Tag Archives: Cytoscape

Grinstein on dataviz at VIZBI.

Video Tip of the Week: Weave, Web-based Analysis and Visualization Environment

At the recent Discovery On Target conference, a workshop on data and analytics for drug discovery contained several informative talks. This week’s Video Tip of the Week was inspired by the first speaker in that session, Georges Grinstein. Not only was the software he talked about something I wanted to examine right away (Weave)–his philosophy on visualization of data was so in line with my informal thoughts on the topic that I just connected with it immediately. But also–stay for the “living figures” down below.

Grinstein on dataviz at VIZBI.

Grinstein on dataviz at VIZBI.

Grinstein has been working on dataviz for a long time. And he’s been working with big data since long before big data was trendy. For some of his background and philosophy, check out this talk at a VIZBI conference. Because so many of the problems are the same across big data types, the software that he’s been working on could really be useful for the new issues facing big data in biology. But I don’t know that I’ve heard about it among the genoscenti just yet. (In this talk he also covers RadViz, a radial visualization tool that some folks might find useful. It was also mentioned in the workshop.)

One of the key things that he wanted us to take away from the workshop was that we need to offer people multiple, interactive visualizations for them to get the most of out the data. This is something I’ve been looking for quite a bit. I fell in love with an early version of the Caleydo stuff for exactly this reason. But I understand that it can be tricky.

Weave, or the Web-based Analysis and Visualization Environment, gets closer to this with super responsiveness than I’ve seen elsewhere. This week’s Video Tip is a short intro to this platform, but I’ll link you below to a longer form that you should watch if you want to dive into this tool. Here you’ll see that just by dragging a CSV file in, you can then set up a scatter plot, bar chart, parallel coordinates, a color histogram, and a table. In seconds. Really.

This brief intro doesn’t do full justice to this tool, of course. I joined the Weave-users discussion group and found a recent webinar recording that you should watch. But you’ll have to grab it from the group, it doesn’t appear to be stored on a video platform site (search for the thread called IVPR Update on Weave Monday 3/23). It goes into more detail on the features, of course. And sharing data, and reproducibility of the visualizations with the session history options.

I downloaded the Weave Desktop and ran it on my little system. I grabbed some transcription factor score data from the ENCODE project with the UCSC Table Browser, got it in csv format, pulled it in, and within seconds was looking over all the data on the X chromosome for this TFBS I was interested in. Clicking an item in my table highlighted it in my histogram. And that was just to kick the tires. According to the video, you could have had a tile of Cytoscape (because you can integrate with Cytoscape–I didn’t get that far yet though) and checked out interaction data as well. Although I mention Cytoscape because readers here probably know it, that’s just one of the linkable tools. R is embedded, and other stats tools, and you can modify your scripts right from Weave. Some of these additional features may be part of the Analyst Workstation sub-project. I couldn’t always tell which tool had which features in my early explorations.

But if there’s one thing I’d like you to do after reading this post (if you read this far) is look at this paper that is just out. As I was noodling on Weave, I thought to myself that it was PERFECT to create the kind of “living figures” that I want to see in more papers. Now go see Dynamic Data Visualization with Weave and Brain Choropleths. I don’t care if you aren’t interested in brain choropleths–go look at the figures. In each one, there’s a link to a Weave demo, like this:

Weave demo PLOS

Click on those demos to load them. You can be interacting with the data on the brain maps, with pre-set Weave tiles of different features of the data set for you. Open the gears icons to change the settings. Now imagine this with gene expression maps in C. elegans bodies. Or with transcription factors and scores in mouse embryos. Or Venns with big piles of GO terms (but what I really want there is UpSet anyway). Or any of a dozen other types of data we get in big data papers now that are really impossible to explore in traditional publication format. I want this for genomics papers in the future, okay?

