But researchers are working all the time to understand, characterize, and evaluate viral sequences. They will access a number of different tools to do so. We talked last month about GISAID and EpiFlu as our Tip of the Week, and how the special access agreement they have developed has provided some otherwise reluctant governments to share the newest sequence data. So if you want the most current sequences–you would turn to EpiFlu.

There are other virus resources that you should investigate too. Another important site is the IRD, or Influenza Research Database. They have developed an extensive repository of many flu sequences, and have provided a wide range of tools to help researchers investigate and evaluate the data. In addition, they have incorporated some tools that provide novel analyses of the underlying data. This includes predictions of cytotoxic T-cell epitopes, and a sequence feature variant type analysis that they mention in their recent paper.

For this week’s video tip, I include their first of eight videos that will help you to understand their organization and tools. But be sure to keep going for the other 7 that they offer at their YouTube pages.

Be sure to also read the paper that they recently published–it has a nice overview of their tools, their strategies, and also provides a nice use case example of how to flow through a typical evaluation. And if you want other virus data besides flu check out the companion site Virus Pathogen Database and Analysis Resource. You’ll see a similar organization but with a wider range of sequences available. They have a separate thread of videos for the ViPR tools as well.

Quick links:

IRD, Influenza Research Database: http://www.fludb.org/

Other viruses not just flu are in the Virus Pathogen Resource (ViPR) that offers a similar structure and tools: http://viprbrc.org

References:
Squires, R., Noronha, J., Hunt, V., García-Sastre, A., Macken, C., Baumgarth, N., Suarez, D., Pickett, B., Zhang, Y., Larsen, C., Ramsey, A., Zhou, L., Zaremba, S., Kumar, S., Deitrich, J., Klem, E., & Scheuermann, R. (2012). Influenza Research Database: an integrated bioinformatics resource for influenza research and surveillance Influenza and Other Respiratory Viruses, 6 (6), 404-416 DOI: 10.1111/j.1750-2659.2011.00331.x

Pickett, B., Sadat, E., Zhang, Y., Noronha, J., Squires, R., Hunt, V., Liu, M., Kumar, S., Zaremba, S., Gu, Z., Zhou, L., Larson, C., Dietrich, J., Klem, E., & Scheuermann, R. (2011). ViPR: an open bioinformatics database and analysis resource for virology research Nucleic Acids Research, 40 (D1) DOI: 10.1093/nar/gkr859

BioBase has a series of video tutorials for both TransFac and HGMD (and more for the other databases such as Proteome, Genome Trax and ExPlain). For this weeks tip of the week, we’ve embedded two video tutorials.

This first explains MATCH, an analysis tool in TransFac to predict binding sites for Transcription Factors in a particular DNA sequence.

The second video tip is a quick tutorial on how to get started with searching HGMD

If you are interested in advanced searching of these two databases, or Genome Trax, Proteome or ExPlain, check out the video tutorials from BioBase.

Related Tutorials:DGV: Database of Genomic Variants, DBTSS

The MyCancerGenome site aims to serve that actionable end of the data spectrum. It has been developing for a while, but the recent story in the New York Times reminded me of it: Variations on a Gene, and Tools to Find Them. So for this week’s Video Tip of the Week, I bring you a look at the My Cancer Genome resources. They have a nice intro video that I will include here. It highlights features that I wouldn’t have been able to access–the part that links patient records + mutations + the curated detailed pages about the mutations and relevant studies. The public has access to that last part, but you wouldn’t be able to see the electronic health record part from the public side.

Papers are coming out that describe the deposition of information into the MyCancerGenome site. You can learn more about the philosophy and strategy about cataloging the somatic mutations that are clinically relevant in the recent paper about the DIRECT (DNA mutation Inventory to Refine and Enhance Cancer Treatment) project. A tab at that site shows you the initial data associated with that, from non-small cell lung cancer (NSCLC) mutations in the Epidermal Growth Factor Receptor (EFGR). And as more of this data comes along we’ll see it grow, of course. Seems a good step in translational medicine. So have a look at the useful and evidence-based information about specific cancer-related variations they are collecting.

Another feature is a search option to find clinical trials–by disease or by gene. I don’t think I’ve seen a gene-specific search for this kind of information before. This could be useful for people who need access to new treatment options if they have specific mutation data about their own tumors.

