As you may know, we’ve been doing these video tips-of-the-week for eight years now. We have completed or collected around 400 little tidbit introductions to various resources through this past year, 2015. At first we had to do all of our own video intros, but as the movie technology became more accessible and more teams made their own, we were able to find a lot more that were done by the resource providers themselves. So we began to collect those as well. At the end of the year we’ve established a sort of holiday tradition: we are doing a summary post to collect them all. If you have missed any of them it’s a great way to have a quick look at what might be useful to your work.
Silos. This is a big problem for us with human genome data from individuals. We’re getting sequences, but they are locked up in various ways. David Haussler’s talk at the recent Global Alliance for Genomics and Health meeting (GA4GH) emphasized this barrier, and also talked about ways they are looking to work around the legal, social, and institutional barriers that we’ve created. He talked about Beacon, which I highlighted recently as a Tip of the Week. But there are other strategies needed to connect physicians and patients with other folks who might help them get to answers. Heidi Rehm’s talk provided information about a possible tool for this: PhenomeCentral.
Unfortunately, the videos aren’t uploaded to YouTube, you have to go to the June 10 Meeting page and obtain them from there. The one that contained the information on PhenomeCentral is the one called “Matchmaker Exchange”.
PhenomeCentral is a repository for secure data sharing targeted to clinicians and scientists working in the rare disorder community. PhenomeCentral encourages global scientific collaboration while respecting the privacy of patients profiled in this centralized database.
Certainly people in bioinformatics are familiar with the really crucial information from OMIM and Orphanet. But these are aggregators of information, not patient-specific. There may be lists of features of a condition, but how they appear in a given patient’s situation might vary.
What this new strategy will do is let doctors and researchers take the phenotype and genotype data (you can upload VCF files), and make predictions about the genes involved. They also have ways to “matchmake” possibly similar disease manifestations. This project is part of the larger “MatchMaker Exchange” collection (Note: MME is not a dating site…it’s also still under development). But the idea is that with patient details one could search for matches with other similar patients (depending on the privacy level of the records, of course). It sounded to me like a kind of BLAST for medical conditions (they didn’t call it that). But it also has ways to semantically link phenotype concepts, because they might be entered differently by different evaluating physicians, yet be the same type of issue underneath. That Human Phenotype Ontology (HPO) that I’ve covered a couple of times lately enables this.
They have 3 levels of privacy settings included: private, matchable (where you can find it in a search, but it’s not wide open to everyone), and public.
So although I used the GA4GH talk as a launching point to learn more about the features and conceptual parts of the PhenomeCentral software, I also came across this other webinar that was more specific about the software features (which is what I typically prefer for our tips, the specific software tools). The Genetic Alliance is a patient-centric group interested in answers for genetic and genome-variant medical situations, actively working with advocacy groups and researchers to bridge the needs of both. In their webinar series last year they included PhenomeCentral.
What I didn’t realize from the GA4GH overview was that there are additional tools, including a pedigree tool in the PhenoTips part. We find a lot of people find our blog searching for pedigree tools, so I wanted to be sure to mention that specifically. You can try it out by entering fake data in the playground over there, and accessing the Pedigree Tool from that record. This was also handy for me because I didn’t create a login for the main PhenomeCentral site due to the privacy issues.
So have a look at PhenomeCentral. And from the GA4GH video I learned that there is a special journal issue coming up in the fall that will have papers related to these projects. So I’ll link to the PhenoTips publication below now, but when more references become available for this tool or project I’ll add them in. I expect there will be metrics about algorithms in use and other technical details that are important for fully evaluating the tool.
References: 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
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.
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.
References: 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
But I can also see the need to collect some of this information on mobile devices, during conversations with patients and families. Or even at the next family holiday gathering. And perhaps an iPad based tool might be handy for those sorts of things. I found out about one of them, Proband, via twitter:
Since I don’t have an iPad, I can’t evaluate it myself. But you may be interested in the review that was done of it a while back. Proband App lets anyone be a genetic counselor…or at least draw like one. The team is actively seeking out feedback, though, and some of these things may have changed. They have been presenting posters at conferences like ACMG and ASHG, and also reaching out in other ways too. When I emailed them with a question, they were very responsive. They also provided a data sheet with updates listed from March, so I’m certain they are continuing to actively develop this tool.
Be sure to pick the right one on the iTunes store.