This software has a lot of potential for analysis, visualization, and sharing of data. I can’t cover it all in a brief blog post. The Weave team has thought carefully about sharing with colleagues, reusable templates, and provenance of data, and all this is built right into to this tool. If you are analyzing data for others, you can set up dashboards for them to see specific views. See their help and info docs for more details, and check out the longer videos in the forum.  I think it would connect with a lot of people–and could benefit the genomics community greatly. Have a look. I think you’ll like it.

Quick links:

Weave: http://iweave.com/

GitHub: https://github.com/WeaveTeam

Weave-users discussion: https://groups.google.com/forum/#!forum/weave-users

Weave desktop: http://info.oicweave.org/projects/weave/wiki/Installer

More videos, Weave IVPR channel: https://www.youtube.com/channel/UCXJrO9cug3c7B7eRJSwZ4vQ


Patterson, D., Hicks, T., Dufilie, A., Grinstein, G., & Plante, E. (2015). Dynamic Data Visualization with Weave and Brain Choropleths PLOS ONE, 10 (9) DOI: 10.1371/journal.pone.0139453

Daniels, K., Grinstein, G., Russell, A., & Glidden, M. (2012). Properties of normalized radial visualizations Information Visualization, 11 (4), 273-300 DOI: 10.1177/1473871612439357

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…

Priorities when the workplace is on fire:

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…

  • Wait, where is the $100 genome exactly? I must have missed a tweet somewhere RT @deanhendrix: If we can sequence a human genome for $100, why can’t we openly publish for $100? http://t.co/JUIg5HnZ via @thePeerJ #openaccess #cmonnow  [Mary]
  • RT @genetics_blog: NAR: Most conserved non-coding sequences are regulatory factor binding sites http://t.co/kcFwPeZ7 #bioinformatics [Mary]
  • RT @bffo: Very cool, new cystoscope App store http://t.co/u8gbLiAk #Bioinformatics [Mary]
  • Heh–fair point: RT @phylogenomics: At end @mjpallen says “Radio has survived alongside TV” in reference to how traditional microbiology will survive alongside genomics #SAMG12 [Mary]
  • RT @mem_somerville: Was looking up old story, realized that Nurse, Venter, Collins all have motorcycles. Want to see them race. (must be a gene…) [Mary]
  • @OpenHelix: RT @genome_gov: #microbiome Mapping of human microbiome produces insights, surprises. http://t.co/TYiXCvgX [Mary]
  • And then… RT @matthewherper: Was The Human Microbiome Project A Waste Of Money? – Forbes http://t.co/Crb9eFzo via @sharethis [Mary]
  • And then…snorf:
  • Oooh boy: RT @drbachinsky: Hay Festival 2012: Dull middle-aged scientists should not get grants, says DNA pioneer James Watson via @Telegraph http://t.co/1iGAfFof [Mary]
  • I want to photosynthesize. RT @Argent23: The next twist in the Elysia story. Seems like >50 algal chloroplast genes were transferred into the slug genome! http://t.co/fDJ4iJYa [Mary]

Special Bonus item: if science had tabloids—you have to go see Francis Collins and Fred Sanger “Hot Pics!” http://fakescience.tumblr.com/omgscience

Video Tip of the Week: GenomeSpace, an integrator of integrators

Recently, the Broad Institute announced a new tool: GenomeSpace. When I first looked at it, admittedly a very cursory look, I wasn’t sure how it would be much different than an integrator of tools like Galaxy or GenePattern. Obviously that cursory look was wrong at first glance since both Galaxy and GenePattern are in their list of tools that are supported. So what is GenomeSpace? Well, you can read the answer here at their “What is GenomeSpace” page :). Basically, GenomeSpace has several functions. As described here, “GenomeSpace supports several bioinformatics tools, all integrated to allow easy accessibility, easy conversion, and frictionless sharing.” It is a space (in that every expanding Amazon cloud) that allows you to store your data files and, importantly, GenomeSpace allows you to seamlessly move those files between the tools to complete complex, or simple, analyses. It achieves this by automatically converting file formats and by allowing the user to attach their accounts at the tools to their account at GenomeSpace, thus alleviating the need to log in several times when using more than one tool.

