A genetic cartography of humans

The Phase I paper of the 1000 genomes project has been published in Nature.  Similarly to the completion of the first draft of the human genome sequence, this work constitutes a milestone in the path to understand the complex relationships between genotype and phenotype in our species. When we had the first human sequence we had, for the first time, a broad view of what were the genetic constituents of our species, no doubt that this has served to advance our understanding in many fields related to human biology and disease. What is then the significance of having 999 genomes more? I have been asked this question by some journalists in the last days. 

If one would like to describe our species purely in genetic terms, a single genome could be a good approximation, but only that, an approximation. We know that we all differ from each other genetically, and that some of these differences explain part of the observable differences (the phenotype). What is the extent and nature of the genetic differences that exists currently?, or that even existed before in the human population?, which of these differences are important in terms of phenotypic variability, including the propensity to suffer from certain diseases?, what fraction of these differences have no important effect and can vary freely?. All these questions cannot get an answer from the analyses of a single genome, and only the comparison of a large set of genomes would serve to have a better idea of what is the genome of our species.

The analogy of a map has been used several times to illustrate how the genome sequence has helped us navigate it and has enabled dramatic improvements in how we address questions related to human biology. I think the analogy is very good, since a map in itself has only a limited scientific value, since it is, basically, a description. However, similarly to how ancient maps dramatically affected the course of history, having this maps enable unanticipated scientific discoveries. This first 1000 (1092 to be extact) genomes constitutes a first cartography of human genetic variability. Providing detailed information of what mutations occur in different populations. This map is not complete, of course, but enables a good level of resolution. The authors estimate that we now have a catalogue of more than 98% of the mutations that occur at a frequency of at least 1%. Continuing with the analogy we still miss is the specific details of how the coastal areas are: like if we would see them from very far away. This missing variability may be important, since variants involved in deleterious phenotypes (disease) are expected to be at very low frequencies. Thus the effort of improving this cartography will continue and 1500 additional genomes are planned within the consortium. In parallel, many other projects and even some from particular private persons are producing more individual genome sequences. It will be important to ensure that all these information ends up in public repository, so that this information is efficiently exploited by the scientific community.  

The 1000 paper is very descriptive but already shows some important results that have an impact on how we think about the relationships of genotypes and phenotypes. They report that an individual would carry on average 200-300 variants that affect conserved residues in non-coding sequences, and even 2-4 that have been associated to disease in other studies. All individuals sequenced are healthy and thus this result tells us about the plasticity of the genome to tolerate mutations that may be deleterious in other genetic backgrounds. There is much to learn from this and the 1000 genomes will be a useful resource for studies trying to associate genetic backgrounds with disease propensity. In addition the genome sequences carry the footprints of the recent evolution of human populations, and the level of observable variability of a site can be informative of the potential functionality. Thus the possible applications of this data are many, and as I posed to a journalist. The main scientific discovery enable by this articles yet to come.

Finally, there is one important aspect that journalists do not pay much attention. Putting together this project has been a gigantic effort and has required the development of new tools and algorithms to work with this massive amount of data. Only the coordinated efforts of many groups has made this possible.This comes at a time in which such tools are desperately needed, given the growing impact of idividual genome sequencing in medicine and other fields. Similar to how an ambitious mission to bring a rover to Mars impacts scientific development beyond the particular purpose of this mission, the tools developed by the 1000 genomes project are already playing a role in hundreds other genomics project. Thus the merit of this big consortium project is not entirely the immediate scientific discoveries- at times deceiving because they are inevitably only descriptive- but their catalytic effect on a scientific field. 

 

Challenges in phylogenetic tree visualization

I recently read an excellent review by Roderic Page, on the challenges in phylogenetic tree representation and visualization. It provides an overview  on existing software and tools (although he missed our ETE package, see image below for an example of ETE's visualization features). The number and diversity of existing tools is overwhelming, but probably matches the diversity of different interests and possible applications of phylogenetic trees. One may be interested in  overlaying sequence information (see below), while other would be interested in displaying information on the geographical distribution of the species. Some may need to represent uncertainty and overly different topologies, or networks to represent transfers of genetic material, the possibilities are unlimited.

