Ingenuity http://www.ingenuity.com Intuitive web-based applications for quickly analyzing and accurately interpreting the biological meaning in your genomics data Thu, 24 Jul 2014 16:18:11 +0000 en-US hourly 1 http://wordpress.org/?v=3.9.1 Product Update: Ingenuity Pathway Analysis 2014 Summer Releasehttp://www.ingenuity.com/blog/news/product-update-ingenuity-pathway-analysis-2014-summer-release http://www.ingenuity.com/blog/news/product-update-ingenuity-pathway-analysis-2014-summer-release#comments Thu, 24 Jul 2014 16:18:11 +0000 http://www.ingenuity.com/?p=4818 For some, summer is defined by a day at the beach, a BBQ with friends or the 4th of July fireworks.  For us, it’s the annual Ingenuity Pathway Analysis 2014 Summer Release.  In the 11 years since we officially launched … Read More

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For some, summer is defined by a day at the beach, a BBQ with friends or the 4th of July fireworks.  For us, it’s the annual Ingenuity Pathway Analysis 2014 Summer Release.  In the 11 years since we officially launched IPA, the application has grown into one of the most well-used and cited (nearly 10,500 citations) bioinformatics tools for modeling, analyzing, and understanding complex biological and chemical systems.

Some of the highlights from this summer’s release:

Exploring Endpoints of Canonical Pathways

Canonical Pathways in IPA have historically displayed disease and functional endpoints as “text boxes.” Now, these endpoints can be used to interactively visualize the directional impact a pathway exerts upon them. In the new IPA release, diseases and functions on Canonical Pathways are interactive and can be used by the Molecule Activity Predictor (MAP) to simulate the effect on disease or function. Using this feature, you can now explore how endpoints of Canonical Pathways may be increased or decreased based on activation or inhibition of molecules within that pathway.

Discover & Explore Diseases or Functions

It’s never been faster to discover diseases or functions that are biologically (and statistically) relevant to a set of molecules on a network or pathway. With Ingenuity IPA, you can now automatically connect diseases or functions of interest to the relevant molecules and use MAP (Molecule Activity Predictor) to simulate how activated or inhibited molecules are likely to affect the disease based on findings in the Ingenuity Knowledge Base.

Configure Comparison Analysis Heat Maps

When comparing an analysis heat map, you can quickly focus on diseases, functions, or Canonical Pathways of interest and narrow the list of diseases, functions, or pathways that are shown in a given heat map. In the Disease and Functions tab, you can filter on major categories or on specific individual diseases and functions.

If you have any questions about these new features, please do not hesitate to contact our support team.

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Genomic Data Needs Standards and Best Practices to Succeed in the Clinichttp://www.ingenuity.com/blog/news/genomic-data-needs-standards-best-practices-succeed-clinic http://www.ingenuity.com/blog/news/genomic-data-needs-standards-best-practices-succeed-clinic#comments Tue, 22 Jul 2014 21:28:16 +0000 http://www.ingenuity.com/?p=4813 As more and more scientists upload exome and whole-genome data to analyze with QIAGEN’s Ingenuity applications, we are reminded of the high stakes for ensuring that genomic data formats are standardized so they can be shared across research and clinical … Read More

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As more and more scientists upload exome and whole-genome data to analyze with QIAGEN’s Ingenuity applications, we are reminded of the high stakes for ensuring that genomic data formats are standardized so they can be shared across research and clinical enterprises.

To that end, we are proud to be a member of the Global Alliance for Genomics and Health. As many blog readers already know, the Global Alliance (or GA4GH) is an international coalition of more than 150 organizations that have joined forces to come up with standards and best practices for genomic data. The ultimate goal is to advance the use of genomic data in the clinic for improved diagnostics, treatment, and basic understanding of disease and drug response.

The Global Alliance principles really resonate with the QIAGEN Silicon Valley team. One of the major challenges highlighted by the alliance is that of data access, integration, and interoperability; they point to data silos as a real barrier to advancement in clinical genomics. All of our products, and the Knowledge Base engine that powers them, are based on the tenet that discovery and analysis happen most effectively when data is completely integrated with consistent formatting and ontology.

As scientists and clinicians around the world gear up to generate more genomic data than we’ve ever seen before, it is critical that we as a community establish standard data formats, compatible analysis tools, and best practices for data interpretation.