Typically we like to highlight open access tools, but seemed to me the $4.99 app price isn’t exactly prohibitive if you already own an iPad. Just be sure to find the right one in the Apple store–it’s not the music one. Oh–related to this though–they are also considering other platforms. And they are piloting a server piece that will integrate the pedigree data with other parts of electronic health records systems. In another article about the team’s work (Genomic Singularity Is Near), they add more details on their larger goals:
“Miller asserts that in the future, Proband will be able to incorporate test results and other personal health information stored in electronic health records. “Querying pedigrees based on scientific and medical questions is another near-term goal,” he adds.”
Another point I’ll just quickly make about Proband: they noted in that Singularity article, and in one of their meeting abstracts that they are conforming to the standards established in the field:
The app enables the user to create complex family pedigrees by fully implementing, with minor exceptions, the nomenclature outlined by the Pedigree Standardization Work Group (PSWG) in Bennett et al. 2008.
This is crucial, of course, and I’m glad to see this. I’ve attached the reference for that Bennett paper below, and it has really helpful guidance on the symbols and meanings, and even astonishingly complex assisted reproduction relationships like this planned adoption: “Couple contracts with a woman to carry a pregnancy using ovum of the woman carrying the pregnancy and donor sperm.” (Fig 3. Wow, that’s some diagram. PS: *cough* googlescholar for pdf). I also saw that Proband are using the Human Phenotype Ontology (HPO). I expect to be exploring HPO in some other upcoming tips as well–this is going to be increasing important as we collect more sequencing data from individuals and try to figure out what it all means.
So if you need to draw pedigrees for clinical or research situations, or maybe for genealogies, you might want to have a look at this app. It might be an engaging teaching tool as well.
Reference: Bennett R.L., Kathryn Steinhaus French, Robert G. Resta & Debra Lochner Doyle (2008). Standardized Human Pedigree Nomenclature: Update and Assessment of the Recommendations of the National Society of Genetic Counselors, Journal of Genetic Counseling, 17 (5) 424-433. DOI: http://dx.doi.org/10.1007/s10897-008-9169-9
Edited to note that the app is now freely available, and changed the screen shot accordingly.
So, 23andMe has received our spit. The machines are churning away as we speak. I expect that sometime over the next few weeks to get some results for myself, my husband and our two daughters. What do I expect to find? Well, let’s look at two trees representing my history. The first is a pedigree following heart disease on my paternal side (there has not been any reported on my maternal side). Here is a pedigree I whipped up using Madeline 2.0′s web service (I say whipped up, because I didn’t use all the features, just for illustration purposes, a tutorial here :). Of course this will be nothing like that done in the research I posted about a while back. I don’t have a team of doctors, nor a lot of time:
I’m the red square, 109. The black squares are those that have been diagnosed with heart disease. All also were diagnosed with hypertension before that. Patient 101 died of cancer… after having four heart attacks from her mid 40′s on. Patient 106 died of a heart attack at age 55. Patient 102 has had a couple heart attacks as has patient 104. I was diagnosed with hypertension at the age of 18 (at which time I was 140lbs, 6′ tall, non-drinker, non-smoker, physically active). In this pedigree, none are obese. Though my paternal side can tend to burly, they are for the most part within healthy ranges. Patient 103 and 101 especially have been lifelong healthy weights. I myself have been nearly technically obese, but lost the weight.
I think from this I’ll be able to tell, quite clearly, that I will have a high propensity towards heart disease and heart attack. What do I need to do to ward that off? Eat less food, mostly plants, exercise, don’t smoke. Pretty much the advice everyone should take I assume. That I have had hypertension since 18 doesn’t bode well for good news from my maternal side (where heart disease and heart attacks are unknown).
I looked at the list of disease risks, and from what I know of my family health history, I don’t expect many surprises.
Daughter 1′s Pedigree? Here it is:
Her biological grandfather might have had a heart attack. Nothing else known.
Daughter 2′s Pedigree? Her maternal side has obesity. Nothing else known.
There I expect to find something useful!
