New Data Release for MyVariant.info 201708
Another fresh data release for MyVariant.info is out! In this data release, we have updated the data from ClinVar and UniProtKB to their latest versions, and also added variant annotation from CIViC and Cancer Genome Interpreter. Here are more details.
Data Sources Updated
ClinVar was updated to its latest (same version for both hg19 and hg38 assembly). And the variant annotations from UniProtKB were also updated to the latest (hg38 only):
Some numbers for GRCh37/hg19 variants:
| last release | new release | # of variants in last release |
# of variants in new release |
|
| ClinVar | 2017-06 | 2017-08 | 307,101 | 310,280 |
Similarly, some numbers for GRCh38/hg38 variants:
| last release | new release | # of variants in last release |
# of variants in new release |
|
| UniProtKB | 2017-03 | 2017-07 | 477,711 | 527,607 |
| ClinVar | 2017-06 | 2017-08 | 307,286 | 310,577 |
ClinVar annotations are available under "clinvar" subfields for each annotated variant. UniProtKB annotations are available under "uniprot" subfields for each annotated variant. MyVariant.info aggregates annotations from ClinVar, dbSNP, dbNSFP and other 17 sources for each variant, so you can access them all in one request.
The total number of unique variants is now over 424M (424,524,227), slightly higher than our previous release on June 2017, which is 424,519,520. More details about the variant data we provide from MyVariant.info are always available from our documentation. The programmatic access of this information is available from our metadata endpoint (and hg38 metadata).
New Data Sources Added
In this data release, we added variant annotations from CIViC and Cancer Genome Interpreter (CGI), through our collaborations with the GA4GH VICC working group. Both provide extensive annotations of cancer-associated genetic variants. And more specifically:
CIViC is an open access, open source, community-driven web resource for Clinical Interpretation of Variants in Cancer. The goal of CIViC is to enable precision medicine by providing an educational forum for the dissemination of knowledge and active discussion of the clinical significance of cancer genome alterations.
Cancer Genome Interpreter is designed to support the identification of tumor alterations that drive the disease and detect those that may be therapeutically actionable. CGI relies on existing knowledge collected from several resources and on computational methods that annotate the alterations in a tumor according to distinct levels of evidence.
You can access the data from CIViC under "civic" field. And note that "civic" field is only available for hg19 variants. Here are a few query examples:
curl 'http://myvariant.info/v1/variant/chr11:g.534285C%3ET?fields=civic'
curl 'http://myvariant.info/v1/variant/chr1:g.11187094G%3ET?fields=civic'
curl 'http://myvariant.info/v1/variant/chr17:g.7578455C%3EA?fields=civic'
You can access the data from Cancer Genome Interpreter under "cgi" field. And note that "cgi" field is only available for hg19 variants. Here are a few query examples:
curl 'http://myvariant.info/v1/variant/chr3:g.178936091G%3ET?fields=cgi'
curl 'http://myvariant.info/v1/variant/chr3:g.41266109C%3ET?fields=cgi'
curl 'http://myvariant.info/v1/variant/chr3:g.41266113C%3EG?fields=cgi'
You can also do some combined queries just like other data sources we have:
curl 'http://myvariant.info/v1/variant/chr2:g.29443600G%3ET?fields=civic%2Ccgi'
curl 'http://myvariant.info/v1/query?q=_exists_:civic%20AND%20_exists_:cgi&fields=civic%2Ccgi'
curl 'http://myvariant.info/v1/query?q=civic.evidence_items.drugs.name:crizotinib&fields=civic'
curl 'http://myvariant.info/v1/query?q=cgi.gene:ALK%20AND%20cgi.association:resistant&fields=cgi'
That's all! And as always, feel free to reach us at help@myvariant.info or @myvariantinfo if you have any questions or feedback.
Join Mark2Cure and Dazzle4Rare
From August 13th to August 20th, Mark2Cure will be participating in the #Dazzle4Rare campaign to raise awareness for rare diseases. Did you know? About 10% of the population lives with a rare disease, and roughly 50% of rare diseases don’t have any sort of disease-specific foundation to support or research those diseases. See more interesting statistics about rare disease at Global Genes.
If you have a rare disease story you would like us to highlight for the campaign, please get in touch!