Another aspect of the Global Alliance is to encourage data sharing, something that we’ve championed for years. The Publish and Share tools in our products allow customers to make their exact analysis workflow transparent and reproducible for others in the field, as well as enabling other scientist to reanalyze the original data in different ways. These features were designed to improve the overall quality of science and to let researchers be as open as they wish to be.

With so much at stake, the Global Alliance will take time to develop its best practices. We look forward to working closely with all of the other members to build something great for this community, and to make genomics as useful as possible in mainstream medicine.

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The Ingenuity® Knowledge Base: The Big Picture!http://www.ingenuity.com/blog/science/ingenuity-knowledge-base-big-picture http://www.ingenuity.com/blog/science/ingenuity-knowledge-base-big-picture#comments Wed, 16 Jul 2014 02:08:51 +0000 http://www.ingenuity.com/?p=4761 We ran a series of blog posts the last few months where we took a closer look at the Ingenuity Knowledge Base. We highlighted the manual curation, depth of content, integration efforts as well as advanced analysis tools that make this repository unique. Now that … Read More

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We ran a series of blog posts the last few months where we took a closer look at the Ingenuity Knowledge Base. We highlighted the manual curationdepth of contentintegration efforts as well as advanced analysis tools that make this repository unique. Now that we’ve explored various aspects of the Ingenuity Knowledge Base, here’s a handy infographic to help you visualize how it all comes together — and how it can help you interpret your gene expression and sequencing data.

Ingenuity Knowledge Base infographic final4 (2)

Click on the infographic above to download the PDF

Listed below are the four previous blog posts, in case you missed them:

Please feel free to download the Ingenuity Knowledge Base infographic and share among your colleagues.  Leave your comment on our Ingenuity Knowledge Base blog series below. We’d love to know how it has helped you in your research and analysis.

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Getting to Know The Ingenuity® Knowledge Base: Analysis Tools (Part 4 of 4)http://www.ingenuity.com/blog/products/getting-know-ingenuity-knowledge-base-analysis-tools-part-4-4 http://www.ingenuity.com/blog/products/getting-know-ingenuity-knowledge-base-analysis-tools-part-4-4#comments Tue, 24 Jun 2014 18:52:32 +0000 http://www.ingenuity.com/?p=4726       In this blog series, we’ve been taking a closer look at the Ingenuity Knowledge Base. So far, we have looked at the depth of content as well as the manual curation and integration efforts that make this … Read More

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Ingenuity Knowledge Base

 

 

In this blog series, we’ve been taking a closer look at the Ingenuity Knowledge Base. So far, we have looked at the depth of content as well as the manual curation and integration efforts that make this repository unique. Today we’ll look at the advanced algorithms that compute across all of this information to deliver the most relevant and useful results to scientists using Ingenuity Pathway Analysis (IPA), Ingenuity Variant Analysis, and our new Ingenuity Clinical product.

Just as we have developed unique approaches to curating and integrating content, the team behind Ingenuity Knowledge Base has come up with sophisticated algorithms to accelerate scientific discoveries using methods you can’t find in any other web-based bioinformatics solution.

For example, while other tools can help you find links between genes or genetic elements, we have taken the next step and show you the directionality between those elements — not just that there is a link, but the nature of the linkage. Instead of “A is associated with B,” Ingenuity Knowledge Base captures the nature of the association. For example: “A increases B” or “A decreases B” (where A and B might be genes, small molecules, transcription factors, or other elements). This is very important when you want to use the Knowledge Base for computational purposes. These directional associations are leveraged by advanced statistical and modeling to generate biologically relevant predictions. This provides valuable and unique information about activation or inhibition that will set the stage for your next experiment. Such analysis is a critical component of our Causal Network Analysis  and Upstream Regulator Analysis computational tools within IPA, which predict regulators, downstream effects, or whole networks based on gene expression data.

Further leveraging the computational power of these relationships, we have introduced advanced simulation tools, so applications powered by Ingenuity Knowledge Base can simulate biologically relevant upstream and downstream effects based on underlying content. Given specified activity of a particular molecule, for instance, you can see at a glance what effect that would have on other molecules, functions, or diseases. This feature, available through IPA, can be used even without your own data set, giving scientists an opportunity to explore complex interactions of molecules even before performing an experiment.