 Most importantly he mentions some of the challenges of tree visualization software such as the ability to represent huge trees and to allow interactive behavior with the user. In our group we have encountered such needs and this is the reason behind implementing more visualization features in ETE. Fortunately new technologies are offering new opportunities as well, and I enjoyed imagining the possibilities that 3D visualization and touchscreen technologies will provide to researchers. Definitely is a field to follow.

 If you are interested in the topic. I recommend this video.

Phylogenetic Tree Challenge in Encyclopedia Of Life

 The Encyclopedia of Life initiative aims at providing an open, digital resource providing comprehensive information about the diversity of life. It has recently opened a call for teams that can provide a phylogeny-aware organization of as many scientific names as possible. This text is from the call:

A prize is offered to the individual or team that can provide a very large, phylogenetically-organized set(s) of scientific names suitable for ingestion into the Encyclopedia of Life as an alternate browsing hierarchy.  

[...]

Among other factors, the total number of uniquely named nodes, node/leaf ratios and tree height may be used to compare entries so contestants should consider how they wish to trade off strict consensus versus other methods of reflecting the state of phylogenetic knowledge.

Problems to solve include 1) how to assign labels to unnamed nodes, 2) how to fill in gaps so that the set of taxa included is as comprehensive as possible, even if trees are not fully resolved or all taxa have not been analyzed, 3) how to handle competing hypotheses, 4) how to update the hierarchy at least annually.  

The winning submission must be available to EOL and others under an acceptable CC license if it is under copyright.  The tree need not be previously published in peer-reviewed form.
 
 and more information is available here.

  

RECOMB 2012 (Barcelona): one week left for early registration

 As I reported in an earlier post, RECOMB 2012 will be held in Barcelona and CRG's Bioinformatics and Genomics program is part of the local organizing committee.
 This post is a reminder that the deadline for early registration with a reduced rate is approaching and will expire 31st of January. More information here.

 See you there!

Sequencing species.... by the thousands

 When I was giving my first steps in the field of comparative genomics, there was not much to think about when deciding which genomic datasets to use: one would just take them all. With only a few dozens of genomes, mostly of bacteria, one could have everything at hand, in the local disk, just need to update every couple of months by adding one or two more...

 These times have definitely passed, and now the flow of newly sequenced genomes is... well, overwhelming (see figure below, taken from Genomes Online). This is both a blessing and a curse for us doing comparative genomics, since we have an unprecedented amount of data which enables more resolution, but we are increasingly facing novel technical and analyitical challenges.

 Just to give a taste of this avalanche of genomes from different species (projects for sequencing genomes for a given species, such as the 1000 genomes is another story) that is coming, I here list some of the projects I am aware of that aim at sequencing thousands of genomes from a given taxonomic group.

• i5K: 5000 arthropod genomes
• 1000 fungal genomes
• genome 10K: 10000 vertebrate genomes  
• 10000 microbial genome project

As expected, in this kind of projects it is way more easy to come up with a bold number, than to actually define the list of species that are actually going to be sequenced. At least this is what I can tell from my involvement in the i5K initiative, in which prioritisation of species to be sequenced is not simple, since usually one wants to weigh in different criteria (phylogenetic relevance, biological, economical, and clinical importance, etc).   

 I'm sure I missed some, and, in addition, there is a growing flow of genomes that are sequenced by independent groups, including my modest own group. One common weakness of this large, and small-scale initiatives is that they sometimes come with the cost for covering the genome sequencing but do not account for the necessary bioinformatics analyses to actually make sense of the data. With the sequencing costs dropping and the potential analyses becoming more complex, the actual costs of sequencing projects will more and more be on the side of the analysis beyond the assembly and annotation phases. As a result, many bioinformatics groups are streching their resources to contribute to genomics projects without getting any specific funding.

In my opinion the planning of a sequencing project should account for all the downstream phases with their associated costs. With such an approach we may end up having a handful of genomes less, but we will definitely learn more from them. 

Watch the talks from the CRG Symposium: Computational Biology of Molecular Sequences.

 If you missed the opportunity to attend physically our past symposium on "Computational Biology of molecules" (see this past post), you can now watch the videos of the talks (read message below).

*****************

Dear all,

All contents of the 10^th CRG Annual Symposium on Computational Biology of Molecular Sequences, celebrated last 10^th and 11^th of November, are now available online.

