Tag Archives: phenotype


Friday SNPpets

This week’s SNPpets include stories about the FlyBase memoriam for Bill Gelbart, Phenolyzer for gene discovery from phenotypes, tissue- and tumor-PPI comparison, Beacon, shotgun metagenomics, the future decade in genomics, no-so-scary personal genome sequencing and apps for it, DNA-barcoded beer, and more.

Welcome to our Friday feature link collection: SNPpets. During the week we come across a lot of links and reads that we think are interesting, but don’t make it to a blog post. Here they are for your enjoyment…

Video Tip of the Week: Human Phenotype Ontology, HPO

Typically, our Tips-of-the-Week cover a specific software tool or feature that we think readers would maybe like to try out. But this week’s tip is a bit different. It’s got a conceptual piece that is important, as well as referencing several software tools that work with this crucial concept to enable interoperability of many tools, helping us link different data types in a common framework.

Conceptually, the Human Phenotype Ontology (HPO) is much like other controlled vocabulary systems you may have used in genomics tools–like Gene Ontology, Sequence Ontology, or others that you might find at the National Center for Biomedical Ontology. We’ve covered the idea of broad parent terms, increasingly precise child terms, and standard definitions in tutorial suites. It’s important to standardize and share the same language to describe the same things among different projects, software providers, and as we move more genomics to the clinic, sharing descriptors for human phenotypes and conditions will be crucial.

The concepts and strategies are becoming mature at this point. and we now have lots of folks who agree and want to use these shared descriptors. A really nice overview of the state of phenotype descriptions and how to use them for discovery and for integration across many data resources was published earlier this year: Finding Our Way through Phenotypes.  It also offers recommendations for researchers, publishers, and developers to support and use a common vocabulary.

For this week’s video, I’m highlighting a lecture by one of the authors of that paper, Peter Robinson. It’s a seminar-length video, but it covers both the key conceptual features of the HPO, provides some examples of how it can be useful in translational research settings, and also describes the range of tools and databases that are using the HPO now. I think it’s worth the time to hear the whole thing. The audio is a bit uneven in parts, but you can get the crucial stuff.

The early part is about the concepts of specific terms, synonyms, and shared terms that can mean completely different things (think American football and European football). He describes the phenotype ontology. There are examples of research that leads to phenotypes that are then used as discovery and diagnostic tools. He talks about tools that utilize the HPO right now, including Phenomizer for obtaining or exploring appropriate terms, PhenIX, Phenotypic Interpretation of eXomes for prioritization of candidate genes in exome sequencing data sets. There is also PhenoTips, that can help you to collect and analyze patient data (and also edit pedigrees).

Many large scale projects and key genomics tools employ the human phenotype ontology.

Many large scale projects and key genomics tools employ the human phenotype ontology.

He also notes how tools like DECIPHER, NCBI Genetic Testing Registry, GWAS Central, and many more include the human phenotype vocabulary. This is a great sign for a project like this, that’s it is being adopted by so many groups and tools world-wide. They’ve also worked with key large-scale projects in this arena to ensure that the vocabulary is suited and workable, and update them when needed. They credit OMIM and Orphanet as being crucial to their efforts as well. As part of the Monarch Initiative, there seems to be solid support going forward as well.

There are more tools to discuss, but I’m going to save those for another post. This one is already loaded with things you should check out, so be sure to come back for further exploration of the HPO-related tools and projects that are worth exploring.

Quick links:

Human Phenotype Ontology: http://www.human-phenotype-ontology.org/

Phenomizer: http://compbio.charite.de/phenomizer/

PhenIX: http://compbio.charite.de/PhenIX/

PhenExplorer: http://compbio.charite.de/phenexplorer/

PhenoTips: https://phenotips.org/

Monarch Initiative: http://monarchinitiative.org/

Deans A.R., Suzanna E. Lewis, Eva Huala, Salvatore S. Anzaldo, Michael Ashburner, James P. Balhoff, David C. Blackburn, Judith A. Blake, J. Gordon Burleigh, Bruno Chanet & Laurel D. Cooper & (2015). Finding Our Way through Phenotypes, PLoS Biology, 13 (1) e1002033. DOI: http://dx.doi.org/10.1371/journal.pbio.1002033

