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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Vulcan Digital Engineering Application

The application is being developed with the goal of preventing the entropy of all the different single purpose applications. This application utilizes a framework that enables different file formats to be read and understood through plugins dynamically loaded to the main application containing the framework. The main application provides interoperability to all the different plugins, this allows each file format to convert to every other file format that has been read. There is no theoretical limit to the number of plugins that can be used by the application. Even though the plugins may be individually written and serve a purpose like single use scripts, the plugins can only be used with the main application, this forces the application and plugins to be linked. In theory this will force better data management, or at least the bundling of the main application with the plugins.

Lehmer, JacobP↗
DOE OSTI2020

ParseGen v.1.0.0

ParseGen is a software library that helps users create software that parses, or reads and understand, text file formats. ParseGen is based on formal language theory and is aimed at helping larger software applications read input files. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. SAND2021-2714 O

Ibanez-Granados, Daniel↗
DOE OSTI2022

PIO Tools

This is a set of utilities for reading and manipulating PIO files written in python and C++. These files are intended to be building blocks for other scripts / programs that will use them to do great things. The PIO format itself is described in LA-UR-05-7425 at page 102 and embodied in code LA-CC-05-052. In addition to reading the raw PIO files, the bundled utilities will expand variable that use a compressed sparse row notation

Swaminarayan, Sriram↗
DOE OSTI2014

Meraculous2

meraculous2 is a whole genome shotgun assembler for short-reads that is capable of assembling large, polymorphic genomes with modest computational requirements. Meraculous relies on an efficient and conservative traversal of the subgraph of the k-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. Additional features include (1) handling of allelic variation using "bubble" structures within the deBruijn graph, (2) gap closing of repetitive and low quality regions using localized assemblies, and (3) an improved scaffolding algorithm that produces more complete assemblies without compromising on scaffolding accuracy

Chapman, Jarrod↗
DOE OSTI2023

LowFive v1.0

LowFive is a new data transport layer based on the HDF5 data model, for in situ workflows. Executables using LowFive can communicate in situ (using in-memory data and MPI message passing), reading and writing traditional HDF5 files to physical storage, and combining the two modes. Minimal and often no source-code modification is needed for programs that already use HDF5. LowFive maintains deep copies or shallow references of datasets, configurable by the user. More than one task can produce (write) data, and more than one task can consume (read) data, accommodating fan-in and fan-out in the workflow task graph. LowFive supports data redistribution from n producer processes to m consumer processes.

Morozov, Dmitriy↗
DOE OSTI2022

DIVA/DeviceEditor (DIVA) v6.0.0

The DIVA software interfaces a process in which researchers design their DNA with a web-based graphical user interface (DeviceEditor), submit their designs to a central queue, and a few weeks later receive their sequence-verified clonal constructs. Each researcher independently designs the DNA to be constructed with a web-based BioCAD tool, and presses a button to submit their designs to a central queue. Researchers have web-based access to their DNA design queues, and can track the progress of their submitted designs as they progress from "evaluation", to "waiting for reagents", to "in progress", to "complete". Researchers access their completed constructs through the central DNA repository. Along the way, all DNA construction success/failure rates are captured in a central database. Once a design has been submitted to the queue, a small number of dedicated staff evaluate the design for feasibility and provide feedback to the responsible researcher if the design is either unreasonable (e.g., encompasses a combinatorial library of a billion constructs) or small design changes could significantly facilitate the downstream implementation process. The dedicated staff then use DNA assembly design automation software to optimize the DNA construction process for the design, leveraging existing parts from the DNA repository where possible and ordering synthetic DNA where necessary. Once all requisite process inputs are available, the design progresses from "waiting for reagents" to "in progress" in the design queue. Human-readable and machine-parseable DNA construction protocols output by the DNA assembly design automation software are then executed by the dedicated staff exploiting lab automation devices wherever possible. Since the all employed DNA construction methods are sequence-agnostic, standardized (utilize the same enzymatic master mixes and reaction conditions), completely independent DNA construction tasks can be aggregated into the same multi-well plates and pursued in parallel. The resulting sets of cloned constructs can then be screened by high-throughput next-gen sequencing platforms for sequence correctness. A combination of long read-length (e.g., PacBio) and paired-end read platforms (e.g., Illumina) would be exploited depending the particular task at hand (e.g., PacBio might be sufficient to screen a set of pooled constructs with significant gene divergence). Post sequence verification, designs for which at least one correct clone was identified will progress to a "complete" status, while designs for which no correct clones were identified will progress to a "failure" status. Depending on the failure mode (e.g., no transformants), and how many prior attempts/variations of assembly protocol have been already made for a given design, subsequent attempts may be made or the design can progress to a "permanent failure" state. All success and failure rate information will be captured during the process, including at which stage a given clonal construction procedure failed (e.g., no PCR product) and what the exact failure was (e.g. assembly piece 2 missing). This success/failure rate data can be leveraged to refine the DNA assembly design process.

