Concept: Pipeline transport
An incremental, loosely planned development approach is often used in bioinformatic studies when dealing with custom data analysis in a rapidly changing environment. Unfortunately, the lack of a rigorous software structuring can undermine the maintainability, communicability and replicability of the process. To ameliorate this problem we propose the Leaf system, the aim of which is to seamlessly introduce the pipeline formality on top of a dynamical development process with minimum overhead for the programmer, thus providing a simple layer of software structuring.
Quantification of cellular antigens and their interactions via antibody-based detection methods are widely used in scientific research. Accurate high-throughput quantitation of these assays using general image analysis software can be time consuming and challenging, particularly when attempted by users with limited image processing and analysis knowledge. To overcome this, we have designed Andy’s Algorithms, a series of automated image analysis pipelines for FIJI, that permits rapid, accurate and reproducible batch-processing of 3,3'-diaminobenzidine (DAB) immunohistochemistry, proximity ligation assays (PLAs) and other common assays. Andy’s Algorithms incorporates a step-by-step tutorial and optimization pipeline to make batch image analysis simple for the untrained user and adaptable across laboratories. Andy’s algorithms provide a simpler, faster, standardized work flow compared to existing programs, while offering equivalent performance and additional features, in a free to use open-source application of FIJI. Andy’s Algorithms are available at GitHub, publicly accessed at https://github.com/andlaw1841/Andy-s-Algorithm .
Pipeline safety in the United States has increased in recent decades, but incidents involving natural gas pipelines still cause an average of 17 fatalities and $133 M in property damage annually. Natural gas leaks are also the largest anthropogenic source of the greenhouse gas methane (CH4) in the U.S. To reduce pipeline leakage and increase consumer safety, we deployed a Picarro G2301 Cavity Ring-Down Spectrometer in a car, mapping 5893 natural gas leaks (2.5 to 88.6 ppm CH4) across 1500 road miles of Washington, DC. The δ(13)C-isotopic signatures of the methane (-38.2‰ ± 3.9‰ s.d.) and ethane (-36.5 ± 1.1 s.d.) and the CH4:C2H6 ratios (25.5 ± 8.9 s.d.) closely matched the pipeline gas (-39.0‰ and -36.2‰ for methane and ethane; 19.0 for CH4/C2H6). Emissions from four street leaks ranged from 9200 to 38 200 L CH4 day(-1) each, comparable to natural gas used by 1.7 to 7.0 homes, respectively. At 19 tested locations, 12 potentially explosive (Grade 1) methane concentrations of 50 000 to 500 000 ppm were detected in manholes. Financial incentives and targeted programs among companies, public utility commissions, and scientists to reduce leaks and replace old cast-iron pipes will improve consumer safety and air quality, save money, and lower greenhouse gas emissions.
Next-generation sequencing (NGS) has revolutionized plant and animal research in many ways including new methods of high throughput genotyping. Genotyping-by-sequencing (GBS) has been demonstrated to be a robust and cost-effective genotyping method capable of producing thousands to millions of SNPs across a wide range of species. Undoubtedly, the greatest barrier to its broader use is the challenge of data analysis. Herein we describe a comprehensive comparison of seven GBS bioinformatics pipelines developed to process raw GBS sequence data into SNP genotypes. We compared five pipelines requiring a reference genome (TASSEL-GBS v1& v2, Stacks, IGST, and Fast-GBS) and two de novo pipelines that do not require a reference genome (UNEAK and Stacks). Using Illumina sequence data from a set of 24 re-sequenced soybean lines, we performed SNP calling with these pipelines and compared the GBS SNP calls with the re-sequencing data to assess their accuracy. The number of SNPs called without a reference genome was lower (13k to 24k) than with a reference genome (25k to 54k SNPs) while accuracy was high (92.3 to 98.7%) for all but one pipeline (TASSEL-GBSv1, 76.1%). Among pipelines offering a high accuracy (>95%), Fast-GBS called the greatest number of polymorphisms (close to 35,000 SNPs + Indels) and yielded the highest accuracy (98.7%). Using Ion Torrent sequence data for the same 24 lines, we compared the performance of Fast-GBS with that of TASSEL-GBSv2. It again called more polymorphisms (25.8K vs 22.9K) and these proved more accurate (95.2 vs 91.1%). Typically, SNP catalogues called from the same sequencing data using different pipelines resulted in highly overlapping SNP catalogues (79-92% overlap). In contrast, overlap between SNP catalogues obtained using the same pipeline but different sequencing technologies was less extensive (~50-70%).