Now, let’s look at my ethnic background. I come from, on my maternal side, a long line of very proud Virginians, FFV in fact (with the expected boasts of 2 presidents, 2 signers, and several governors). As such, my genealogy is documented on my maternal side back over 500 years in many cases. My paternal side? Anglo-German-Native. It was not well documented, but after I became a Mormon* at the age of 18, I documented a lot of it, some lineages back 200-300 years. Here is an Ancestry.com view (name redacted and just known-ancestry listed):
My paternal grandfather? He had two grandparents born in Germany with German surnames, German ancestors, two grandparents of English ancestry, surnames and ancestors. My paternal grandmother? Three of her grandparents were of Native American ancestry (Mattaponi to be exact). I’ll put a caveat there. Though her maternal side is well-documented Mattaponi, there are questions about further back (her grandfather was said to be of African descent, and it appears to be some early Anglo-Scottish mixing). These caveats are not without basis. The native American tribes of Virginia were well-known to have inter-married and mixed with both the African-American and Anglo-American populations. Nonetheless, you just have to look at photos (and birth certificates of my great grandmother to know she was a Mattaponi.
Maternal side? Well, Anglo-Scottish back hundreds of years.
What do I expect to find with my 23andMe data? Perhaps some questions answered (is the Lathe surname and ancestry from the Danelaw and Viking settlements of old as stories would have us believe), but for the most part I don’t expect anything new or surprising.
Daughter 1′s biological genealogy (her cultural genealogy is a mix of mine, my husbands and her biological):
African, possibly from the regions of what is now Nigeria and Angola (from some research I did a while back). Her biological grandmother was reported to be “Creole”.
As I and my family await our 23andme kit to scan our genomes, family history has come back to the forefront of my thoughts. I used to be very fascinated by my own genealogy, and with adopted children, the concepts of descent, biology and culture have taken adjusted meanings for me. It’s why we have a ‘family map’ instead of a ‘family tree’. The difference between our cultural genealogy and our genetic genealogy has been become quite clear to me. Obtaining our family ancestry through these tests will bring a lot of these issues back to focus.
But there is a specific issue that is directly related to genomics, genomics tools and my family: same-gender headed household representation in pedigree and genealogy software. It’s non-existent or takes a difficult workaround to make it happen.
With the rising use of personal genomics data, there is a corresponding rise in the use of pedigree software for medical purposes and genealogy software for family history purposes. Neither of these handle non-traditional family structures well. I use ‘non-traditional’ lightly here though because even though same-gender headed households might be relatively new as a recognized family structure, the concept of family can be quite fluid across time and cultures. What is traditional and considered the ‘norm’ today in US culture (nuclear families of two genders with children born to them) for ‘family’, is obviously not the case in the past, nor in contemporary cultures in other parts of the world.
One challenge in using family history as a health technology is that the geneticist or clinician defines family based on biology, whereas individuals often include those linked socially.
Genetic heritage and history is indeed important in determining disease susceptibilities, but ignoring or misunderstanding socially-defined kinship can lead to misdiagnosis, the lack of understanding of environmental influences and worse. Tools for modeling pedigrees must be able to flexibly model these family structures in order to be useful.
The researchers look at two groups and conclude that current tools are inadequate to model their family structures. Samoans were one group (Japanese-Americans the other):
When Samoan American participants were asked, “tell me about your family,” persons fulfilling social roles were described by that relationship. For example, an individual raised as a brother was identified as a brother whether or not there was a biological basis to the relationship. Similarly, individuals adopted in to or out of a family were described as the children of the family in which they were raised, not as offspring of the biological family. When further questioned, the participants could identify the biological link. But even when the biological relationship was known, the Samoan Americans reported family relationships based on social rather than biological ties.
They go in to good detail into why this is a problem. They also, early in the paper, suggest modern American society is changing. Americans already are one of the most ‘adopting’ nations in the world. And, as the authors note, our family structures are becoming more fluid (perhaps converging with Samoan concepts in some ways?):
For example, the Western postmodern family has looser kinship ties than in the past, with relationships that are diverse and fluid (Stacey, 1998). Blended, adoptive, and gay families, as well as those resulting from a variety of assisted reproductive technologies, place an emphasis on choice rather than genetics. For many, family is about social relationships and not solely concerned with the transfer of genes from one generation to the next (Finkler, 2001;Lévi-Strauss, 1969; Peletz, 1995). Nonbiological social factors, such as role behavior, determine family membership, so that a mother’s sister’s son who has been raised with you is your brother (Finkler, 2001). Both formal and informal adoptions are traditional practices and very common in certain societies: Polynesia often being presented as the exemplar (Brady, 1976; Carroll, 1970; Levy, 1973).
So, let me side step adoption or other non-genetic descent issues for a moment, and hone in on gay families and representation in current pedigree tools available. Though the Recommendations for Standardized Human Pedigree Nomenclature (pdf) mentions it in passing (“For example, information that is commonly recorded on a pedigree (e.g., same-sex relationships…)”) there is no standard suggested. In my and my colleague’s research so far we have yet to find a software or online medical pedigree tool that easily accepts same-gender parental groups, or represents them well.