What's new in Mark2Cure?
The EDEM1 Entity Recognition mission is over 95% complete, please help us finish it so we can launch the next one. If it seems like we’ve been quiet lately it’s because we’ve been preparing for some major updates. If you’re curious about what’s in the pipeline or would like to preview/provide feedback for potential future interface designs, we’d LOVE to hear from you! Your feedback is how we improve! If not for our many marvelous Mark2Curators providing constructive criticism, Mark2Cure would be a clunky and more difficult to use platform.
Speaking of our volunteers, citizen scientists, participants, contributors, volunpeers, and Mark2Curators…there was an interesting discussion earlier today within the citizen science community on the best way to address the amazing people who help make science happen. In fact, a bunch of researchers even wrote an interesting paper about the pros and cons of different terminology
Which takes us to our current poll.
Lastly, there is an ongoing effort to increase discussion, collaboration, and cooperation within the citizen science (or whatever you wish to call it) community. This has led our friend Alice to introduce #CitSciStories. You may think that your contributions to science in your spare time are no big deal, but from the perspective of the researchers who rely on these contributions...you are amazing! Inspiring! Awesome beyond words! We love what you do and we love learning from you and getting to know you. If you'd like to share your story and inspire others to help science, please get in touch with Alice (@PenguinGalaxy). You can learn more about the #CitSciStories effort, here.
Upcoming #CitSciChat on Biomedical Citizen Science
New Mark2Cure Video added to our youtube playlist!
The Citizen Science Conference in May was very productive, and the last of Mark2Cure's recorded talks is now available on our youtube channel. As previously mentioned, Max delivered the project slam for Mark2Cure and was selected as one of the top three to deliver an abbreviated version during the 'Night in the Clouds' event.
View the two-minute talk here:
Biomedical CitSciChat on Wed. July 19th, at 11:00am PT
Speaking of the conference, we were able to connect in person with a lot of lovely people in the citizen science arena, especially the amazing people from @EyesOnAlz, @CitSciBio, and @CochraneCrowd. Because we're all passionate about bringing citizen science to biomedical research, we organized a panel for a biomedical #citscichat. Caren Cooper (@CoopSciScoop) kindly agreed to moderate the chat as usual, and Pietro (@pmichelu, @EyezOnAlz) was able to convince @foldit's Seth Cooper to join the panel.
What: Hour long chat on biomedical citizen science (#CitSciChat)
Where: online via twitter
When: Wed July 19 2:00pm ET (11:00am PT)
Why: Because citizen science is used in biomedical research too
Who: Everyone interested in citizen science is welcome to join this chat which will be moderated by citizen science expert and author, Caren Cooper. The panel so far includes:
Mark2Cure of course! Mark2Cure is a citizen science project for addressing the big data issue of biomedical literature. Citizen scientists help look for clues about NGLY1-deficiency in curated literature. (@Mark2Cure/@gtsueng, @x0xmaximus, @AndrewSu) Cochrane Crowd is a citizen science project from the Cochrane Collaborative, and also looks to make biomedical literature more useful. Citizen Scientists help identify randomized controlled trials so that Cochrane Reviewers can use them to answer important medical questions. (@Cochrane_Crowd, @annanoelstorr) EyesOnAlz/Stall Catchers is a citizen science project from the Human Computation Institute to identify blood blockages in short videos of the brain. Their game is super fun, helps with Alzheimer's research AND they have a major event (Catchathon) coming up. If you would like to host a local catchathon, check out this post. (@EyesOnAlz, @seplute, @Clair_csg, @pmichelu) CitSciBio is NIH's new biomedical citizen science hub. It is sponsored by the Division of Cancer Biology at the National Cancer Institute. There are tools for collaborating, creating projects, and now you can login via your scistarter account. (@citscibio) Fold.it is a long standing, and very successful citizen science game which empowers gamers and volunteers to help determine the structure of proteins important to biomedical research. Seth Cooper from Northeastern University has agreed to join the panel to share about this wildly successful project. (@UWGameScience)
Beat the heat and help science!
Need an excuse to stay indoors, avoid chores, and avoid the summer heat? Look no further! One of our current missions is over 80% complete. Help us finish it!