Across our algorithms, one of our guiding principles has been ease of use for people interacting with Ingenuity Knowledge Base. The greatest analytics in the world wouldn’t mean much if they were too complicated to use! We always spend a great deal of time designing the functionality, testing the usability, documenting its usage, and leveraging the computational horsepower of the cloud to run all these computations so that users don’t have to worry about processing power or elbowing neighbors off an in-demand local cluster. Taken together, these attributes make it much easier and faster for users to test a hypothesis than if they were running, say, a series of R packages, perl scripts, or some other one-off solution.

This is further demonstrated in Ingenuity Variant Analysis, where we leverage the vast array of complex directional relationships and interactions to provide biologically relevant predictions of causal genetic variation from DNA sequencing data. By using the Biological Filter within Variant Analysis, users can supply biological terms that describe the disease of study, and sophisticated algorithms will walk the ontology and compute across relationships to prioritize variants of interests. The biological terms the system accepts span from abstract to highly specific, and the semantic algorithms do the rest of the heavy lifting. This enables the user to focus on a biological area of interest while the system prioritizes variants of interest.

As we explore and expand our definition for how we think about the power of the Ingenuity Knowledge Base, Variant Analysis offers publicly available reference data sets so users can see how their results vary from normal. For example, you could select the 1,000 Genomes project as a filter within the Variant Analysis Filter cascade and see immediately that the mutation occurring at 20 percent in your population only occurs at 0.4 percent in the average population, with additional biological context provided by Knowledge Base — a real boon as you’re trying to make sense of genetic variants.

And as we push the boundaries we are discovering new utility for the Ingenuity Knowledge Base. Most recently, this includes resolving a key bottleneck faced by clinical geneticists in interpreting sequence-based diagnostic tests. In support of Ingenuity Clinical we have significantly expanded our investment and content coverage of genetic variation to disease phenotype association. As our coverage grows for each disease area, algorithms developed based on standards from ACMG, AMP, CAP, and others in the genetic testing community can help prioritize and score clinically relevant genetic variation from clinical tests. This enables medical geneticists to take advantage of the richness of sequence-based tests previously unavailable while scaling the clinical testing laboratory capacity to interpret these tests.

As you can see from this series of blog posts, we have invested a tremendous amount of time and effort building Ingenuity Knowledge Base into the underlying platform that powers the Ingenuity web applications — now you can understand why we’re so proud of it!

Thanks for taking the time to read these blog posts and learn more about the engine powering all of our great applications.

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Supporting STEM Education with Bioinformatics Programhttp://www.ingenuity.com/blog/news/supporting-high-school-stem-education http://www.ingenuity.com/blog/news/supporting-high-school-stem-education#comments Wed, 18 Jun 2014 18:52:59 +0000 http://www.ingenuity.com/?p=4674 According to the U. S. Department of Commerce, STEM occupations are growing at 17 percent, while others are growing at 9.8 percent. It has been estimated that by 2020, the U.S. will demand 123 million highly skilled workers, but there … Read More

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High-school bioinformatics program led by Dr. Michael Edwards

Dr. Michael Edwards teaching bioinformatics mini course at High School at the Green Valley Ranch Denver School of Science and Technology.

According to the U. S. Department of Commerce, STEM occupations are growing at 17 percent, while others are growing at 9.8 percent. It has been estimated that by 2020, the U.S. will demand 123 million highly skilled workers, but there will only be 50 million qualified people to fill these roles.

As part of the life science community, we are taking an active role in supporting STEM programs.  STEM-focused educational programs are one of the primary ways we can pique the interest of young people who will be the researchers and engineers of tomorrow.

We recently supported a high-school bioinformatics program led by Dr. Michael Edwards, an IPA customer and power user. Dr. Edwards is a bioinformatics expert and assistant professor at the University of Colorado, Denver.

The course, which ran for 2.5 weeks and included 75, 11th-grade students from the Green Valley Ranch Denver School of Science and Technology, was developed by Dr. Edwards with the help of science teachers, Jeremy Wickenheiser and David Scudder, at the school. As part of their hands-on unit, they used top-of-the-line bioinformatics software, including Ingenuity IPA, to analyze real scientific datasets. At the end of the session, they presented their findings to the group.

“To my knowledge, we are the first school in the nation to offer this level of instruction in bioinformatics, at this stage of education, to this many kids,” said Edwards, commenting on this innovative program.

Dr. Edwards hopes to continue providing this program to high school students in the Denver area and drawing them into a rewarding profession of research and discovery in the life sciences.

Pictures from this course can be found on Dr. Micheal Edwards’s facebook page.

