De novo Nanopore read quality improvement using deep learning.

BACKGROUND:Long read sequencing technologies such as Oxford Nanopore can greatly decrease the complexity of de novo genome assembly and large structural variation identification. Currently Nanopore reads have high error rates, and the errors often cluster into low-quality segments within the reads. The limited sensitivity of existing read-based error correction methods can cause large-scale mis-assemblies in the assembled genomes, motivating further innovation in this area. RESULTS:Here we developed a Convolutional Neural Network (CNN) based method, called MiniScrub, for identification and subsequent "scrubbing" (removal) of low-quality Nanopore read segments to minimize their interference in downstream assembly process. MiniScrub first generates read-to-read overlaps via MiniMap2, then encodes the overlaps into images, and finally builds CNN models to predict low-quality segments. Applying MiniScrub to real world control datasets under several different parameters, we show that it robustly improves read quality, and improves read error correction in the metagenome setting. Compared to raw reads, de novo genome assembly with scrubbed reads produces many fewer mis-assemblies and large indel errors. CONCLUSIONS:MiniScrub is able to robustly improve read quality of Oxford Nanopore reads, especially in the metagenome setting, making it useful for downstream applications such as de novo assembly. We propose MiniScrub as a tool for preprocessing Nanopore reads for downstream analyses. MiniScrub is open-source software and is available at https://bitbucket.org/berkeleylab/jgi-miniscrub

Atmospheric observations made at Oliktok Point, Alaska, as part of the Profiling at Oliktok Point to Enhance YOPP Experiments (POPEYE) campaign

Between 1 July and 30 September 2018, small unmanned aircraft systems (sUAS), tethered balloon systems (TBSs), and additional radiosondes were deployed at Oliktok Point, Alaska, to measure the atmosphere in support of the second special observing period for the Year of Polar Prediction (YOPP). These measurements, collected as part of the Profiling at Oliktok Point to Enhance YOPP Experiments (POPEYE) campaign, targeted quantities related to enhancing our understanding of boundary layer structure, cloud and aerosol properties and surface&ndash;atmosphere exchange and providing extra information for model evaluation and improvement work. Over the 3-month campaign, a total of 59 DataHawk2 sUAS flights, 52 TBS flights, and 238 radiosonde launches were completed as part of POPEYE. The data from these coordinated activities provide a comprehensive three-dimensional data set of the atmospheric state (air temperature, humidity, pressure, and wind), surface skin temperature, aerosol properties, and cloud microphysical information over Oliktok Point. These data sets have been checked for quality and submitted to the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program data archive (http://www.archive.arm.gov/discovery/, last access: July 2019) and are accessible at no cost by all registered users. The primary dataset DOIs are https://doi.org/10.5439/1418259 (DataHawk2 measurements; Atmospheric Radiation Measurement Program, 2016), https://doi.org/10.5439/1426242 (TBS measurements; Atmospheric Radiation Measurement Program, 2017) and https://doi.org/10.5439/1021460 (radiosonde measurements; Atmospheric Radiation Measurement Program, 2013a).</p

The challenges to integrating wind energy : a study of ERCOT’s ability to integrate substantial amounts of wind energy by 2030

textThe wind energy industry in the U.S. has seen robust growth within the last two decades. The amount of renewable resources available throughout the U.S. is substantial, and as renewable energy penetration approaches a significant proportion of total electricity generation, grid operators and utilities will be presented with a myriad of challenges. Such is the case in wind’ rich Texas, where the rate of wind installations surpasses every other state and rivals that of China. By the end of 2009, the ERCOT region of Texas had approximately 9000 MW installed, serving 6.5% of the annual electricity load . The intermittent nature of wind energy can place a burden on existing generators as they are increasingly relied on to provide regulation of power, frequency control and back-up energy services when wind production is low. Exacerbating the difficulty of integrating wind energy is the mismatch of wind generation and electricity demand. Although Texas is blessed with plentiful wind resources, the majority of energy produced typically occurs at night when electricity demands are low. The result is transmission congestion that prevents cost effective generators from serving load. Despite these integration difficulties, ERCOT is paving the way forward with transformative infrastructure plans and proactive rulemaking. This report provides a background on the state of the wind energy industry in the U.S., with a review of power system operation strategies and wind integration best practices. With that context, this study concludes that ERCOT’s electricity market operations, transmission plans, and Texas’ renewable energy policies will act to reasonably and reliably accommodate wind generation capacity that serves over 15% of annual load by 2030.Geological Science