Kohler, S., Doelken, S., Mungall, C., Bauer, S., Firth, H., Bailleul-Forestier, I., Black, G., Brown, D., Brudno, M., Campbell, J., FitzPatrick, D., Eppig, J., Jackson, A., Freson, K., Girdea, M., Helbig, I., Hurst, J., Jahn, J., Jackson, L., Kelly, A., Ledbetter, D., Mansour, S., Martin, C., Moss, C., Mumford, A., Ouwehand, W., Park, S., Riggs, E., Scott, R., Sisodiya, S., Vooren, S., Wapner, R., Wilkie, A., Wright, C., Vulto-van Silfhout, A., Leeuw, N., de Vries, B., Washingthon, N., Smith, C., Westerfield, M., Schofield, P., Ruef, B., Gkoutos, G., Haendel, M., Smedley, D., Lewis, S., & Robinson, P. (2013). The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data Nucleic Acids Research, 42 (D1) DOI: 10.1093/nar/gkt1026

Köhler, S., Schulz, M., Krawitz, P., Bauer, S., Dölken, S., Ott, C., Mundlos, C., Horn, D., Mundlos, S., & Robinson, P. (2009). Clinical Diagnostics in Human Genetics with Semantic Similarity Searches in Ontologies The American Journal of Human Genetics, 85 (4), 457-464 DOI: 10.1016/j.ajhg.2009.09.003

Zemojtel, T., Kohler, S., Mackenroth, L., Jager, M., Hecht, J., Krawitz, P., Graul-Neumann, L., Doelken, S., Ehmke, N., Spielmann, M., Oien, N., Schweiger, M., Kruger, U., Frommer, G., Fischer, B., Kornak, U., Flottmann, R., Ardeshirdavani, A., Moreau, Y., Lewis, S., Haendel, M., Smedley, D., Horn, D., Mundlos, S., & Robinson, P. (2014). Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome Science Translational Medicine, 6 (252), 252-252 DOI: 10.1126/scitranslmed.3009262

Girdea, M., Dumitriu, S., Fiume, M., Bowdin, S., Boycott, K., Chénier, S., Chitayat, D., Faghfoury, H., Meyn, M., Ray, P., So, J., Stavropoulos, D., & Brudno, M. (2013). PhenoTips: Patient Phenotyping Software for Clinical and Research Use Human Mutation, 34 (8), 1057-1065 DOI: 10.1002/humu.22347

Friday SNPpets

Welcome to our Friday feature link collection: SNPpets. During the week we come across a lot of links and reads that we think are interesting, but don’t make it to a blog post. Here they are for your enjoyment…

What’s The Answer? Open Thread (Genotype/Penetrance Function)

BioStar is a site for asking, answering and discussing bioinformatics questions. We are members of the community and find it very useful. Often questions and answers arise at BioStar that are germane to our readers (end users of genomics resources). Every Thursday we will be highlighting one of those questions and answers here in this thread. You can ask questions in this thread, or you can always join in at BioStar.

Question of the Week:

How do I compute the proportion of cases/controls for each genotype from the penetrance function?

The question isn’t actually about a specific resource, but since the answer is clear and we do deal with a lot of genotype resources, I thought this was applicable to this thread.

Phenotype resources and databases

For another project I’m on, I had to research some of the sources of information around phenotyping experimental animal models.  And just as I needed it, the RGD team produced a very nice screencast of access to the phenotyping data and resources that they offer about rat phenotyping.  If you are interested in that type of data, go have a look at their video and explore the resources that they introduce:  RGD Phenotyping Portal screencast.

If that is data you are interested in, you might also explore some of the other things I’ve been looking at.  The MGI team Jackson Laboratory has a division that focuses on mouse phenotype data as well.  Called Mouse Phenome Database (MPD), you can access quite a range of data that already exists. They also have protocols for phenotyping that may be useful to folks who are characterizing animal models.

