Quick note about this upcoming conference in San Francisco, February 15-20: http://www.triconference.com/. OpenHelix will have a booth there, and I’ll post details about that later, but wanted to draw your attention right now to some of the content.
There’s a lot of stuff going on at this conference, but some particular talks of note to readers of this blog include some folks in the Informatics Channel you might want to hear from:
Integrating Transcriptome and Genome Sequencing to Understand Functional Variation in Human Genomes
Tuuli Lappalainen, Ph.D., Principal Investigator & Core Member, New York Genome Center; Assistant Professor, Systems Biology, Columbia University
Detailed characterization of cellular effects of genetic variants is essential for understanding biological processes that underlie genetic associations to disease. Integration of genome and transcriptome data has allowed us to characterize regulatory and loss-of-function genetic variants as well as imprinting both at the population and individual level, as well as their tissue-specificity and role in disease associations.
Stable Reference Structures for Human Genome Analysis
David Haussler, Ph.D., Distinguished Professor and Scientific Director, UC Santa Cruz Genomics Institute, University of California Santa Cruz
Currently there are many different ways to map individual patient DNA and call genetic variants relative to the human reference genome GRCh38, and on top of this, when an expanded version GRCh39 arrives, quite a bit of remapping and recalling turmoil will be created. I describe a new scheme being developed with assistance from the Global Alliance for Genomics and Health in which mapping to the reference genome and calling variants would become a precisely defined and relatively stable process, with a well-defined incremental update when the reference genome expands to a more comprehensive version. This will enable a better standardized and more accurate discourse about human genetic variation for science and medicine.
Accessible and Reproducible Large-Scale Analysis with Galaxy
James Taylor, Ph.D., Ralph S. O’Connor Associate Professor, Biology; Associate Professor, Computer Science, Johns Hopkins University
I will discuss the Galaxy framework for accessible genomic data analysis. I will particularly highlight new features of Galaxy which are enabling analysis at increasingly larger scales, including UI and backend improvements, as well as other recent improvements to Galaxy.
There’s a lot more going on as well, but this track seemed particularly well suited to our readers. Have a look.
Note: OpenHelix is a part of Cambridge Healthtech Institute.