Have a look at My Cancer Genome, and think about where we are going with this data. I hope that the new cancer genomics data will really help drive appropriate and effective treatment strategies.

Quick link:

My Cancer Genome site: http://www.mycancergenome.org/

NYT article: Variations on a Gene, and Tools to Find Them

References:

Swanton, C. (2012). My Cancer Genome: a unified genomics and clinical trial portal The Lancet Oncology, 13 (7), 668-669 DOI: 10.1016/S1470-2045(12)70312-1

Yeh, P., Chen, H., Andrews, J., Naser, R., Pao, W., & Horn, L. (2013). DNA-Mutation Inventory to Refine and Enhance Cancer Treatment (DIRECT): A Catalog of Clinically Relevant Cancer Mutations to Enable Genome-Directed Anticancer Therapy Clinical Cancer Research, 19 (7), 1894-1901 DOI: 10.1158/1078-0432.CCR-12-1894

My Cancer Genome. 2013. http://www.mycancergenome.org (Accessed 4/30/2013).

TCGA–The Cancer Genome Atlas–collects large numbers of data sets on various cancers. They collect different types of data: GWAS, expression, protein, and more. But it can be a challenge to keep up the the huge amounts of data that are coming in. They have a portal where you can query the underlying data sets, with many features that you might be interested in. But another group has developed another strategy to access data sets–their roadmap offers a quicker and easier way to assess, and then access, what’s available, as well as providing a more general strategy for organizing access to the files.

I’ll let the team explain with their own video:

But be sure to check out their paper where they explain their strategy in more detail. They provide links to the queries they generate to you can explore that too. And you can consider this method for other types of data sets you might want to navigate as well.

There may be other ways you want to interact with TCGA data, and you can still access their portal for other types of queries. But this offers another way to quickly locate subsets of data sets that you might be interested in exploring with other tools.

Hat tip to Bell Eapen for the notice:

A self-updating road map of The Cancer Genome Atlas. feedly.com/k/XYsYT0 Good read

— Bell Eapen (@beapen) 21. April 2013

Quick links:

TCGA Roadmap Dashboard: http://tcga.github.io/Roadmap/

TCGA site portal: https://tcga-data.nci.nih.gov/tcga/

References:

Robbins, D., Gruneberg, A., Deus, H., Tanik, M., & Almeida, J. (2013). A self-updating road map of The Cancer Genome Atlas Bioinformatics DOI: 10.1093/bioinformatics/btt141

The Cancer Genome Atlas (TCGA) Research Network (2008). Comprehensive genomic characterization defines human glioblastoma genes and core pathways Nature, 455 (7216), 1061-1068 DOI: 10.1038/nature07385

This week’s video Tip of the Week offers you a quick tour of GISAID’s resources and their EpiFlu™ database. This is the database you might be hearing about in the news—the one to which researchers submit the new H7N9 influenza sequence data that they are collecting. Originally this initiative was seeded as the “Global Initiative on Sharing Avian Influenza Data” but it has evolved to become the “Global Initiative on Sharing All Influenza Data” to describe a broadened mission to collect any flu data. Researchers around the world can quickly share their discoveries of any types of influenza viruses and make the sequence details as well as epidemiological and clinical data available to other researchers, who then explore and analyze that information. Researchers from various disciplines, including veterinary, virology, bioinformatics, epidemiology, immunology, and clinical analysis access this information. Currently the US CDC and others are using the data to explore the development of new vaccines, antiviral drugs, and diagnostic kits and to learn about the characteristics of the virus isolates which could affect public health policy making. Even before they had access to physical virus samples to test, they could begin assessments using the EpiFlu data. In this tip I’ll show you how researchers submit to and access this global resource. My goal is to show researchers who might want to use the information some of the details, but other people might be curious to have a look under-the-hood too.

For today’s tip I focus on how researchers would use the EpiFlu database, with a quick tour of some features. Recently I signed up for access to the site, which was quickly approved. And then I asked the GISAID team for permission to make the video, which they also quickly granted, and I have asked them to review the movie to make sure I didn’t go out of bounds of the Data Access Agreement. As a registered user, I’m not allowed to show the general public the sequence data itself, but I will show you how researchers would obtain the details they need to take their analyses further. And I did get permission to open one record to illustrate a key point the record. (Information in that record has been published in the New England Journal of Medicine by the submission team. Reference below.) Later, you can sign up for access to see the details yourself. The data is publicly accessible, as long as you identify yourself and agree to the terms. The terms of use are not designed to be a barrier to access and research—they are in place to give us the freedom and responsibility to use the data appropriately. There have been objections to this sharing model, but going into detail on the history and development of GISAID is not the subject of this post.