To get a good idea of what GenomeSpace might be able to do for a researcher, check out the recipes on the site. As Anton  states:

GenomeSpace is an integration of integrators,” Nekrutenko said. “The benefit to the user is that this brings together distinctive collections of functionalities offered by individual tools.”

The site is new, and only in beta. They only recently opened up registration from their invite-only stage. As such, there are some bugs and some features that aren’t quite at full capacity. For example, the Galaxy and UCSC Table Browser integration is with the test versions of those tools during beta. Thus, for example, your account at Galaxy will not be recognized when trying to link that account with GenomeSpace. I had to create a new one on the test site. And, if you go to the public version of the Table Browser, it will look different (no link to GenomeSpace as there is on the test site). Currently there are seven tools, more to come.

All that aside, it’s definitely a tool to get acquainted with. And with that in mind, take a quick introductory spin with me in this week’s video tip to get an idea of what you might be able to do.

Quick Links:

UCSC Table Browser (OH tutorial)
Galaxy (OH Tutorial)
Cytoscape (OH Tutorial)

Broad Institute


What’s the answer? Cytoscape plug-ins

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:

Cytoscape Plug-in for retrieving Protein-Protein Interactions

I wish to find out all interactions WITHIN a set of around 200 HUMAN proteins. The identifiers I can use are gene_name, Uniprot_accession and Uniprot_Ids. So far I tried two plugins viz. MIMI and APID2NET.

MIMI doesn’t seem to accept 200 proteins in one go, so I’ve to merge the networks. APID2NET shows too many nodes without any interactions. The STRING DB shows quite a many interactions for which MIMI/APID2NET don’t report anything.

I tried the STRING plugin too, but it looks like it can accept one ID at a time. Am I missing something here?

Can somebody recommend some good and hassle less plugins/tricks to import PPIs. I’ve to do subsequently a BINGO analysis.

Thanks in advance


Although most people in this arena will be familiar with Cytoscape, it can be challenging to know which specific plug-ins might be best for a given purpose. One of the cool things about a forum like BioStar is that there is a range of folks who have wide experience with the tools from so many different projects that often someone has a bit of guidance on things that did (or didn’t) work.

In this case someone offered a suggestion that seemed to fit the bill precisely! Check out the answers, and note the selected () answer to see which it is. It’s a tool I noticed in the past partly because it was the first bioinformatics tool that I had seen that came from Cuba and I thought that was cool–BisoGenet.

But if you have other suggestions you can also offer them at BioStar.

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…

Guest Post: iRefWeb — Andrei Turinsky

This next post in our continuing semi-regular Guest Post series is from Andrei Turinsky, one of the developers of iRefWeb. If you are a provider of a free, publicly available genomics tool, database or resource and would like to convey something to users on our guest post feature, please feel free to contact us at wlathe AT openhelix DOT com or the contact form (write ‘guest post’ as subject heading). We welcome introductions to your resource, information on updates, highlights of little known gems or opinion pieces on the state of genomic research and databases.

What is iRefWeb?

Protein-protein interactions (PPI) have become an important tool in biomedical research. Yet the PPI data for a specific organism tend to be distributed over a number of different databases. Comparison and integration of PPI information across databases remains a challenging task.

iRefWeb (Turner et al. (2010) Database, Vol. 2010, Article ID baq023.) is a web interface to a broad integrated landscape of protein-protein interactions (PPIs). For a given gene or protein, you can access all PPI records and protein complexes, consolidated non-redundantly from ten major public databases: BIND, BioGRID, CORUM, DIP, IntAct, HPRD, MINT, MPact, MPPI and OPHID. iRefWeb also presents various supporting evidence, helping you to gauge the reliability of an interaction. Versatile search filters allows you to retrieve the PPIs with a given level of support. Other features facilitate the analysis of possible inconsistencies across PPI data and the examination of PPI statistics. Data consolidation procedure effectively combines redundant records using the iRefIndex process (Razick et al (2008) BMC Bioinformatics 9, 405.).