Plahar, Hector↗
DOE OSTI2025

Pxl

The code consists of several scripts. The image is fetched from a predefined URL, downloaded, and is displayed in the virtual environment at a predefined location. The image is also dynamically scaled to fit in the virtual environment depending on its size. The image is sent to have each pixel's value written to a CSV file. While the CSV is being written, a dictionary is populated with values that map each pixel to a temperature reading. The image's height, width, position and references to its corners are sent to make a button that is the same size as the image and placed right behind the image in the virtual scene. The button defines behavior that should be triggered when the user pushes the image. Unity provides visual cues that alert the user when they are about to touch something in the virtual environment. The code holds references to the cues for the left and right hands. The button queries the cue tracker and receives the position of the active cue in the form of a 3D vector. The 3D vector is compared to the bottom left corner of the image to transform the world space coordinates of the cue to the pixel space of the image. The specific pixel is approximated relative to how far left and up the user touched from the bottom left corner of the image. The approximated pixel value, which is represented as a coordinate in 2D space, is used to retrieve the temperature value associated with the approximated pixel. A window of text is then updated to display the temperature reading.

. Otis, KrystianeS [Idaho National Laboratory (INL↗
DOE OSTI2022

Single reader between-cases AUC estimator with nested data

The area under the receiver operating characteristic curve (AUC) is widely used in evaluating diagnostic performance for many clinical tasks. It is still challenging to evaluate the reading performance of distinguishing between positive and negative regions of interest (ROIs) in the nested-data problem, where multiple ROIs are nested within the cases. To address this issue, we identify two kinds of AUC estimators, within-cases AUC and between-cases AUC. We focus on the between-cases AUC estimator, since our main research interest is in patient-level diagnostic performance rather than location-level performance (the ability to separate ROIs with and without disease within each patient). Another reason is that as the case number increases, the number of between-cases paired ROIs is much larger than the number of within-cases ROIs. We provide estimators for the variance of the between-cases AUC and for the covariance when there are two readers. We derive and prove the above estimators’ theoretical values based on a simulation model and characterize their behavior using Monte Carlo simulation results. We also provide a real-data example. Moreover, we connect the distribution-based simulation model with the simulation model based on the linear mixed-effect model, which helps better understand the sources of variation in the simulated dataset.

Health Care Sciences & Services↗
DOE OSTI2014

Quality scores for 32,000 genomes

More than 80% of the microbial genomes in GenBank are of ‘draft’ quality (12,553 draft vs. 2,679 finished, as of October, 2013). In this study, we have examined all the microbial DNA sequences available for complete, draft, and Sequence Read Archive genomes in GenBank as well as three other major public databases, and assigned quality scores for more than 30,000 prokaryotic genome sequences. Scores were assigned using four categories: the completeness of the assembly, the presence of full-length rRNA genes, tRNA composition and the presence of a set of 102 conserved genes in prokaryotes. Most (~88%) of the genomes had quality scores of 0.8 or better and can be safely used for standard comparative genomics analysis. We compared genomes across factors that may influence the score. We found that although sequencing depth coverage of over 100x did not ensure a better score, sequencing read length was a better indicator of sequencing quality. With few exceptions, most of the 30,000 genomes have nearly all the 102 essential genes. The score can be used to set thresholds for screening data when analyzing “all published genomes” and reference data is either not available or not applicable. The scores highlighted organisms for which commonly used tools do not perform well. This information can be used to improve tools and to serve a broad group of users as more diverse organisms are sequenced. Finally and unexpectedly, the comparison of predicted tRNAs across 15,000 high quality genomes showed that anticodons beginning with an ‘A’ (codons ending with a ‘U’) are almost non-existent, with the exception of one arginine codon (CGU); this has been noted previously in the literature for a few genomes, but not with the depth found here.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