Integrating Wikidata and other linked data sources – Federated SPARQL queries
This blog is about running federated SPARQL queries on Wikidata. A federated query is a special type of SPARQL query that runs on more then one SPARQL endpoint. It allows access to multiple linked data resources in a single query. Below is a template of a federated query.
Structure of a federated query. It contains query patterns for both the local endpoint (green box) and a remote endpoint (blue box). The address of the remote SPARQL endpoint is expressed with the SERVICE keyword. (sourcecode)
The WikiData Query Service (WDQS) now supports federated SPARQL queries on a limited number of endpoints. Remote SPARQL endpoints can be added to the list of supports endpoints by nomination.
Wikidata aims to provide the sum of all knowledge to the world at large. To fulfil this, it needs to be a hub to the total knowledge space. After all, different technical, legal or social limitations exist to include all in a single repository. Through federation or distributed querying, local and remote data can be combined. Here we explore three ways to apply this type of querying on Wikidata content.
From Wikidata to an external SPARQL endpoint (Wikipathways)
The following query applies federation to integrate between a pathway from Wikipathways and Wikidata. Wikidata contains items on human pathways from Wikipathways. Metabolic interactions are not yet captured in Wikidata. Through federation, these metabolic interaction can be obtained. In reverse direction is it possible to obtain properties of pathway elements from Wikidata. Take for example the “Sudden Infant Death Syndrome (SIDS) Susceptibility Pathways (Homo sapiens)” pathway. It contains various biological interactions. We could now, using federated queries, get properties such as the mass of a given pathway element.
Sudden Infant Death Syndrome (SIDS) Susceptibility Pathways (Homo sapiens)” pathway (http://www.wikipathways.org/index.php/Pathway:WP706)
Using this query as input, with a federated query it is possible to enrich this pathway with properties not captured in Wikipathways. One example would be the following query that takes interactions from the above pathway and combines that with the mass of the individual pathway parts.
You can run this query here or watch it run on youtube
From a remote SPARQL endpoint to Wikidata
If a remote SPARQL endpoint is not (yet) eligible to be used in the WDQS, it is possible to run the query from the external endpoint. That is, if the external endpoint accepts submitting federated SPARQL queries. The SPARQL endpoint of UniProt is a nice example. UniProt includes much more properties for proteins than currently captured in Wikidata. Properties that due to the more restrictive nature of the applicable license can’t be included in Wikidata. The following federated SPARQL endpoint runs on the SPARQL endpoint of UniProt. It selects all human UniProt entries with a sequence variants that leads to a loss of function, and also physically interacts with a drug used as an enzyme inhibitor.
Integrating Wikidata content with data from UniProt using federated query submitted at http://sparql.uniprot.org
From a local SPARQL endpoint to Wikidata (Data from a database that will never go into WD)
Another interesting use case where federation can be quite handy, is in the context of local data. Epidemiological data on for example Zika outbreaks can contain large set of measurements spread over multiple time frames. Loading those measurements into Wikidata, can be be difficult especially if the outbreak is ongoing resulting in new data arriving in rapid intervals. One solution to enable integration with that data and other resources like Wikidata is running distributed queries from a local SPARQL endpoint. The local SPARQL endpoint has two roles, first it collects the measurements from the different Zika studies, secondly federated queries can be executed to enrich these measurements with knowledge from Wikidata. We have create an example script that takes data on Zika outbreaks, converts that to linked data as RDF, which is then loaded in a local SPARQL endpoint. This prototype is available on github.
This approach also works when one would like to integrate sensitive data (clinical patient data) with external WIkidata knowledge if the local endpoint is maintained from within a secure infrastructure which allows getting data from outside the infrastructure, but prevents exports.
Indeed SPARQL has a steep learning curve.
Although writing SPARQL queries can be perceived as being quite intimidating, the feature to run federated queries on Wikidata content is very valuable and needed to make Wikidata the central hub of research data in the life sciences. The effort to learn SPARQL is worth it. Fortunately, Wikidata provides a large set of examples. Either for inspiration or as learning material.
There are also quite some developments to make writing queries easier.
There is also a R package that integrates SPARQL with R scripts, where the example queries from Wikidata can be scraped, which means that one could use the advantages SPARQL offers without writing a SPARQL query, simply by building on what others already made.