I also came across a project based in the EU that offers data and standardized protocols for phenotyping.  EUMORPHIA offers the Empress SOPs that they are developing, as well as access to the Europhenome database that contains the results.

As much as I still love to look at genomes, I’m ready to move down the path and look at the phenomes too :)

Tip of the Week: SwissVar, a New Genotype-phenotype Resource from SIB

SwissVar_tip_movieToday’s tip is on a new genotype/phenotype resource from the Swiss Institute of Bioinformatics, or SIB. I was already a fan of many SIB tools and resources, and was using one (ENZYME) when I found a notice about SwissVar. SwissVar is described as ‘a portal to Swiss-Prot diseases and variants.’ It includes information about genotype-phenotype relationships for each specific variant, manually annotated from literature. Manual annotation adds a level of quality and believability to this data. The SwissVar portal also contains various pre-computed information that may aid in determining the effect of the variant. Genotype-phenotype searches can begin with either Medical Subject Headings, or MeSH terms (Disease), gene or protein names (General characteristics) or variants (Functional/structural features). There are multiple ways to modify your searches, and results are clean tables of data including gene/protein accessions, names, links to MeSH definitions and links to variation reports.

If your research could benefit from high quality, manually curated genotype/phenotype information, I suggest you watch this tip, and then explore SwissVar according to your own interests.

SwissVar – a Portal to Swiss-Prot Diseases and Variants: http://www.expasy.ch/swissvar/

New SNPs in the Mouse Phenome Database

From the MGI mailing list the other day came notice of 2 new SNP sets that have been added to the Mouse Phenome Database SNP collection (MPD).

From their note:

- Center for Genome Dynamics (CGD) – SNP data from Mouse Diversity Genotyping Array (CGD2). 582,000+ locations and 72 strains.

- Palmer A – SNP data, 8200+ locations, 58 strains (Chicago1)

I like the mouse SNP tools at MGI.  I covered them in my full tutorial that you can watch for free here.  But there’s a separate access point for mouse SNPs from the MPD interface as well.  Phenotype might be an interesting way to be thinking about your genes and topics of interest if you haven’t considered that before.  A lot of people start with their genes of interest and look under the flashlight, but maybe look around at phenotypes as a starting point for some new ideas and directions.

Tip of the Week: PhenX Toolkit for GWAS Phenotype and Exposure Studies


Today’s tip is on a new resource brought to you by the National Human Genome Research Institute, or NHGRI. The resource is PhenX Toolkit version 2.1, which was released on May 22 2009. The PhenX Toolkit provides protocols for taking standardized measurements of research subjects’ physical characteristics and their environmental exposures. You can browse for protocols by domain or measurement type, or search for protocols. If you register, you are also able to collect sets of reports. These can be save for each of your projects, or for later modification. I’ll introduce you (briefly) to all of this and more in this tip.

I learned about this new resource from a GenomeWeb Daily News article in which they published NHGRI’s press release.

Tip of the Week: Phenotypic Data from the PhysioNet

PhysioNet TipOne of the things I’ve been thinking about lately are connections between genotype and phenotype – it is a topic in the news & I have been working on tutorials for the genotype-to-phenotype resources PhenomicDB & NCI’s dbGaP. Recently a friend notified of an article in Science featuring the PhysioNet – a resource intended to stimulate current research and new investigations in the study of complex biomedical and physiologic signals. The article was interesting & so I checked out this nice resource. In this short video I introduce you to a few of the features and data types available from the PhysioNet. You can read more about the PhysioNet, or see their mission statment by following the ‘continue reading’ link.

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A HuGE database

ResearchBlogging.org :) that was fun writing that title. A recent correspondence in Nature Genetics outlined some changes in the HuGE Navigator. This database has been available in some form since 2001. The basic purpose of the database is to…

navigate and mine the growing scientific literature on human gene-disease associations and related data in human genome epidemiology. As an interconnected system of applications that users can enter by using genes, diseases, or risk factors as the starting point, HuGE Navigator provides a potential bridge between epidemiologic and genetic research domains.

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