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Getting to Know The Ingenuity® Knowledge Base: Content Integration (Part 3 of 4)http://www.ingenuity.com/blog/products/getting-know-ingenuity-knowledge-base-content-integration-part-3-4 http://www.ingenuity.com/blog/products/getting-know-ingenuity-knowledge-base-content-integration-part-3-4#comments Wed, 11 Jun 2014 17:00:32 +0000 http://www.ingenuity.com/?p=4626 In this blog series, we’ve been taking a closer look at the Ingenuity Knowledge Base. Our other posts described the manual curation process we use to ensure the highest quality of information in our database and the ExpertAssist Findings that … Read More

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The Ingenuity Knowledge Base

In this blog series, we’ve been taking a closer look at the Ingenuity Knowledge Base. Our other posts described the manual curation process we use to ensure the highest quality of information in our database and the ExpertAssist Findings that add depth of content. Today, we look at how content from many disparate sources is integrated to make information computable across The Knowledge Base so it can be used to power Ingenuity Variant Analysis, Ingenuity Pathway Analysis, and our new Ingenuity Clinical tool.

The Ingenuity Knowledge Base pulls content from dozens of different sources, from publicly accessible scientific and clinical databases to peer-reviewed journals and more. On the database front, this includes findings and annotations from major NCBI databases (EntrezGene, RefSeq, OMIM disease associations), targets and pharmacological relevance of FDA-approved and clinical trial drugs, clinical biomarkers, Gene Ontology annotations, a normal gene expression body atlas for more than 30 tissues and the NCI-60 panel of cancer cell lines, microRNA-mRNA target databases and GWAS databases. For journals, we curate information from nearly 4,000 scientific publications.  And now with the acquisition of BIOBASE, we are expanding coverage to include HGMD, PGMD and others.

But of course it would be of limited utility if we just aggregated this information in its original state. So our team developed QIAGEN’s Ingenuity Ontology, a framework for organizing and describing biological evidence that allows users to ask questions across all of these data sources and get a coherent answer back. Other taxonomies in the scientific realm tend to be isolated, but our ontology offers a way to integrate all of the content together with consistent terms and references. That careful structure lets us add information all the time without having to reclassify existing data. The idea was simple: there’s a lot of insight that can be extracted from a very large, horizontally and vertically integrated the Knowledge Base.

Indeed, it turns out that users of Ingenuity products can perform remarkable modeling processes and can get a clearer view of the relationship between the wholes and the parts in biological relationships when information is well integrated. Pulling together, for instance, separate information sources about variants and about disease allows for the discovery of many connections that may not otherwise be obvious. That provides for more predictive analysis and more comprehensive views of biological network behavior.

Also, because we store everything in a very consistent way, the data is useful both inside and outside of the Ingenuity Knowledge Base. We support public identifier sets such as RefSeq IDs, microarray chip numbers and genetic coordinates that allow users to import their own data and link it to information from external sources. That keeps our content interoperable and really maximizes value for users.

Content integration isn’t just about bringing in massive amounts of data and formatting it consistently. Our framework also filters content, testing for structural integrity and other factors. That lets us alert a public database when we find an error — a handy way to give back to the community — or flag scientific content that doesn’t seem likely. This helps to make sure the original source gets carefully reviewed.  Further, the ontology provides consistent layers of abstraction and extensive use of synonyms to map terms across the different resources.  This framework supports easy traversal across silo’d use of scientific terms across domains, journals and researchers as well as supports the natural evolution of scientific understanding and terminology over time.

In our next Ingenuity Knowledge Base blog post, we’ll take a look at the bigger picture and how the Knowledge Base uniquely powers advanced algorithms that exponentially speed new scientific discoveries in ways no other web-based bioinformatics system has in the past.

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Getting to Know The Ingenuity® Knowledge Base: Timely Comprehensive Content Coverage (Part 2 of 4)http://www.ingenuity.com/blog/products/getting-know-ingenuity-knowledge-base-timely-comprehensive-content-coverage-part-2-4 http://www.ingenuity.com/blog/products/getting-know-ingenuity-knowledge-base-timely-comprehensive-content-coverage-part-2-4#comments Wed, 04 Jun 2014 17:27:51 +0000 http://www.ingenuity.com/?p=4614 In this blog series, we’ve been taking a closer look at the Ingenuity Knowledge Base. Our first post covered the manual curation process that we have been using since the database was first built. Today, we look at a more … Read More

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Ingenuity Knowledge Base

In this blog series, we’ve been taking a closer look at the Ingenuity Knowledge Base. Our first post covered the manual curation process that we have been using since the database was first built. Today, we look at a more recent program we have put in place to add considerable depth of content to the Knowledge Base engine.