Finally, there is always the help of the Twitter space. Many are quite eager to share SPARQL knowledge.
The Gene Wiki project: Looking to the future v.2017
The Gene Wiki project has been generously funded by the National Institutes for General Medical Sciences (NIGMS) since 2009. As the second funding period is wrapping up early next year, it was time to once again look forward and think about our vision for the next 4-5 years. Posted below is what we came up with, submitted earlier this week to the NIH as a competing renewal proposal with Lynn Schriml and Kristian Andersen as co-Investigators. Fingers crossed!
Also a fine time to recognize that this proposal resulted from the direct and indirect contributions of so many people — postdocs, grad students, staff, past and current collaborators, Wikidata and Wikipedia communities, etc etc — far too many to name individually here. For a mostly comprehensive list, please see our grant-related publications.
New Data Release for MyVariant.info 201706
Another fresh data release for MyVariant.info is out! In this data release, we have updated the data from ClinVar to their latest versions, and also added two new fields under ClinVar and ExAC to handle specific cases, including genotype set and multi-allelic variants. Here are more details.
Data Sources Updated
ClinVar was updated to its latest (same version for both hg19 and hg38 assembly):
Some numbers for GRCh37/hg19 variants:
| last release | new release | # of variants in last release |
# of variants in new release |
|
| ClinVar | 2017-04 | 2017-06 | 282,772 | 307,101 |
Similarly, some numbers for GRCh38/hg38 variants:
| last release | new release | # of variants in last release |
# of variants in new release |
|
| ClinVar | 2017-04 | 2017-06 | 282,956 | 307,286 |
ClinVar annotations are available under "clinvar" subfields for each annotated variant. MyVariant.info aggregates annotations from ClinVar, dbSNP, dbNSFP and other 12 sources for each variant, so you can access them all in one request.
The total number of unique variants is now over 424M (424,519,520), slightly higher than our previous release on April 2017, which is 424,515,266. More details about the variant data we provide from MyVariant.info are always available from our documentation. The programmatic access of this information is available from our metadata endpoint (and hg38 metadata).
New Field for genotype set under ClinVar
There are a few submissions in ClinVar that represent assertions about simple or complex genotypes. To include this information in MyVariant.info, we have included a new genotypeset field under clinvar. There are two subfields under genotypeset, which is genotype and type. The "genotype" field records all variants as hgvs ids sharing the same genotype with the target variant. And the "type" field specifies the genotype which these variants are sharing, e.g. "CompoundHeterozygote".
- Query for variants having "genotypeset" information:
curl 'http://myvariant.info/v1/query?q=_exists_:clinvar.genotypeset'
* Or query for the genotypeset information for a specific variant:
curl 'http://myvariant.info/v1/variant/chr5:g.151208511G>A?fields=clinvar.genotypeset'
{
"_id": "chr5:g.151208511G>A",
"_version": 2,
"clinvar": {
"_license": "https://goo.gl/OaHML9",
"genotypeset": {
"genotype": [
"chr5:g.151239534C>A",
"chr5:g.151208511G>A"
],
"type": "CompoundHeterozygote"
}
}
}
New Field for multi-allelic under ExAC and ExAC-nonTCGA subset.
A multiallelic site is a specific locus in a genome that contains three or more observed alleles, again counting the reference as one, and therefore allowing for two or more variant alleles. The VCF source file from ExAC provides information about multi-allelic variants by organizing information about all multi-allelic variants at the same locus in one record. Hence, we decide to include a 'multi-allelic' field under 'exac'. The field will list all multi-allelic variants as hgvs ids related to a specific variant.
Thus, users could query for all multi-allelic variants for a target variant, e.g. chr10:g.103234255C>G using:
curl 'http://myvariant.info/v1/variant/chr12:g.103234255C>G?fields=exac.multi-allelic'
{
"_id": "chr12:g.103234255C>G",
"_version": 3,
"exac": {
"_license": "https://goo.gl/MH8b34",
"multi-allelic": [
"chr12:g.103234255C>T",
"chr12:g.103234255C>G"
]
}
}
Or query for all multi-allelic variants in ExAC using:
curl 'http://myvariant.info/v1/query?q=_exists_:exac.multi-allelic'
Please note that these two fields do not introduce any incompatible changes in the data structure, so your existing code should just work fine.