Leading scientists in computational biology came together in Barcelona on the occasion of the tenth edition of the CRG Annual Symposium, which focused on computational biology of molecular sequences, organized by the Centre for Genomic Regulation (CRG). The auditorium of the Barcelona Biomedical Research Park (PRBB) hosted the event, celebrated from Thursday 10 to Friday 11 November 2011.

In the microsite you can find the inaugural video of the Symposium, videos of the talks, interviews with some of the speakers, participants and organizers of the event and two summary videos that capture the major points of all sessions. There are also available two articles that summarize the talks and news related to the field of computational biology of sequencing.

We hope that these resources are useful for you!

Click here to visit the 10^th CRG Annual Symposium web.

XI Jornadas de Bioinformatica in Barcelona (23-25 January)

  A short note to spread the word on the joint Spanish and Portuguese Meeting on Bioinformatics.  This is a yearly meeting that is gaining momentum every year, and it is a great opportunity to meet most groups doing bioinformatics in the region. Talks are in English and everybody is welcome to attend.

 As other years, this meeting has associated a regional (Spain, Portugal and North Africa) ISCB student symposium. This year this symposium is co-organized by, Salvador Capella-Gutierrez, one of the members of my lab. 

 If you plan to submit a communication, there is time till the end of November.

 See you there.

ALPHY 2012: French-Spanish meeting on Bioinformatics and Evolutionary Genomics (March 19 -21, Banyuls-sur-Mer)

 I am glad to announce ALPHY 2012, which for the first time is jointly co-organized by French and Spanish researchers. I was very glad to be invited by my French colleagues to sit at the organizing committe. I think it is a great opportunity to join two communities with ample experience in phylogenetics-related research.

ALPHY is an annual meeting, organized in France since 1995, dedicated to the field of Bioinformatics and Comparative Genomics (ALPHY = ALignments and PHYlogeny). The main goal of this meeting is to promote informal exchanges in this highly multidisciplinary field, and to encourage young scientists to present their work. The official invitation follows, plus a very tempting picture of the location.

This year, ALPHY is co-organized by Spanish and French scientists, in the nice city of Banyuls. There will be two invited speakers (Henrik Kaessmann and Jose Castresana), and the program will be open to contributions for 20’ talks.
The registration to the meeting is free, but mandatory. Please use the link (top left of this page) to register. If you wish to present your work, submit your abstract in the registration form.
Important dates:

• Deadline for abstract submission: January 10 2012
• Deadline for registration : February 1st 2012

Hasta pronto – A bientôt – fins aviat - see you in Banyuls!

RECOMB 2012 (Barcelona)

 The next RECOMB meeting will be held at Barcelona. Our department is part of the local organizing committee and the list of confirmed speakers looks very promising.

 Submission opened in September, and you still have time to submit papers until the end of the week. Do not miss the deadline.

Special BiB issue on "Orthology and Applications"

 An special issue on "Orthology and Applications"  is out in the journal Briefings in Bioinformatics.

 This special issue has been edited by Christophe Dessimoz and comprises a number of interesting papers including several comprehensive reviews and also original research articles. Some of the papers emerge from efforts on orthology benchmarking and standardization of datasets that were initiated during the first "Quest for Orthologs meeting" in 2009. See this letter reporting from that meeting. We contributed with an article reporting on the comparison of expression patterns between across-species orthologs and paralogs of a similar evolutionary age.

On the "orthology conjecture"

 Hi,

 Jonathan Eisen has opened a thread in his blog to discuss the recent paper by Hahn and colleagues on the "ortholog conjecture"  You can read more about the discussions raised by this paper here.

This is what I wrote, a text which I had to split in three pieces in Eisen's blog given the word limit for comments!!

Hi

I appreciate the effort by Matthew Hahnn on explaining the story behind his paper on the so-called "Ortholog conjecture" and on facing some of the criticism. This paper attracted my interest as that of many others that work on or just use orthology. For instance it was chosen by one of my postdocs for our "Journal Club" meeting. And it was discussed during our last "Quest for Orthologs" meeting in Cambridge. I think is raising a necessary discussion and therefore I think is a good paper. This does not mean that I fully agree with the interpretation and conclusions ;-). I hope to modestly contribute to this debate with the following post.

