Reducing the complexity of virtual machine networking

Virtualization is an enabling technology that improves scalability, reliability, and flexibility. Virtualized networking is tackled by emulating or paravirtualizing network interface cards. This approach, however, leads to complexities (implementation and management) and has to conform to some limitations imposed by the Ethernet standard. RINA turns the current approach to virtualized networking on its head: instead of emulating networks to perform inter-process communication on a single processing system, it sees networking as an extension to local inter-process communication. In this article, we show how RINA can leverage a paravirtualization approach to achieve a more manageable solution for virtualized networking. We also present experimental results performed on IRATI, the reference open source implementation of RINA, which shows the potential performance that can be achieved by deploying our solution

The Impact of Coastal Phytoplankton Blooms on Ocean-Atmosphere Thermal Energy Exchange: Evidence From a Two-Way Coupled Numerical Modeling System

A set of sensitivity experiments are performed with a two-way coupled and nested ocean-atmosphere forecasting system in order to deconvolve how dense phytoplankton stocks in a coastal embayment may impact thermal energy exchange processes. Monterey Bay simulations parameterizing solar shortwave transparency in the surface ocean as an invariant oligotrophic oceanic water type estimate consistently colder sea surface temperature (SST) than simulations utilizing more realistic, spatially varying shortwave attenuation terms based on satellite estimates of surface algal pigment concentration. These SST differences lead to an similar to 88% increase in the cumulative turbulent thermal energy transfer from the ocean to the atmosphere over the three month simulation period. The result is a warmer simulated atmospheric boundary layer with respective local air temperature differences approaching similar to 2 degrees C. This study suggests that the retention of shortwave solar flux by ocean flora may directly impact even short-term forecasts of coastal meteorological variables. Citation: Jolliff, J. K., T. A. Smith, C. N. Barron, S. deRada, S. C. Anderson, R. W. Gould, and R. A. Arnone (2012), The impact of coastal phytoplankton blooms on ocean-atmosphere thermal energy exchange: Evidence from a two-way coupled numerical modeling system, Geophys. Res. Lett., 39, L24607, doi:10.1029/2012GL053634

Reducing INDEL calling errors in whole genome and exome sequencing data

BACKGROUND: INDELs, especially those disrupting protein-coding regions of the genome, have been strongly associated with human diseases. However, there are still many errors with INDEL variant calling, driven by library preparation, sequencing biases, and algorithm artifacts. METHODS: We characterized whole genome sequencing (WGS), whole exome sequencing (WES), and PCR-free sequencing data from the same samples to investigate the sources of INDEL errors. We also developed a classification scheme based on the coverage and composition to rank high and low quality INDEL calls. We performed a large-scale validation experiment on 600 loci, and find high-quality INDELs to have a substantially lower error rate than low-quality INDELs (7% vs. 51%). RESULTS: Simulation and experimental data show that assembly based callers are significantly more sensitive and robust for detecting large INDELs (>5 bp) than alignment based callers, consistent with published data. The concordance of INDEL detection between WGS and WES is low (53%), and WGS data uniquely identifies 10.8-fold more high-quality INDELs. The validation rate for WGS-specific INDELs is also much higher than that for WES-specific INDELs (84% vs. 57%), and WES misses many large INDELs. In addition, the concordance for INDEL detection between standard WGS and PCR-free sequencing is 71%, and standard WGS data uniquely identifies 6.3-fold more low-quality INDELs. Furthermore, accurate detection with Scalpel of heterozygous INDELs requires 1.2-fold higher coverage than that for homozygous INDELs. Lastly, homopolymer A/T INDELs are a major source of low-quality INDEL calls, and they are highly enriched in the WES data. CONCLUSIONS: Overall, we show that accuracy of INDEL detection with WGS is much greater than WES even in the targeted region. We calculated that 60X WGS depth of coverage from the HiSeq platform is needed to recover 95% of INDELs detected by Scalpel. While this is higher than current sequencing practice, the deeper coverage may save total project costs because of the greater accuracy and sensitivity. Finally, we investigate sources of INDEL errors (for example, capture deficiency, PCR amplification, homopolymers) with various data that will serve as a guideline to effectively reduce INDEL errors in genome sequencing