That's all! And as always, feel free to reach us at help@myvariant.info or @myvariantinfo if you have any questions or feedback.
Happy Fathers Day!
A HUGE thanks to all the dads (and EVERYONE) who has been contributing to make a difference for the NGLY1 families.
Shipping delays Apologies to international prize and drawing winners who were waiting for their prizes. Most of the international packages that we shipped out in May/June have been returned to us due to customs issues (fortunately, this happened at some point prior to shipping so the postage on these is still good, unfortunately, it took a long time for these to get back to us so we can address the issue). We’ll be trying again to get these out ASAP.
Max’s original project slam now online
As mentioned in our previous newsletter, Max delivered the project slam for Mark2Cure at the Citizen Science Conference in Minnesota. The project slam talks were supposed to have been recorded and still may be released by the Citizen Science Association someday, but we couldn’t wait. Here’s our recording of Max’s project slam. He finished within his allotted four minutes, and was engaging enough to win one of three invitations to deliver an even shorter version of the slam at an even the following day.
You can check it out here: https://www.youtube.com/watch?v=7kxlhhFLdmM
You be the scientist! One thing we’ve heard (and quite agree with) at the Citizen Science Conference is that trained volunteers are capable of doing more than simple tasks. Mark2Curators have very much fed into the tutorial process, and played an important role in testing and improving the design of the interface. The entities our users have identified from the text have already yielded interesting clues which we’ve used to expand the set of documents to investigate, and by now, there are users who have read a lot of abstracts—A LOT! If you’ve read something that sticks out in your mind as being potentially related to NGLY1-deficiency, share it with us! We’d love to hear YOUR hypothesis on what might be an interesting term to explore and why.
Science Game Lab: tool for the unification of biomedical games with a purpose
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| Figure 1. SGL home page demonstrating site-wide high score list, game listing, and links to achievements, help, and user profile information. |
 |
| Figure 2. Badges displayed on user’s profile page. Available badges not yet achieved are greyed out. |
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| Figure 3. The heads up display provided by the SGL iframe. Shows events captured by the API and provides users with immediate feedback. |
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| Figure 4. Tasks in SGL can be grouped into quests. The figure shows a particular user’s progress through various quests available within the system. |
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games meant for mobile devices
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development of quests that span multiple games
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teachers to build SGL-focused lesson plans and track student progress
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creating new ‘SGL-native’ games
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integration with external authentication systems
Building communities of knowledge with Wikidata
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answering queries across topics ranging from potential new cancer drugs to today’s birthdays to subway stations in Paris.
Happy Memorial Day weekend!
The last few weeks have been a bit hectic, so we've got plenty of news and info to share with you.
First of all, if you haven't seen it yet, Cochrane Crowd has posted about about our joint webinar and the #MedLitBlitz. If you missed the webinar or had technical difficulties/time zone issues with it, it's available on youtube. The prize packages for the top three participants of #MedLitBlitz are packed and will be shipped either today or early next week (depending on whether or not shipments have been picked up for today or not).
Secondly, Mark2Cure was at the Citizen Science Association conference from 2017.05.15-2017.05.20, and was fortunate enough to share about YOUR work to an audience of scientists who LOVE citizen science! More than a few researchers stopped to introduce themselves to me and spoke highly of our community! Although it's always weird to hear a recording of your own voice, I recorded my presentation because it wouldn't be fair to talk about the amazing work you've done without sharing it with you! You can find my presentation for the biomedical session in our youtube channel. On a side note, I know the audio quality isn't the best which is why I've transcribed it using youtube's captioning software. If you have trouble hearing the presentation (because of the poor audio quality), please turn on the closed captions.
Max also delivered two lightning talks for the event, which I hope to upload soon.
In addition to the talks, we had a poster for Mark2Cure and a table at two public events.
We were especially pleased to be so close to our buddy at Cochrane Crowd for this event
Lastly, it looks like one of the missions was completed just as I was settling back in after the conference. A HUGE thanks to everyone that helped complete the carpingly mission. A new mission has been launched in its place, so check it out if you have some free time.