The site details

You can learn more about the issues that were a catalyst to the development of GISAID from an editorial published in Nature, cited below. GISAID continues to evolve, and you can learn more about the state of the current initiative and its scientific advisors by visiting their website. Since 2010, the German government, represented by the Federal Ministry of Food, Agriculture and Consumer Protection is the official host of the site, and the Federal Research Institute for Animal Health is responsible for the quality of the data in GISAID.

When you are logged into the GISAID site, you’ll have access to a range of features. Related news items are posted. You can see the list of all the other registered users, and you can easily contact them from within the system for questions and collaborations. Most importantly, though, you have access to the relational database component called EpiFlu. This is where researchers can submit new sequences that they isolate. There are many fields for storing crucial metadata. The entry form offers different fields depending on the type of isolate and host. EpiFlu is where other researchers can query for the types of strains, hosts, or submission details they are interested in. These sequences and metadata can be downloaded for use with other tools. There are also some analysis tools provided in the EpiFlu interface. Sequences can be submitted for BLAST analysis or used to generate a multiple-sequence alignment with an installation of Jalview.

In speaking with folks at GISAID last week about their philosophy I learned about upcoming new software they are working on. The GISAID group plans an EpiFlu 2.0 which they are building from scratch. That version will have additional features that enhance the connectivity with other resources and for enhancing collaborations, and with better scalability. As we continue to see the deluge of sequence data coming in from all kinds of sources in the future, this will really be necessary. I don’t know what the target date is for the next version, but I’ll be keeping an eye out for that as a future tip.

For non-researchers

If you are a member of the public curious about information sources on the flu, please read this excellent guidance on sources of flu information by Maryn McKenna: The New Bird Flu, and How to Read the News About It. Not all news is the same. Let’s be careful out there.

An example of sequence being submitted to GISAID:

The Hangzhou Center for Disease Control and Prevention, has submitted a new case of the novel H7N9 strain to GISAIDtiny.cc/ojj2uw

— GISAID AI Digest (@AIDigest) 5. April 2013

One last note:

What is important is not the exact #H7N9 case count, but the behavior of the #H7N9 virus

— WHO (@WHO) 10. April 2013

And researchers are using GISAID to help understand the behavior of H7N9 right now.

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Quick links:

GISAID Foundation and EpiFlu website: www.gisaid.org

Follow GISAID on Twitter at @AIDigest: http://twitter.com/AIDigest

Register for access: http://gisaid.org/register

BTW: I also asked how they pronounce their name—it’s like “jees-aid”, if you want to know. I had only seen it written in text form and hadn’t heard it from any sources so I wanted to be sure.

References for the video and post:

Editorial (2006). Boosting access to disease data Nature, 442 (7106), 957-957 DOI: 10.1038/442957a

Butler, D. (2013). Urgent search for flu source Nature, 496 (7444), 145-146 DOI: 10.1038/496145a

Gao, R., Cao, B., Hu, Y., Feng, Z., Wang, D., Hu, W., Chen, J., Jie, Z., Qiu, H., Xu, K., Xu, X., Lu, H., Zhu, W., Gao, Z., Xiang, N., Shen, Y., He, Z., Gu, Y., Zhang, Z., Yang, Y., Zhao, X., Zhou, L., Li, X., Zou, S., Zhang, Y., Li, X., Yang, L., Guo, J., Dong, J., Li, Q., Dong, L., Zhu, Y., Bai, T., Wang, S., Hao, P., Yang, W., Zhang, Y., Han, J., Yu, H., Li, D., Gao, G., Wu, G., Wang, Y., Yuan, Z., & Shu, Y. (2013). Human Infection with a Novel Avian-Origin Influenza A (H7N9) Virus New England Journal of Medicine DOI: 10.1056/NEJMoa1304459

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Disclosure: OpenHelix has no financial or scientific relationship with the GISAID Foundation or EpiFlu. I merely approached them as I do many other resources to ask for permission to do a movie. I offered them the opportunity to review my materials because of the sensitivity of this issue and the desire to NOT cause any kind of international public health incident. The goal of this is to show people the insides of a database or resource that they may not be familiar with.

