Thursday, April 28, 2011

Product Updates: GeneSifter Lab and GeneSifter Analysis Editions

Spring is here and so are new releases of the GeneSifter products. GeneSifter Lab Edition (GSLE) has been bumped up to 3.17 and GeneSifter Analysis Edition (GSAE) is now at 3.7.

What's New?

GSLE - This release includes big features along and a host of improvements. For starters, we added comprehensive inventory tracking. Now, when you configure forms to track your laboratory processes, you can add and track the use of inventory items.

Inventory items are those reagents, kits, tubes, and other bits that are used to prepare samples for analysis. GSLE makes it easy to add these items and their details like barcodes, lot numbers, vendor data, and expiration dates. Items contain arbitrary units so you can track weights as easily as volumes.

When inventory items are used in the laboratory, they can be included in steps. Each time the item is used, the amount to use can be preconfigured and GSLE will do the math for you. When the inventory item's amount drops below a threshold, GSLE can send an email that includes a link for reordering.

In addition to inventory items we increased support for the PacBio RS, and have made Sample Sheet template design completely user configurable. Sample Sheets are those files that contain the samples' names and other information needed for a data collection run. While GSLE always had good sample sheet support, vendor's frequently change formatting and needed data requirements. In some cases a new software release could be required.

The new sample sheet configuration interface eliminates the above problem, and makes it easy for labs to adapt their sheets to changes. A simple web form is used to define formatting rules and the data that will be added. GSLE tags are used to specify data fields and a search interface provides access to all fields in the database. At run time, the sample sheet is filled with the appropriate data.

View the product sheet to see the interfaces and other features.

GSAE - The new release continues to advance GSAE's data analysis capabilities. Specific features include paired-end data analysis for RNA-Seq and DNA re-sequencing applications. We've also improved the ways in which large datasets can be searched, filtered, and queried. Additional improvements include new dashboards to simplify data access and setting up analysis pipelines.

Finally, for those participating in our partner program, we continue to increase the integration between GSLE and GSAE with single sign on and data transfer features.

More details can be found in the product sheet.

Thursday, April 21, 2011

Science, Culture, Policy

What do science, culture, and policy have in common? In order to improve the quality and affordability of health care, all three have to change. This message is central to Sage Bionetworks’ mission and the theme from this year’s Sage Commons Congress held April 15th and 16th in San Francisco.

What’s the problem? 
Biology is complex. This complexity makes it difficult to understand why some people are healthy and why others get sick. In some cases we have a clear understanding of the biochemical origins of health conditions and their treatments. Unfortunately, most drugs are effective for only a fraction of the people they treat, and in the cases where drugs are effective, their effectiveness is diminished by side effects. The most striking problems being adverse events, which are the sixth leading cause of death in the US.

One way to cost effectively improve health care is to increase the efficacy of treatments in greater numbers of individuals. Also referred to as personalized medicine, the idea is that future treatments are accompanied by diagnostic tests that indicate the treatment's effectiveness. Accomplishing this goal requires that we understand the ways in which drugs affect their specific and non-specific targets with much higher precision. We also need to understand each target’s role in its biological pathway. However, as we attempt to break systems down into pathways and their component parts, a problem emerges. The components participate in multiple pathways and pathways interact with other pathways to form higher-ordered networks, and these interactions vary within individuals.
LinkedIn or Biology?

When visualized, biological networks look a lot like LinkedIn, Facebook, or Twitter networks. In these social networks, individuals participate in many groups and have connections to one another. Unlike social networks, which are easy to dissect, our biological networks comprise millions of interactions between proteins, DNA, RNA, chemicals, and microorganisms. Studying these networks requires advanced data collection technologies, computer programs, software systems, and social interactions. Therein lies the rub.

 More data isn't enough
Turning the vision of personalized therapies into reality requires a large numbers of scientists who understand the power of global analyses and can work together in research communities. Hence, one part of the Sage mission is to get greater numbers of scientists to adopt new approaches. Another part is getting them to share their data in useful ways.

Accomplishing this goal requires changing the research culture from one that emphasizes individual contributions to one that promotes group participation. Our publish or perish paradigm, combined with publication business models, discourages open-access and data sharing. It also reduces innovation. According to data presented by Aled Edwards, when faced with the opportunity to look at something completely new, we focus on well-known research problems. Why? Because funding is conservative and doing the same thing as your peers has less risk.