I think one of the causes that this paper has caused so much debate is that the conclusions seem to challenge common practice (inferring function from orthologs), and could be interpreted as the need of changing the strategies of genome annotation. I think, however, that one should interpret carefully these results before start annotating based on paralogous proteins. As I will discuss below one of the problems is that we need to agree in what is the conjecture to then agree in how to test it. I see three main points that can be a source of confusion: i) the issue of what is actually stated by this conjecture, ii) the issue of annotation, and iii) the issue of time

1) What is the "ortholog conjecture"?
Or in other terms, when should we expect orthologs to be more likely to share function than paralogs?. Always? Of course not. All of us would agree that two recently duplicated paralogs are likely to be more similar in function than two distant orthologs, so it is obvious that the conjecture is not simply "orthologs are more similar in function than paralogs". In reality the expectation that orthologs are more likely to be similar in function than paralogs, as least this is how I interpret it, is directly related to the effect that duplication have on functional divergence. If gene duplication has some effect on functional divergence (even in not 100% of the cases), then, given all other things equal (divergence time, story of speciation/duplication events - except fpr the duplication defining the orthologs) one would expect orthologs to be more likely to conserve function.

I think this complexity is not well considered (by many authors, in general). Hahn refeers to the famous review of orthology by Koonin (2005) as the source for the term "ortholog conjecture". However, In that paper this conjecture is discussed always within the context of genes accross two particular species, whether in Hahn's paper it is taken as well to other contexts. Thus, the proper context in which to test this conjecture is only between orthologs and between-species paralogs. As we can see,  Red and purple lines in Hahn paper in figure2 do not show any clear difference.

 Secondly, Koonin was very cautions in his paper, stating that he was referring to "equivalent functions" and not exactly the same "function", correctly implying that the functional contexts would be different in the two different species. This brings me to the next point.

ii) annotation
If the expectation of functional conservation of orthologs refers to a given pair of species, then it makes no sense to test that expectation between paralogs within the same species and orthologs in different species. We were interested in this issue and it took us some effort to control for this "species" influence on the comparison, if you are interested you can read our paper on divergence of expression profiles between orthologs and paralogs (http://www.ncbi.nlm.nih.gov/pubmed/21515902)

As Hahn founds, and it was anticipated by Koonin in that review, there is a huge influence of the "species context", a big constraint of what fraction of the function is shared. Indeed I think is the dominant signal in Hahn's paper. Why is that? One possibility is that the functional context determines the function, I agree. However, we should not discard biases in how different communities working around a model species define processes and function, also the type of experiments that are usually done. For instance experimental inference from KO mutants might be common from mouse, but I guess is not the case in humans (!!). I think this may be having a big influence and might even be the dominant signal in Hahns paper.

Finally function has many levels and I expect subfunctionalization mostly affect lower levels (i.e. more specific). Biases may also
 exist in the level of annotation between species or between families of different size (contributing more or less to the orthologs/paralogs class).

Microarray data are less likely to be subject to biases (although some may exist), at least they should be expected to be free of "human interpretation biases" and so Hahn and colleaguies did well, in my opinion, of testing that dataset. It is important to note that for microarrays and for orthologs and between-species paralogs (which I think is the right frame for testing the conjecture) ortholgs are more likely to share an expression context. This is compatible to what we found in the paper mentioned above, and compatible with the orthology conjecture as stated by koonin (accross species)


iii) time
 Finally, one aspect which I think is fundamental is the notion of "divergence time". Since paralogs can emerge at different time-scales they are composed by a heterogeneous set of protein pairs. Most of comparisons of orthologs and paralogs (Hahn's as well) use sequence divergence as a proxy of time. However this is only a poor estimate, specially when duplications (as in here) are involved (we explored this issue in the past: http://www.ncbi.nlm.nih.gov/pubmed/21075746). This means that for a given divergence time paralogs may have larger sequence divergence than orthologs at the same divergence time, or otherwise (if gene conversion is playing a role). Is the conjecture based on sequence divergence or on divergence time?, I think the initial sense of using orthology to annotate accross species is based on the notion of comparing things at the same evolutionary distance. Thus basing our conclusions on divergence times might not be the proper way of doing it.

CONCLUSIONS AND PROPOSAL FOR RE-STATEMENT

To conclude, and with the intention of going beyond this particular paper,
I would finish by saying that the key to the problem lies on how we interpret the so-called "ortholog conjecture" or how are our expectations on how function evolves. What I get from re-reading Eugene Koonin's paper and how I am using that "assumption" in my day-to-day work is the following:

"Orthologs in two given species are more likely to share equivalent functions than paralogs between these two species"

Therefore the notion of "accross the same pair of species" is important and thus only part of the comparisons made by Hahn and colleagues could directly test this. Looking at the microarray and between-species comparisons data, the conjecture may even hold true!!