Information about the location and magnitudes of natural gas (NG) leaks from urban distribution pipelines is important for minimizing greenhouse gas emissions and optimizing investment in pipeline management. To enable rapid collection of such data, we developed a relatively simple method using high-precision methane analyzers in Google Street View cars. Our data indicate that this automated leak survey system can document patterns in leak location and magnitude within and among cities, even without wind data. We found that urban areas with prevalent corrosion-prone distribution lines (Boston, MA, Staten Island, NY, and Syracuse, NY), leaked approximately 25-fold more methane than cities with more modern pipeline materials (Burlington, VT, and Indianapolis, IN). Although this mobile monitoring method produces conservative estimates of leak rates and leak counts, it can still help prioritize both leak repairs and replacement of leak-prone sections of distribution lines, thus minimizing methane emissions over short and long terms.
Alignment is the first step in most RNA-seq analysis pipelines, and the accuracy of downstream analyses depends heavily on it. Unlike most steps in the pipeline, alignment is particularly amenable to benchmarking with simulated data. We performed a comprehensive benchmarking of 14 common splice-aware aligners for base, read, and exon junction-level accuracy and compared default with optimized parameters. We found that performance varied by genome complexity, and accuracy and popularity were poorly correlated. The most widely cited tool underperforms for most metrics, particularly when using default settings.
Clathrate hydrates are ice-like solid substances that can form inside oil and gas pipelines and are responsible for flow blockages, sometimes leading to catastrophic failures. Minimizing hydrate formation and adhesion on pipeline surfaces can effectively address this problem. In this paper, we achieve the lowering of the adhesion of cyclopentane hydrates by promoting a cyclopentane barrier film between the hydrate and solid surface. The presence of this interfacial liquid film depends on the relative spreading of cyclopentane on the solid surface in the presence of water. We study the role of surface chemistry and surface texture on the spreading characteristics of such interfacial films and their impact on hydrate adhesion. The use of the spreading coefficients as design parameters could take us a step closer to the development of effective passive anti-hydrate surfaces.
Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets.
Oil spills from pipeline ruptures are a major source of terrestrial petroleum pollution in cold regions. However, our knowledge of the bacterial response to crude oil contamination in cold regions remains to be further expanded, especially in terms of community shifts and potential development of hydrocarbon degraders. In this study we investigated changes of microbial diversity, population size and keystone taxa in permafrost soils at four different sites along the China-Russia crude oil pipeline prior to and after perturbation with crude oil. We found that crude oil caused a decrease of cell numbers together with a reduction of the species richness and shifts in the dominant phylotypes, while bacterial community diversity was highly site-specific after exposure to crude oil, reflecting different environmental conditions. Keystone taxa that strongly co-occurred were found to form networks based on trophic interactions, that is co-metabolism regarding degradation of hydrocarbons (in contaminated samples) or syntrophic carbon cycling (in uncontaminated samples). With this study we demonstrate that after severe crude oil contamination a rapid establishment of endemic hydrocarbon degrading communities takes place under favorable temperature conditions. Therefore, both endemism and trophic correlations of bacterial degraders need to be considered in order to develop effective cleanup strategies.
This paper addresses the mechanical behavior of buried steel pipeline crossing subsidence strata. The investigation is based on numerical simulation of the nonlinear response of the pipeline-soil system through finite element method, considering large strain and displacement, inelastic material behavior of buried pipeline and the surrounding soil, as well as contact and friction on the pipeline-soil interface. Effects of key parameters on the mechanical behavior of buried pipeline were investigated, such as strata subsidence, diameter-thickness ratio, buried depth, internal pressure, friction coefficient and soil properties. The results show that the maximum strain appears on the outer transition subsidence section of the pipeline, and its cross section is concave shaped. With the increasing of strata subsidence and diameter-thickness ratio, the out of roundness, longitudinal strain and equivalent plastic strain increase gradually. With the buried depth increasing, the deflection, out of roundness and strain of the pipeline decrease. Internal pressure and friction coefficient have little effect on the deflection of buried pipeline. Out of roundness is reduced and the strain is increased gradually with the increasing of internal pressure. The physical properties of soil have a great influence on the mechanical properties of buried pipeline. The results from the present study can be used for the development of optimization design and preventive maintenance for buried steel pipelines.