Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sample curation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

WE-E-BRE-05: Ensemble of Graphical Models for Predicting Radiation Pneumontis Risk

Purpose: We propose a prior knowledge-based approach to construct an interaction graph of biological and dosimetric radiation pneumontis (RP) covariates for the purpose of developing a RP risk classifier. Methods: We recruited 59 NSCLC patients who received curative radiotherapy with minimum 6 month follow-up. 16 RP events was observed (CTCAE grade ≥2). Blood serum was collected from every patient before (pre-RT) and during RT (mid-RT). From each sample the concentration of the following five candidate biomarkers were taken as covariates: alpha-2-macroglobulin (α2M), angiotensin converting enzyme (ACE), transforming growth factor β (TGF-β), interleukin-6 (IL-6), and osteopontin (OPN). Dose-volumetric parameters were also included as covariates. The number of biological and dosimetric covariates was reduced by a variable selection scheme implemented by L1-regularized logistic regression (LASSO). Posterior probability distribution of interaction graphs between the selected variables was estimated from the data under the literature-based prior knowledge to weight more heavily the graphs that contain the expected associations. A graph ensemble was formed by averaging the most probable graphs weighted by their posterior, creating a Bayesian Network (BN)-based RP risk classifier. Results: The LASSO selected the following 7 RP covariates: (1) pre-RT concentration level of α2M, (2) α2M level mid- RT/pre-RT, (3) pre-RT IL6 level, (4) IL6 level mid-RT/pre-RT, (5) ACE mid-RT/pre-RT, (6) PTV volume, and (7) mean lung dose (MLD). The ensemble BN model achieved the maximum sensitivity/specificity of 81%/84% and outperformed univariate dosimetric predictors as shown by larger AUC values (0.78∼0.81) compared with MLD (0.61), V20 (0.65) and V30 (0.70). The ensembles obtained by incorporating the prior knowledge improved classification performance for the ensemble size 5∼50. Conclusion: We demonstrated a probabilistic ensemble method to detect robust associations between RP covariates and its potential to improve RP prediction accuracy. Our Bayesian approach to incorporate prior knowledge can enhance efficiency in searching of such associations from data. The authors acknowledge partial support by: 1) CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290) and 2) The Terry Fox Foundation Strategic Training Initiative for Excellence in Radiation Research for the 21st Century (EIRR21)

60 APPLIED LIFE SCIENCES↗
NASA NTRS2022

Characterization of Lunar Polar Volatiles for Curation and ISRU - Executive Summary

The goal of this project is to support lunar exploration by simulating and characterizing ice and volatile-rich materials expected to be found at the lunar poles. These materials are highly sensitive to heating, which could significantly alter their composition and prevent scientific studies on lunar samples. During FY19, we obtained materials for and designed a simulated lunar environment, within which volatile-rich simulant could be made. We also refined the procedure for moderate-fidelity lunar simulants at cryogenic temperatures. In FY20, we completed our test setup, and we can now reach cryogenic temperatures and near-lunar pressures with active compositional monitoring of volatiles in the vapor phase. For FY21, we: 1) progressed towards developing sample storage temperature requirements for volatile-rich samples by completing storage testing, along with materials testing for Artemis geologic sampling, 2) obtained instrumentation for solid sample monitoring to characterize solid species, and 3) progressed towards water extraction testing for ISRU. Our test results will directly feed into Artemis science requirements, hardware designs for sample return, vehicle requirements (HLS, Gateway, Orion), and operations planning for lunar exploration activities.

Julie L Mitchell↗
DOE OSTI2026

Database of virus genomes from ultra-deep sequencing of wastewater

Researchers at University of Missouri have conducted ultra-deep RNA sequencing of viral concentrates from wastewater (1 billion Illumina reads per sample). The resulting dataset spans 321 samples collected weekly from 11 cities between 2023-2025. As part of a tri-lab collaboration, scientists at LLNL and LANL cleaned, assembled, and annotated this metagenomic data, identifying nearly 200,000 viral genomes. Careful data curation resulted in a database containing 21,015 high-quality, near-complete viral genomes from wastewater. This database contains viruses predicted to infect a range of hosts including bacteria (most common viruses), plants (most abundant viruses), and vertebrates (rarest viruses). There are also numerous novel viruses that could not be well identified and whose host(s) are unknown. Just 7% of all genomes in the wastewater virus database had genus-level matches in the public NCBI database, and 17% matched to a recently created metagenomic virus database at that level (metaVR). The database will provide baseline information about viruses in wastewater that may be used to additional identify novel viruses during ongoing monitoring

Allen, Jonathan [Lawrence Livermore National Labor↗
NASA NTRS2014

Rapid Classification of Ordinary Chondrites Using Raman Spectroscopy

Classification of ordinary chondrites is typically done through measurements of the composition of olivine and pyroxenes. Historically, this measurement has usually been performed via electron microprobe, oil immersion or other methods which can be costly through lost sample material during thin section preparation. Raman microscopy can perform the same measurements but considerably faster and with much less sample preparation allowing for faster classification. Raman spectroscopy can facilitate more rapid classification of large amounts of chondrites such as those retrieved from North Africa and potentially Antarctica, are present in large collections, or are submitted to a curation facility by the public. With development, this approach may provide a completely automated classification method of all chondrite types.