ATLAS: a Snakemake workflow for assembly, annotation, and genomic binning of metagenome sequence data

Background: Metagenomics and metatranscriptomics studies provide valuable insight into the composition and function of microbial populations from diverse environments, however the data processing pipelines that rely on mapping reads to gene catalogs or genome databases for cultured strains yield results that underrepresent the genes and functional potential of uncultured microbes. Recent improvements in sequence assembly methods have eased the reliance on genome databases, thereby allowing the recovery of genomes from uncultured microbes. However, configuring these tools, linking them with advanced binning and annotation tools, and maintaining provenance of the processing continues to be challenging for researchers. Results: Here we present ATLAS, a software package for customizable data processing from raw sequence reads to functional and taxonomic annotations using state-of-the-art tools to assemble, annotate, quantify, and bin metagenome and metatranscriptome data. Genome-centric resolution and abundance estimates are provided for each sample in a dataset. ATLAS is written in Python and the workflow implemented in Snakemake; it operates in a Linux environment, and is compatible with Python 3.5+ and Anaconda 3+ versions. The source code for ATLAS is freely available, distributed under a BSD-3 license. Conclusions: ATLAS provides a user-friendly, modular and customizable Snakemake workflow for metagenome and metatranscriptome data processing; it is easily installable with conda and maintained as open-source on GitHub at https://github.com/metagenome-atlas/atlas.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A comparison between whole transcript and 3’ RNA sequencing methods using Kapa and Lexogen library preparation methods

Background: 3’ RNA sequencing provides an alternative to whole transcript analysis. However, we do not know a priori the relative advantage of each method. Thus, a comprehensive comparison between the whole transcript and the 3' method is needed to determine their relative merits. To this end, we used two commercially available library preparation kits, the KAPA Stranded mRNA-Seq kit (traditional method) and the Lexogen QuantSeq 3’ mRNASeq kit (3' method), to prepare libraries from mouse liver RNA. We then sequenced and analyzed the libraries to determine the advantages and disadvantages of these two approaches. Results: We found that the traditional whole transcript method and the 3’ RNA-Seq method had similar levels of reproducibility. As expected, the whole transcript method assigned more reads to longer transcripts, while the 3' method assigned roughly equal numbers of reads to transcripts regardless of their lengths. We found that the 3’ RNA-Seq method detected more short transcripts than the whole transcript method. With regard to differential expression analysis, we found that the whole transcript method detected more differentially expressed genes, regardless of the level of sequencing depth. Conclusions: The 3’ RNA-Seq method was better able to detect short transcripts, while the whole transcript RNA-Seq was able to detect more differentially expressed.

3’ RNA-Seq↗
DOE OSTI2019

Expression profiles of cell-wall related genes vary broadly between two common maize inbreds during stem development

The cellular machinery for cell wall synthesis and metabolism is encoded by members of large multi-gene families. Maize is both a genetic model for grass species and a potential source of lignocellulosic biomass from crop residues. Genetic improvement of maize for its utility as a bioenergy feedstock depends on identification of the specific gene family members expressed during secondary wall development in stems. High-throughput sequencing of transcripts expressed in developing rind tissues of stem internodes provided a comprehensive inventory of cell wall-related genes in maize ( Zea mays , cultivar B73). Of 1239 of these genes, 854 were expressed among the internodes at =95 reads per 20 M, and 693 of them at =500 reads per 20 M. Grasses have cell wall compositions distinct from non-commelinid species; only one-quarter of maize cell wall-related genes expressed in stems were putatively orthologous with those of the eudicot Arabidopsis. Using a slope-metric algorithm, five distinct patterns for sub-sets of co-expressed genes were defined across a time course of stem development. For the subset of genes associated with secondary wall formation, fifteen sequence motifs were found in promoter regions. The same members of gene families were often expressed in two maize inbreds, B73 and Mo17, but levels of gene expression between them varied, with 30% of all genes exhibiting at least a 5-fold difference at any stage. Although presence-absence and copy-number variation might account for much of these differences, fold-changes of expression of a CADa and a FLA11 gene were attributed to polymorphisms in promoter response elements. Large genetic variation in maize as a species precludes the extrapolation of cell wall-related gene expression networks even from one common inbred line to another. Elucidation of genotype-specific expression patterns and their regulatory controls will be needed for association panels of inbreds and landraces to fully exploit genetic variation in maize and other bioenergy grass species.