I, however, do think that the conjecture as stated above is limited and does not capture the complexity of orthology relationships. Indeed us, and many other researchers, are tuning the confidence of the orthology-based annotation based on whether the orthologs are one-to-one, one-to-many or many-to-many, even when orthologs are "super-orthologs" (with no duplication event in the lineages separating the two orthologs).

Since, the underlying assumption of the ortholog conjecture is that duplication may (not necessarily always) promote functional shifts, then many-to-many orthology relationships will tend to include  orthologous pairs with different functions.

 Thus I would re-state the conjecture (or expectation) as follows:

 "In the absence of additional duplication events in the lineages separating them, two orthologous genes from two given species are more likely to share equivalent functions than two paralogs between these two species"

 This would be a more conservative expectation, which is closer to the current use of orthology-based annotation that tends to identify one-to-one orthologs, rather than any type.

 When duplications start appearing in subsequent lineages thus creating one- or many-to-many orthology relationships, the situation is less clear. Following the assumption that duplications may promote functional divergence. Then one could expand the conjecture by "the more duplications in the evolutionary history separating two genes, the lower the expectation that these two genes would share equivalent functions".

 I wrote this contribution on the fly, and surely there are ways of expressing this in more appropriate terms. In any case I hope I made clear the idea that the conjecture emerges from the notion of duplications causing functional shifts and that our expectations will be clearer if expressed on those terms. This goes on the lines of what Jonathan Eisen mentioned on considering the whole phylogenetic story to annotate genes.

 Under this perspective, the real important hypothesis is that "duplications tend promote functional shifts", I think this is based on solid grounds and has been tested intensively in the past.  

 Cheers,

Toni Gabaldón

http://treevolution.blogspot.com

CRG Symposium: Computational Biology of Molecular Sequences. 10-11 November

Registration is open for the CRG symposium organized by our Bioinformatics and Genomics programme. This meeting will host internationally reknown scientists in the Bioinformatics field. Just to cite some: Smith, Tramontano, Ponting, Sankoff, Koonin, Bairoch, Brunak... Below you'll find the symposium overview and the complete list of speakers. 

 

Advances in methods to sequence nucleic acids, coupled with more general advances in automation, robotization, and multiplexing, have resulted in the capacity to survey the phenomena of life in a global manner and with unprecedented resolution. As a result, Biology, traditionally an analytic science in which the natural world is dissected in its elemental components in order to be comprehended, is becoming a synthetic science, in which the phenomena of life is approached in more systemic way. In parallel, Biology, a science in which human effort  been directed until very recently towards data acquisition, is increasingly becoming a discipline in which data is obtained with almost no human intervention, and the effort is being directed towards data analysis. Computational systems to store, analyze and model biological data have thus become an essential part of research in Biology. The connection between Biology and Computation, however, runs much deeper as we are coming to realize that the unfolding of the instructions in the genome is, stricto senso, a computation on the DNA sequence.  Biology, thus, cannot be understood without Computation. The two-day CRG symposium on “Computational Biology of Molecular Sequences” will bring together renowned Computational Biologists from around the world, including both pioneers in the field, as well as promising young scientists. Presentations, discussions and dialogue during the Symposium will contribute to survey the status of a discipline that, at the intersection of Biology and Computation, will have an enormous impact on the world of the XXIst century.