I took at one excellent online tool, Madeline 2.0. If one enters a parent, entering a second parent automatically forces an opposite gender. Though there is the ability to model adoptive relationships, there is yet no way to model same-gender couples. I wrote the developers of the tool and received a thoughtful reply. No, there was ability to do this, but considering adopt-in and adopt-out relationships are model, it would make sense to include same-gender couples. They suggested they indeed will consider implementing this. Of course, as with all software and online tools, funding, timing and priorities I know will be an issue. I’ll definitely will keep an eye on developments. So as to not single Madeline out, no other tools that we know of (see here, here and here) allow for same-gender couples or headed families.
When going to family history modeling software for genealogy, the omission is as stark. Every individual has two family trees: a cultural/historical one and a genetic one. For most individuals, those histories overlap. The culture you received from your parents and they from theirs is pretty close to the genetic descent. Even then, its not a perfect overlap. What is important to who you are from a cultural or historical perspective might not at all be related to who are you from a genetic one, and who you are is as much cultural as it is genetic. I am as interested in where I got my cultural ancestry as where I got my genetic one, this has become quite clear to me as we’ve adopted children.
And in the future, descendants will look at their family genealogies and it will be very important to them that one of their ancestors was raised by two men, or two women whether adopted or biological from one parent. As these genealogies are built, those relationships which are very important to their family culture and histories should be represented. I know I personally will hope that this will be the case for our family history in the years to follow.
Yet, for software available it is impossible, a complicated workaround or awkward to allow for same-gender parents in the representation (not to mention paper family trees!). GEDCOM is the defacto standard for exchanging genealogical information. There is no simple standard in GEDCOM for including same-sex parents. That it was developed by the Mormon Church probably has something to do with that ‘oversight’, but frankly given the oversight across the board in pedigree and genealogy standards and software, I doubt that was a deliberate one.
So far I have found software that requires complicated workarounds, like Legacy, or it’s not easy to figure out (though once you do, it’s simple :). Of the many I’ve tried, none even allow it.
In a world where the number of same-sex couples is increasing annually (not to mention adoption, blended families and many other types of structures) and increased interest in family history through both genomics and culture and history, I look forward to seeing the software catch up to the ability to model my family for future researchers and historians.
Burns McGrath, B., & Edwards, K. (2009). When Family Means More (or Less) Than Genetics: The Intersection of Culture, Family, and Genomics Journal of Transcultural Nursing, 20 (3), 270-277 DOI: 10.1177/1043659609334931
I’m always interested in the range of tools available in bioinformatics. I mean, I know why we have so many built around human and other model organisms. But I love to hear about other types of projects around biology that need and use computational tools. I’m kind of a fan of the underserved species. In fact, I think there is so much room there for exciting applications and discoveries that it may actually be more interesting than some of the human navel-gazing stuff
So when I was looking around at the Agricultural Biodiversity Blog I came across the conference announcement for the International Conference on Biodiversity Informatics. I’m intrigued.
Another thing I had come across on the Agro Biodiversity site was a plant pedigree. I’ve recently become interested in that flood-tolerant rice project, and they were discussing the pedigree of that rice. Plant pedigrees…cool. We are just about to release a training on a pedigree tool and I have been thinking about the strengths and limitations of various tools (because that’s what we do, as Jennifer illustrates here) and I realized that plant pedigrees are a new wrinkle entirely. The temporal difference in the parents–and even the possible species range of differences–really got me thinking. But check out their pedigree for that rice (large image, reminds me of a Gene Ontology diagram). Wicked neat. Reminded me of my favorite diagram on mouse pedigrees. The software for this comes from this project that I had stumbled upon separately: Generation Challenge Program.
So much to learn.
EDIT: as I was still percolating on this I remembered my dismay about the representations of synthetic organisms in phylogenies and databases. I wonder what their pedigrees will look like….
Long ago, when our blog was young (less than 2 months old – where does the time go?), Mary wrote a post about the pedigree drawing programs that she knew of, or that were mentioned on the Mouse Genome Informatics (MGI) mailing list. There has been so much interest in that post, as judged by clicks, that we began looking into pedigree analysis tools with the idea of creating one of our trainings on the ‘best’ tool we found. I have been working on finding a great tool to train on – public (free), broad applicability and web-based. I did find a nice little tool named PediDraw, and did a tip of the week on that, but it is so easy to use it doesn’t really warrant a full tutorial.