09 BIOMASS FUELS↗
DOE OSTI2020

Fluorescent amplification for next generation sequencing (FA-NGS) library preparation

BACKGROUND: Next generation sequencing (NGS) has become a universal practice in modern molecular biology. As the throughput of sequencing experiments increases, the preparation of conventional multiplexed libraries becomes more labor intensive. Conventional library preparation typically requires quality control (QC) testing for individual libraries such as amplification success evaluation and quantification, none of which occur until the end of the library preparation process. RESULTS: In this study, we address the need for a more streamlined high-throughput NGS workflow by tethering real-time quantitative PCR (qPCR) to conventional workflows to save time and implement single tube and single reagent QC. We modified two distinct library preparation workflows by replacing PCR and quantification with qPCR using SYBR Green I. qPCR enabled individual library quantification for pooling in a single tube without the need for additional reagents. Additionally, a melting curve analysis was implemented as an intermediate QC test to confirm successful amplification. Sequencing analysis showed comparable percent reads for each indexed library, demonstrating that pooling calculations based on qPCR allow for an even representation of sequencing reads. To aid the modified workflow, a software toolkit was developed and used to generate pooling instructions and analyze qPCR and melting curve data. CONCLUSIONS: We successfully applied fluorescent amplification for next generation sequencing (FA-NGS) library preparation to both plasmids and bacterial genomes. As a result of using qPCR for quantification and proceeding directly to library pooling, the modified library preparation workflow has fewer overall steps. Therefore, we speculate that the FA-NGS workflow has less risk of user error. The melting curve analysis provides the necessary QC test to identify and troubleshoot library failures prior to sequencing. While this study demonstrates the value of FA-NGS for plasmid or gDNA libraries, we speculate that its versatility could lead to successful application across other library types.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Correction to: Ancient polymorphisms contribute to genome-wide variation by long-term balancing selection and divergent sorting in Boechera stricta

Following publication of the original article [1], the authors reported that the Availability of data and materials section required updating. The updated text reads as follows. The short reads of each genotype have been deposited under GenBank accession numbers SRP054739, SRP134283-SRP134373, SRP134393-SRP134433, SRP134436-SRP134479, SRP134481-SRP134572 and SRP134581-SRP134671. All SNPs used in population genetic analyses, locations of all accessions, and custom scripts are available in the Dryad Data Archive at https://doi.org/10.5061/dryad.574pc6n [66]. Seeds from these accessions are available from the Arabidopsis Biological Resource Center.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

SEPATH: benchmarking the search for pathogens in human tissue whole genome sequence data leads to template pipelines

Background: Human tissue is increasingly being whole genome sequenced as we transition into an era of genomic medicine. With this arises the potential to detect sequences originating from microorganisms, including pathogens amid the plethora of human sequencing reads. In cancer research, the tumorigenic ability of pathogens is being recognized, for example, Helicobacter pylori and human papillomavirus in the cases of gastric non-cardia and cervical carcinomas, respectively. As of yet, no benchmark has been carried out on the performance of computational approaches for bacterial and viral detection within host-dominated sequence data. Results: We present the results of benchmarking over 70 distinct combinations of tools and parameters on 100 simulated cancer datasets spiked with realistic proportions of bacteria. mOTUs2 and Kraken are the highest performing individual tools achieving median genus-level F1 scores of 0.90 and 0.91, respectively. mOTUs2 demonstrates a high performance in estimating bacterial proportions. Employing Kraken on unassembled sequencing reads produces a good but variable performance depending on post-classification filtering parameters. These approaches are investigated on a selection of cervical and gastric cancer whole genome sequences where Alphapapillomavirus and Helicobacter are detected in addition to a variety of other interesting genera. Conclusions: We provide the top-performing pipelines from this benchmark in a unifying tool called SEPATH, which is amenable to high throughput sequencing studies across a range of high-performance computing clusters. SEPATH provides a benchmarked and convenient approach to detect pathogens in tissue sequence data helping to determine the relationship between metagenomics and disease.