Confirmed Speakers
Amos BAIROCH Swiss Institute of Bioinformatics (SIB) and University Geneva, Geneva CH
Mathieu BLANCHETTE McGill University, Montréal CA
Søren BRUNAK Technical University of Denmark, Kongens Lyngby DK
Philipp BUCHER Swiss Institute for Experimental Cancer Research (ISREC), Lausanne CH
Brendan FREY University of Toronto, Toronto CA
Mark GERSTEIN Yale University, New Haven US
Nick GOLDMAN European Bioinformatics Institute, Hinxton UK
Tim HUBBARD Wellcome Trust Sanger Institute, Hinxton UK
Eugene V. KOONIN National Center for Biotechnology Information, Bethesda US
Gene MYERS Janelia Farm Research Campus, Ashburn US
Chris PONTING University of Oxford, Oxford UK
David SANKOFF University of Ottawa, Ottawa CA
Ron SHAMIR Tel-Aviv University, Tel-Aviv IL
Temple F. SMITH BioMolecular Engineering Resource Center, Boston US
Terry SPEED Walter & Eliza Hall Institute of Medical Research, Parkville AU
Peter STADLER Universität Leipzig, Leipzig DE
Gary STORMO Washington University School of Medicine, Saint Louis US
Ana TRAMONTANO Sapienza University, Rome IT
Michele VENDRUSCOLO University of Cambridge, Cambridge UK
Martin VINGRON Max Planck Institute for Molecular Genetics, Berlin DE

A new journal for "big" Science

 I have a mixed feeling for the current proliferation of scientific journals. On the one hand I feel that it is a natural response to the increase in the number of researchers in the world and the growing specialization of science. Moreover, it serves to open up the publication system to the wider community and sometimes breaks up dangerous closed circles that monopolize the access to publication in certain areas. On the other hand, as a researcher with broad interests and one who wants to follow the progress of my field, I feel overwhelmed. Times when browsing the table of contents (TOCs) of a handful of journals was enough to identify almost all relevant papers are definitely over. Nowadays one needs complex literature-mining strategies to try to cope with the flow. It seems one also needs to search for potential new Journals that may become the forum for papers relevant to your research. I'm keen to use this blog to spread the word of new Journals that are relevant to my field, as I did in the past. Now I am doing it again.


When I recently heard about the new BMC-based journal Giga Science Journal I felt it will be worth to keep an eye. As they say, "GigaScience aims to revolutionize data dissemination, organization, understanding, and use. An on-line open-access open-data journal, we publish 'big-data' studies from the entire spectrum of life and biomedical sciences."

 
 The original idea of this journal is that it links standard publication with a database to store and search all asociated data. I personally think this journal will fill and important gap and seems perfectly prepared to do so, as judged by the The editorial board, which includes many researchers from centres that are at the forefront of massive data production such as BGI, Wellcome Trust, EBI, JCVI, 

I am looking forward to the first articles to see direct examples of how effective this system is and how the database fits the needs of inherently diverse types of data, but at a first glance it seems that this journal may meet the needs of upcoming studies on massive data such as those coming from genomics or systems biology.

Learn Neighbor Joining method in 1-minute video.

 Hi,

 Have a ruler, a pen, scissors and some tape and glue around?... enough to reconstruct the tree of apes!.

I came across a short video, which illustrates for the general public how to build a phylogenetic tree from pair-wise distances.  The video has been made by Hidetoshi Shimodaira, the guy behind CONSEL package. I am already using it for teaching purposes.

Will we have one on ML and Bayesian reconstruction?


http://www.youtube.com/watch?v=PwiWgVdJ4Y8

Bioinformatics Summer School in Bratislava

Just a quick announcement for a 1-week summer school of bioinformatics in Bratislava, in which I will be lecturing. You can have more info here. 

 Here is a short description from the course website:

The summer school will provide an overview of several areas of computational biology, covering concrete tools, examples of their use, and underlying models and methods. Intended audience includes biologists who want to become more experienced bioinformatics users as well as computer scientists, mathematicians and others who are interested in this exciting research area. The summer school is primarily targeted at doctoral students and postdocs, although more experienced researchers or Master students are welcome to attend as well. The program will include lectures, practical workshops, and research seminars given by experienced researchers from several countries. Working language is English.

Useful tool:phylowidget

Hi, I wanted to share this finding (phylowidget) that is making my life easier with respect to collaborations with experimentalists that are not used to handle newick files.

 I used to send .pdf or .png figures in order to share the results on my phylogenetic analyses, but having the possibility to interactively work with the figure is much better.

 Now I can send a simple link in this way (a very simple example):

http://www.phylowidget.org/lite/index.html?tree='(A:0.1,B:0.2,(C:0.3,D:0.4):0.5);'

and your colleague will be able to explore it. You can play around with the layout and really generate cool images. If the tree is huge you will have to place the file somewhere and provide the URL to phylowidget. This project was developed by a student within the google's summer of code program, which highlights the interest of this initiative.

In the future we plan to have something similar implemented in ETE.