Here is the first video in their series of introductory videos, and it covers many of the features of their educational site. It provides pointers to helpful resources. It directs folks who are new to the area to the important journals in the field. One of the papers referenced within the video is cited below–Grand Challenges for Cheminformatics. For folks who are new to exploring cheminformatics as a field, it offers a nice overview of important areas of science that will be impacted by cheminformatics research–it’s not just drug discovery, but also environmental issues such as green chemistry and global warming.

The other thing that I like about this portal idea is their low-cost textbook that’s available. I think textbook prices are certifiably insane, and in these fast-changing fields would be much better served by efforts like David’s to assemble an e-book that could be much more responsive to the needs of students today.

So check out the Cheminformatics Education portal for more details.

Quick links:

ICEP Indiana Cheminformatics Education Portal

Cheminforeducation’s YouTube channel

References:

Wild, D. (2009). Grand challenges for cheminformatics Journal of Cheminformatics, 1 (1) DOI: 10.1186/1758-2946-1-1

We’ve laughed in the past about a “genome of the day” because there are so many projects each week that we want to explore, and it’s hard to keep up. But recently I wanted to have a look at the peach genome project, because–well, peaches!

And the summary papers are nice. But generally I want to look around that the resources that are now available for exploring that draft genome. So in the paper the team provides links to a number of places where you can go beyond what’s published and further analyze the outcomes.

You can see the peach genome data and tools available at GDR, the Genome Database of Rosaceae. They’ve got a number of tools, including an installation of GBrowse for graphically browsing the genome. But they also have a neat synteny view of strawberry-peach-apple. I never had a software tool that made me crave a frosty smoothie before… They have additional resources at the GDR site that span quite a range of users–there’s a set of Breeders Toolbox options that you never see with mammalian genomes–ya know?

Another site that you can explore for more details about the peach genome data is Phytozome. In this week’s video tip I examine some of the tools you can use at Phytozome to explore the peach genomic data, but you’ll find other genomes are accessible from the site as well. Calculated gene family relationships can be examined among the species with various viewer and sequence tools.

In the video I explore some of the basic browsing options, but I don’t have time to cover some of the other great features at Phytozome. So I encourage you to check out their paper that explains more about how they organize their data, the additional calculations of the gene family relationships, and the tools to further explore those details. You can also do more complex and customized queries with their BioMart interface, and you can perform sequence searches too.

Quick links to tools:

GDR, Genome Database for Rosaceae: http://www.rosaceae.org/

Phytozome: http://www.phytozome.net main site; Peach landing page: http://www.phytozome.net/peach

References:

Verde, I., Abbott, A., Scalabrin, S., Jung, S., Shu, S., Marroni, F., Zhebentyayeva, T., Dettori, M., Grimwood, J., Cattonaro, F., Zuccolo, A., Rossini, L., Jenkins, J., Vendramin, E., Meisel, L., Decroocq, V., Sosinski, B., Prochnik, S., Mitros, T., Policriti, A., Cipriani, G., Dondini, L., Ficklin, S., Goodstein, D., Xuan, P., Fabbro, C., Aramini, V., Copetti, D., Gonzalez, S., Horner, D., Falchi, R., Lucas, S., Mica, E., Maldonado, J., Lazzari, B., Bielenberg, D., Pirona, R., Miculan, M., Barakat, A., Testolin, R., Stella, A., Tartarini, S., Tonutti, P., Arús, P., Orellana, A., Wells, C., Main, D., Vizzotto, G., Silva, H., Salamini, F., Schmutz, J., Morgante, M., & Rokhsar, D. (2013). The high-quality draft genome of peach (Prunus persica) identifies unique patterns of genetic diversity, domestication and genome evolution Nature Genetics DOI: 10.1038/ng.2586

Goodstein, D., Shu, S., Howson, R., Neupane, R., Hayes, R., Fazo, J., Mitros, T., Dirks, W., Hellsten, U., Putnam, N., & Rokhsar, D. (2011). Phytozome: a comparative platform for green plant genomics Nucleic Acids Research, 40 (D1) DOI: 10.1093/nar/gkr944

For this week’s video tip of the week, I’m going to highlight the services of figshare. Figshare is a terrific resource for storing data, posters, papers, slides, code, movies, and more. Nearly any sort of digital item that you may be creating as part of your research or research communications projects can be uploaded to figshare and delivered to the world. It’s permanent, citable, and people can download and comment about anything you provide.

