Halloween is over, and today is election day, go vote! Then, come back and read about what we planning for our next steps in Next Gen sequencing.
This month we are preparing SBIR proposals to target some of the real challenges researchers face when working with next-generation (Next Gen) sequence data.
The first will deal with issues related to detecting rare variants in cancer. With our collaborators we plan to develop control samples to detect different kinds of mutations and use the samples and data produced to develop new software tools and interfaces for measuring results. While the work will focus on cancer research, detecting rare variants in large datasets is a common problem with many applications.
The second proposal will deal with improving tools and methods to validate datasets from quantitative assays that utilize Next Gen data. When you run an RNA-Seq, ChIP-Seq, or Other-Seq experiment, where you collect numerous molecular tags from RNA or DNA in your research samples, how do you know that your data represent interesting biology and are free of artifacts? Pulling the relevent features, that distinguish biological reality from experimental artifact, out of datasets comprised of millions and millions of reads can be a real problem.
The above projects will leverge Geospiza's, Geospiza customers, and community experience to develop novel features and integrated resources that will be added to FinchLab, new products, and open-source contributions to make your work easier. If you are interested in learning more about these projects and (or) participating in working with us to takle the next-generation of hard problems contact us.