
object
GENE
DISEASE
Does Mechanical Turk scale?60
1,000,000 articles per year
10 annotators / article
4 tasks / doc
$0.06 / task
$ 2,400,000 / year
Key stats
• Launched Jan 19, 2015
• In 2.5 weeks
– 1984 document annotations
– 80 unique users
– 22% complete
62
Docum
ent
annota
tions
64
Ben Good
Andra Waagmeester
Lynn Schriml, U Maryland
Elvira Mitraka, U Maryland
Gang Fu, NCBI
Evan Bolton, NCBI
Paul Pavlidis, U British Columbia
Peter Robinson, Charite
Many Wikipedia and Wikidata
editors
WP:MCB Project
Gene Wiki / Wikidata
Ramya Gamini
Louis Gioia
Salvatore Loguercio
Adam Mark
Erick Scott
Greg Stupp
Kevin Xin
Other Group members
Funding and Support
BioGPS: GM83924
Gene Wiki: GM089820
BD2K COE: GM114833
Contact
http://sulab.org
@andrewsu
+Andrew Su
Mark2Cure
Ben Good
Max Nanis
Ginger Tsueng
Chunlei Wu
Next slide!
Why do I Mark2Cure?65
I am retired, have a doctorate in
medical humanities, and have two
children with Gaucher disease. I am
just looking for some way to put my
education to use. Sounds like a perfect
situation for me.
My 4 year old daughter Phoebe is
living with and battling rare
disease.
I have Ehlers Danlos Syndrome. I hope to help people
learn about this painful and debilitating disorder, so that
others like me can receive more effective medical care.
Take part in
something that
helps humanity.
I Mark2Cure in memory of
my son Mike who had type 1
diabetes.
Studied biology in
college and I really
miss it!
In memory of my daughter
who had Cystic Fibrosis
Give back