But all in all, I’m finding the search to be a somewhat difficult slog. So much of the software I have found is fairly old, many of which are no longer supported by their creators. Others are only available commercially and/or have a very focused functionality, are only available on one system or the other, or are in various languages such as Fortran 77 or R. Last week I noticed that Mary’s blog was linked to in a blog post by Gregor Gorjanc, and I must confess that it felt great to know that he was having a similar slog for the ‘right’ pedigree program. Gregor’s post has some nice background information and information on for plotting large, complex animal breeding animal pedigrees. I won’t repeat his information here but his post, as well as others he links to, convinced me I should share some of the gems of knowledge that I have acquired.
The first thing I learned is how easy it was to find useless information (at least to me) by googling for ‘pedigree’ – as in almost 23 million hits with the top I-don’t-know-how-many linking to information or coupons for Pedigree dog food. As I searched, I also learned how many different things people mean by pedigrees – there are pedigrees for keeping track of livestock breeding programs, laboratory mouse strains, dog breeds, and fancy bird crosses. thoroughbred, others are for historians or hobbyists tracing their roots. The term pedigree is also used for business tracking and management software systems. The area that is closest to my personal interests are those that are medically relevant, but even those are amazingly diverse – pedigree can mean everything from a family history given by a patient (riskApps) to e-pedigrees soon to be required by some states for pharmaceutical manufacturers to reduce the chances of dangerous counterfeit chemicals.
Once I got a few promising hits, found some promising sites I tried to extend my searches using the words that were on the sites that I had found. Using search terms such as ‘kinfolk’ and ‘ancestry’ lead me to Anabaptist family databases and presidential genealogies, but not so many drawing programs. The most fruitful/directed search phrase was of course ‘pedigree drawing software’ which retrieved many articles and individual software pages. However, I think THE BEST hit (by far) that I found was the linkage software list at Rockefeller University, and I found it with the search phrase ‘linkage analysis software’. Why do I consider this THE best hit, you ask? Though my searches I have come to believe that pedigree drawing software is somewhat like religion – it is a very personalized thing & only you can know which is best for you. The Rockefeller list is the largest and most comprehensive list that I have anywhere. It is up-to-date and publicly available. It lists over 450 programs in an alphabetized list and provides information such as system availability, recent publications, brief description for each. There is also a searchable version of the list. If I were hunting for the perfect pedigree drawing program for my research, I would search here rather than Google! My hat is off to those who maintain this wonderful list at the Laboratory of Statistical Genetics at Rockefeller University!!
I’ll keep you posted as to my finds as I cull their list. And if you are ‘in the know’, or have found the ‘perfect’ pedigree software PLEASE do comment and add your knowledge here.
I’ve been collecting a list of pedigree analysis tools & have decided to share one of my finds with you for today’s tip. The resource is PediDraw. It was created as a web-based tool that makes it easy for patients to draw their family histories before going to a genetic counselor, and allows the data to be output in a standard format table or pedigree drawing. It allows you to add several branches to the family history & is VERY easy to use. I think with some awareness of its assumptions, and with some creativity, you could use the software for applications other than just patient self-histories. You can read more about the project in the citation below, and see a quick intro to the tool in my tip.
He, M., Li, W. (2007). PediDraw: A web-based tool for drawing a pedigree in genetic counseling. BMC Medical Genetics, 8(1), 31. DOI: 10.1186/1471-2350-8-31
Well, not all mice–not like the project that studied the history of cats (I can haz domesticashun?). This project examined the ancestry of the laboratory inbred mouse. This poster (small section on the left) is one of those cool nearly-secret things you come across once in a while that just make you go: whew–I’m glad somebody knows this… This work was underway when I was at the Jackson Lab and I often think back to it when I read mouse papers, and you can print up the whole document as a poster (it’s a big PDF). I’m not going to link to the PDF itself, please go to this page at Jax: Genealogy Chart of Inbred Strains and click the downloadable Portable Document Format (PDF) file link for to examine this whole mouse pedigree chart.
We describe the origins and relationships of inbred mouse strains, 90 years after the generation of the first inbred strain.
The paper is actually quite a nice description of the how we got to the mice you probably know and love if you have ever worked with them in the lab. It describes important phenotypic considerations around aging and breeding that could impact your work–even if those topics are not the focus of your work.