Figure 1: The iRefIndex process aggregated over 916,059 original PPI records from source databases, 75% of which were redundant. The consolidation merged the redundant PPIs, reducing their number four-fold (orange). Only 232,612 PPIs were non-redundant (blue)

Continue reading

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…

  • A WordCloud Plugin for Cytoscape is now available from the Gary Bader lab. You can read a description of it and download it on this page. [Jennifer]
  • Undergraduate Guide to R by Trevor Martin; hat tip to Storey Lab for that. [Mary]
  • Cool resource, hat tip to James: “Just discovered MorphBank, a database of creative commons licensed images of biological specimens: http://www.morphbank.net” [Mary]
  • Clinical trial for “Finicky Eating in Adults” (F.A.D.) – read a description and fill out the survey, if you are 18+ yrs old, a “picky eater”, and meet other criteria. [Jennifer]
  • GenAge: The Ageing Gene Database. Found this via tweet by attilacsordas, whose code was apparently involved in implementation of this. (I’ll bet that gets even hotter as a topic when boomers get their genomes sequenced…) [Mary]

I ♥ Venns

Ok, I know they aren’t the most sexy graphics in biology–yes, you 3D protein structure geeks have that down. They are a pretty straight-forward representation of the numbers of items in a group and the overlap. But I have always found them really quickly helpful as I’m trying to assess results of lists of things I may have been working on.

So conveniently enough I just got a notice of a new Venn tool today–and it’s a Cytoscape plug-in. That’s a sample of one of the components of it on the right.  And I just happen to be working on the update for our Cytoscape tutorial this week (subscription), so I’ll be able to add it to our tutorial.  Anyway, here’s the notice as it came across the Cystoscape-announce mailing list:

Cytoscape plugin for venn diagrams, version 0.2 has been released.

The plugin provides a diagram view and a details view for comparing two to four Cytoscape groups at a time.

Project web site http://www.dishevelled.org/venn-cytoscape-plugin

Downloads http://sourceforge.net/projects/dishevelled/files/venn-cytoscape-plugin

Screencast http://www.youtube.com/watch?v=UtoW0nVwOV4

This plugin is for Cytoscape version 2.7.0 only, an incompatible change was made in Cytoscape version 2.8.0-beta that hasn’t been resolved or worked around yet.


And they even offer a screencast on it. Check out the interactive capacity of that–a segment of your Venn gets highlighted back on your network/pathway window. How nifty. Made my morning!

Are there other Venn tools out there that people use and like?

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…

  • A Cuban bioinformatics group announces updates to their Cytoscape plug-in. “A new update of SysBiomics database is ready. SysBiomics contains the data feeding BisoGenet network building process; it was updated with most recently versions of protein-protein interactions sources (DIP, BIOGRID, HPRD, MINT and INTACT), GO and KEGG databases as well as the latest information on genes an proteins form Entrez Gene and Uniprot .” Bioinformatics Group http://bio.cigb.edu.cu/ Cool–I think that’s the first tool I know about from Cuba.  [Mary]
  • “In October’s “Nature Genetics”, and just in time for pie-making: http://www.ncbi.nlm.nih.gov/pubmed/20802477 …but where’s the gene that keeps the doctor away?” [Trey, via a colleague’s email :) ]
  • Cool new site on the History of Vaccines. Hat tip to Tara at Aetiology. [Mary]
  • RT @kshameer: RT: @suganthibala: 200 exomes resequenced, found many rare nonsyn SNPs http://bit.ly/bjm2Q6 http://bit.ly/ctQJ59 #genomics #bioinformatics [Mary]