Viral↗
DOE OSTI2021

A gene-editing/complementation strategy for tissue-specific lignin reduction while preserving biomass yield

Lignification of secondary cell walls is a major factor conferring recalcitrance of lignocellulosic biomass to deconstruction for fuels and chemicals. Genetic modification can reduce lignin content and enhance saccharification efficiency, but usually at the cost of moderate-to-severe growth penalties. We have developed a method, using a single DNA construct that uses CRISPR–Cas9 gene editing to knock-out expression of an endogenous gene of lignin monomer biosynthesis while at the same time expressing a modified version of the gene’s open reading frame that escapes cutting by the Cas9 system and complements the introduced mutation in a tissue-specific manner. Expressing the complementing open reading frame in vessels allows for the regeneration of Arabidopsis plants with reduced lignin, wild-type biomass yield, and up to fourfold enhancement of cell wall sugar yield per plant. The above phenotypes are seen in both homozygous and bi-allelic heterozygous T1 lines, and are stable over at least four generations. The method provides a rapid approach for generating reduced lignin trees or crops with one single transformation event, and, paired with a range of tissue-specific promoters, provides a general strategy for optimizing loss-of-function traits that are associated with growth penalties. This method should be applicable to any plant species in which transformation and gene editing are feasible and validated vessel-specific promoters are available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Predicting amyloid status in corticobasal syndrome using modified clinical criteria, magnetic resonance imaging and fluorodeoxyglucose positron emission tomography

Introduction Group comparisons demonstrate greater visuospatial and memory deficits and temporoparietal-predominant degeneration on neuroimaging in patients with corticobasal syndrome (CBS) found to have Alzheimer’s disease (AD) pathology versus those with underlying frontotemporal lobar degeneration (FTLD). The value of these features in predicting underlying AD pathology in individual patients is unknown. The goal of this study is to evaluate the utility of modified clinical criteria and visual interpretations of magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) for predicting amyloid deposition (as a surrogate of Alzheimer’s disease neuropathology) in patients presenting with CBS. Methods In total, 25 patients meeting CBS core criteria underwent amyloid (Pittsburgh compound B; PIB) PET scans. Clinical records, MRI, and FDG scans were reviewed blinded to PIB results. Modified clinical criteria were used to classify CBS patients as temporoparietal variant CBS (tpvCBS) or frontal variant CBS (fvCBS). MRI and FDG-PET were classified based on the predominant atrophy/hypometabolism pattern (frontal or temporoparietal). Results A total of 9 out of 13 patients classified as tpvCBS were PIB+, compared to 2out of 12 patients classified as fvCBS ( P < 0.01, sensitivity 82%, specificity 71% for PIB+ status). Visual MRI reads had 73% sensitivity and 46% specificity for PIB+ status with moderate intra-rater reliability (Cohen’s kappa = 0.42). Visual FDG reads had higher sensitivity (91%) for PIB+ status with perfect intra-rater reliability (kappa = 1.00), though specificity was low (50%). PIB results were confirmed in all 8 patients with available histopathology (3 PIB+ with confirmed AD, 5 PIB- with FTLD). Conclusions Splitting CBS patients into frontal or temporoparietal clinical variants can help predict the likelihood of underlying AD, but criteria require further refinement. Temporoparietal-predominant neuroimaging patterns are sensitive but not specific for AD.

Neurosciences & Neurology↗
DOE OSTI2022

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

59 BASIC BIOLOGICAL SCIENCES↗