ExpertAssist Findings, launched in 2011, are manually reviewed, automatically extracted findings from the abstracts of a broad range of recently published biomedical journals. We modeled the extraction protocol on the Expert Findings process used for our manual curation. Information that comes in through this avenue is manually reviewed for correct mapping and extraction before being imported into the Knowledge Base. That way we maintain the highest quality, have proper synonym resolution, and capture both contextual details and broad functional relationships — all while ensuring the information is computationally accessible.

These findings are updated weekly from about 3,600 scientific publications. (Our Expert Findings manual curation covers the top 300 journals.) This helps keep the Knowledge Base up-to-date with the scientific literature and also broadens the types of content we are able to pull into the information engine.

The other way we provide great depth of content is to pull in more information and curate more biological relationships than any other database. Whether it’s through Expert Findings or ExpertAssist Findings, data pulled into the Knowledge Base is fully contextualized. For example, when integrating a paper about a particular disease, the Knowledge Base will store relevant details from that paper: species, cell gender, cell activation status, the family relationship of patients in the study, zygosity of all subjects, was a mutation benign or malignant, missense or nonsense, and much more.

More recently we have been making significant investments in expanding our coverage of human genetic variation as mapped to disease phenotype and RNA isoform related content.  These coverage investments are driven by the needs of researchers trying to understand and interpret data from NGS technologies, and clinical labs interpreting new sequence based tests.  The addition of content resources from BIOBASE including HGMD, PGMD and others has significantly expanded our hereditary disease and pharmacogenomic coverage, respectively.  When you combine this with new user driven just in time bibliography (JIT-B) support which is under development as part of Ingenuity Clinical, we expect the Ingenuity Knowledge Base will easily maintain it’s gold standard status as the most comprehensive, high-quality, computable, and up-to-date source for biomedical literature as long as researchers find it valuable.

The mantra behind the Ingenuity Knowledge Base has always been that pulling together as much information as possible in the most consistent and high-quality way will be the best way to help scientists answer any kind of question they might have about their experimental results. Our team is constantly looking for ways to add even more to the Knowledge Base.

In our next Ingenuity Knowledge Base blog post, we’ll put together the pieces we’ve talked about with a look at the content integration process that is crucial to keeping all of this information interoperable.

 

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IPA at VBI: Summer Symposium Includes Network Inferencehttp://www.ingenuity.com/blog/news/ipa-vbi-summer-symposium-includes-network-inference http://www.ingenuity.com/blog/news/ipa-vbi-summer-symposium-includes-network-inference#comments Thu, 29 May 2014 16:30:51 +0000 http://www.ingenuity.com/?p=4603 We’re delighted to report that QIAGEN’s Ingenuity Pathway Analysis will be under the spotlight at a symposium hosted by the Virginia Bioinformatics Institute at Virginia Tech. The event will take place from June 9th through 13th and is sponsored by … Read More

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We’re delighted to report that QIAGEN’s Ingenuity Pathway Analysis will be under the spotlight at a symposium hosted by the Virginia Bioinformatics Institute at Virginia Tech.

The event will take place from June 9th through 13th and is sponsored by the Center for Modeling Immunity to Enteric Pathogens (MIEP). The Modeling Mucosal Immunity (MMI) Summer School Program and Symposium will bring together top Virginia Tech faculty and other experts to help experimental immunologists further their knowledge of computational modeling tools that can be useful in evaluating immune system response. The symposium is also open to graduate students in computational biology and bioinformatics.

In addition to IPA, tools covered in the meeting will include CellDesigner, COPASI, ENISI, Cytobank, and Galaxy. QIAGEN’s own Dr. Katherine Wendelsdorf will offer presentations on using IPA for network inference and analysis. Dr. Wendelsdorf is a scientist with a background in modeling; she has focused on analyzing large sets of gene expression data to identify various response states seen in immune cells. She will speak in two back-to-back sessions in the afternoon on Wednesday, June 11th.

Dr. Josep Bassaganya-Riera, Professor of Immunology at VBI and Director of MIEP, said in a statement: “The MMI Summer School and Symposium will provide a window into such promising computational modeling approaches. Participants will learn how they can use these tools for their own experiments and bring their studies to the next level.”

Registration for the symposium is open through June 2.

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