I’ll highlight some of the basics of figshare, but you should learn more about them in a couple of ways. At their site you can see the summary of the features they offer, and you can also see the publication I have attached below that provides some of the history and conceptual framework for figshare.

As publication and outreach methods are changing, and researchers would like to get demonstrable credit for their output that may be outside of the traditional publication system, alternative metrics or altmetics are being developed to serve that. Figshare can let you assess how many people have seen your items, downloaded them, and eventually there will be a collections of links to the citations for them. It also makes it easier for people who use your stuff to credit you properly for them.

The specific example I’ll illustrate is the recent figshare files that Jean Peccoud and  his group created, and where we have provided the training slides, as a package of training materials for their software and site called GenoCAD. Eventually we’ll have a video and full training collection hosted on the OpenHelix site, but for now we wanted to get the slides out for people to look at. The training also requires folks to upload some data, so the data to use is provided. The exercises to complete the intro training are also posted there. Anyone can try them out, comment, and we can get feedback on them.

You’ll note on that page that we have updated the items more than once. But you’ll still have access to the older ones if you needed them. The page is permanent, and changes are traceable.

Using figshare as a mechanism for outreach, communication, and citation is so terrific for science communicators. Recently Stephen Turner initiated a plea to the bioinformatics and genomics communities to improve their behavior: Stop Hosting Data and Code on your Lab Website. People are expressing a lot of frustration when they can’t find the software some team has said they have used, the sample data, or the full data sets that they used for a publication or presentation.  We know postdocs move on, and that links break. But figshare can help solve that. Figshare is also handy for folks looking for the materials you provide or have described somewhere. And really–there’s just no excuse for not storing your data, code, and any other research related digital materials there. I’m looking at you Sasquatch genome team….

An introduction to the features of figshare can als be found in their video:

An introduction to figshare from figshare on Vimeo.

Do take a look at figshare, and start using it. It will benefit you, and the larger science community as well.

Quick links:

figshare: http://figshare.com/

Stephen Turner’s plea to bioinformatics folks: Stop Hosting Data and Code on your Lab Website (By the way, Stephen also stored that blog post at figshare, so it has a handy citation you’ll also see below!)

GenoCAD training materials example on figshare: http://dx.doi.org/10.6084/m9.figshare.153827

GenoCAD website: http://www.genocad.org/

Peccoud Lab example of using figshare’s API to host the items:  http://peccoud.vbi.vt.edu/genocad-training-set-i/

References:

Stop Hosting Data and Code on your Lab Website. Stephen Turner. figshare. http://dx.doi.org/10.6084/m9.figshare.105125 Retrieved 18:22, Mar 19, 2013 (GMT)

Singh, J. (2011). FigShare Journal of Pharmacology and Pharmacotherapeutics, 2 (2) DOI: 10.4103/0976-500X.81919

Cai, Y., Wilson, M., & Peccoud, J. (2010). GenoCAD for iGEM: a grammatical approach to the design of standard-compliant constructs Nucleic Acids Research, 38 (8), 2637-2644 DOI: 10.1093/nar/gkq086

Today’s video starts off with a kind of silly live-action sequence , but fun silly, and walks through FlyBase on an introductory level. Check it out.

They have a  youtube channel with two additional (and much shorter) videos on using TermLink, a controlled vocabulary search tool, and an introduction to Fast-Track, a community paper curation tool.

 
Today’s tip is from NCBI. Specifically, NCBI’s Genome Workbench. The workbench is

…an integrated application for viewing and analyzing sequence data. With Genome Workbench, you can view data in publically available sequence databases at NCBI, and mix this data with your own private data.

It’s a useful program and they have a great set of videos to introduce you to the workbench’s functions and features. The video embedded here is the introduction, but they also have several additional videos including how to load a genome into the workbench, phylogenies and others. Check it out.

( forgive the delay of this week’s tip. Snow canceled work, and knocked out Internet access!)

Related Tutorials:NCBI Overview