From Edwards' Presentation
Bottom line, we need to take more risk in our research and take more risk sharing data pre and post publication. Taking more risk means we need to trust each other more.

Simply increasing data availability, however, is not enough. We also need to change health care policy. Vicki Seyfert-Margolis (Senior Advisor, Science Innovation and Policy Office of the FDA) gave a presentation (of her views) that helped explain why research expenditures are increasing while the drug pipeline is getting smaller. She described the medical product ecosystem as a large community of individuals from academia, biotech/pharma, device/diagnostic companies, regulators, payors, physicians, and patients, and discussed how all parties need to be involved in changing their practices to improve outcomes. Seyfert-Margolis closed her presentation by focusing on the public’s (patients') role in changing health policy and how, through social media, the public can become more involved and influence direction.

Changing the world is hard
Sage’s mission is ambitious and audacious. Simultaneously tackling three major problems, as Sage is trying to do, has significant risk. So, what can they do to mitigate their risk and improve success? I’ll close by offering a couple of suggestions.

Education is needed - The numbers of researchers who understand the kinds of data that are needed and how to analyze those data and develop network models is small. Further, technology advances keep moving the target, and evaluating models requires additional bench research and others need to be convinced that this is worthwhile. Sage is on the right path by initiating the conversation, but more is needed to increase understanding and evaluating data. Creating a series of blog articles and tutorials would be good first steps. It would help if presentations focused less on final results and more on data collection and analysis processes.

Be Bold - Part of the congress included presentations about a federation experiment in which a group of labs collaborated by openly sharing their data with each other in real time. This is a good step forward, that would be great step forward if the collaboration ran as a publicly open project where anyone could join. Open it up! Success will be clear when a new group, who is unknown to the current community, forms and accomplishes interesting work with their own data and the commons data. A significant step forward, however, is the openness of the meeting itself as all slides and video recordings of the presentations are available. Additionally, twitter and other forms of realtime communication were encouraged.

In closing, I laud Steven Friend and Eric Schadt for founding Sage Bionetworks and pushing the conversation forward. For the past two years the Sage Commons Congress has brought together an amazing and diverse group of participants. The conversation is happening at a critical time because health care needs to change in so many ways. We are at an amazing conversion point with respect to science, technology, and software capabilities that the opportunity for having an impact is high. Geospiza is focused on many aspects of the mission, and we look forward to helping our customers work with their data in new ways. It’s been a pleasure to have the opportunity to participate and help advance progress.

Wednesday, April 6, 2011

Sneak Peak: RNA-Sequencing Applications in Cancer Research: From fastq to differential gene expression, splicing and mutational analysis

Join us next Tuesday, April 12 at 10:00 am PST for a webinar focused on RNA-Seq applications in breast cancer research.

The field of cancer genomics is advancing quickly. News reports from the annual American Association of Cancer Research meeting are indicating that whole genome sequencing studies such as the 50 breast cancer genomes (WashU) are providing more clues about the genes that may be affected in cancer. Meanwhile, the ACLU/Myriad Genetics legal action over genetic testing for breast cancer mutations and disease predisposition continues to move towards the supreme court.

Breast cancer, like many other cancers, is complex.  Sequencing genomes is one way to interrogate cancer biology. However, the genome sequence data in isolation does not tell the complete story. The RNA, representing expressed genes, their isoforms, and non-coding RNA molecules, needs to be measured too. In this webinar, Eric Olson, Geospiza's VP of product development and principal designer of GeneSifter Analysis Edition, will explore the RNA world of breast cancer and present how you can explore existing data to develop new insights.

Next Generation Sequencing applications allow biomedical researchers to examine the expression of tens of thousands of genes at once, giving researchers the opportunity to examine expression across entire genomes. RNA Sequencing applications such as Tag Profiling, Small RNA and Whole Transcriptome Analysis can identify and characterize both known and novel transcripts, splice junctions and non-coding RNAs. These sequencing based-applications also allow for the examination of nucleotide variant. Next Generation Sequencing and these RNA applications allow researchers to examine the cancer transcriptome at an unprecedented level. This presentation will provide an overview of the gene expression data analysis process for these applications with an emphasis on identification of differentially expressed genes, identification of novel transcripts and characterization of alternative splicing as well as variant analysis and small RNA expression. Using data drawn from the GEO data repository and the Short Read Archive, NGS Tag Profiling, Small RNA and NGS Whole Transcriptome Analysis data will be examined in Breast Cancer.

You can register at the webex site, or view the slides after the presentation.