Fries, M.↗
NASA NTRSDate not supplied

Using X-Ray Computed Tomography to Image Apollo Drive Tube 73002

The Apollo missions collected 382 kg of rock, regolith, and core samples from six locations on the Moon. Although most Apollo samples are well characterized, several types of samples remain wholly or largely unstudied since their return: unopened and/or sealed drive tube samples, samples frozen upon return, and samples stored in a He-purged environment. NASA selected nine teams to participate in the Apollo Next Generation Sample Analysis (ANGSA) Program to study representative samples from each of these categories. The first sample studied as part of the ANGSA program is drive tube 73002, a 4 cm diameter unopened (but unsealed) drive tube collected on a landslide deposit near Lara Crater at the Apollo 17 landing site. It was part of a ~60 cm long double drive tube, and the bottom half of the tube (73001)was sealed under vacuum on the Moon (and will be studied next). As part of the preliminary examination of sample 73002, the entire drive tube was imaged with a high resolution X-ray Computed Tomography (XCT) scan prior to opening and dissecting the sample. Additionally, >50 XCT scans have been made of “large” clasts (>4 mm) removed from the core as part of the ongoing dissection process. Here we will present both the whole drive tube XCT data showing the overall structure of sample 73002 prior to dissection, as well as XCT scans of individual clasts that reveal the types and abundance of different lithologies present within the drive tube. We will also discuss the utility of the scans as part of the curation and preliminary examination process, as well as the potential for future science returns from the XCT scans.

Ryan A Zeigler↗
DOE OSTI2021

National Virtual Biotechnology Laboratory: Report on Rapid R&D Solutions to the COVID-19 Crisis

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply short ages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. Within months, NVBL teams produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment (PPE), creating nearly 1,000 new jobs. They used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported U.S. Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDC), and U.S. Department of Defense (DoD) efforts to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. NVBL teams also studied how to control indoor virus movement to minimize uptake and protect human health. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development (R&D) solutions. As the fight against COVID continues, sustained efforts are needed to confront this pandemic as well as future threats. Examples include: 1) Establishing “supply chains on demand” to meet emergency production needs by leveraging the materials and manufacturing expertise of DOE national laboratories and developing advances in electronics, sensing, robotics, and automation capabilities; 2) Improving the speed and robustness of drug discovery by integrating experimental platforms with DOE’s computational and experimental user facilities, which provide unique resources to support the discovery of high-potential therapeutic agents; 3) Protecting public, environmental, and animal health by developing new testing protocols and instrumentation adaptable to diverse sample types (both physiological and environmental) to quickly detect a wide range of pathogens and monitor other biorisks; 4) Supporting near-real-time data needs of decision-makers at the local, regional, state, and national levels by advancing data curation, analysis, and modeling using artificial intelligence and new data science tools for managing and evaluating large diverse datasets; 5) Harnessing DOE’s expertise in environmental modeling to design rooms and air handling for offices, classrooms, restaurants, and other structures to minimize biorisk transmissions. Going forward, NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, the Office of Science will continue to be an integral component of agency wide efforts to prepare for and respond to biorisks and other crises.

42 ENGINEERING↗
NASA NTRS2013

Coordinated in Situ Analyses of Organic Nanoglobules in the Sutter's Mill Meteorite

The Sutter's Mill meteorite is a newly fallen carbonaceous chondrite that was collected and curated quickly after its fall. Preliminary petrographic and isotopic investigations suggest affinities to the CM2 carbonaceous chondrites. The primitive nature of this meteorite and its rapid recovery provide an opportunity to investigate primordial solar system organic matter in a unique new sample. Here we report in-situ analyses of organic nanoglobules in the Sutter's Mill meteorite using UV fluorescence imaging, Fourier-transform infrared spectroscopy (FTIR), scanning transmission electron microscopy (STEM), NanoSIMS, and ultrafast two-step laser mass spectrometry (ultra-L2MS).

Nakamura-Messenger, K.↗
DOE OSTI2016

Palliative Short-Course Radiation Therapy in Rectal Cancer: A Phase 2 Study

Purpose: The management of patients with symptomatic rectal cancer not amenable to curative treatment may be challenging. The aim of this phase 2 study was to evaluate the efficacy of short-course radiation therapy in patients with obstructing rectal cancer. Methods and Materials: Patients who were not candidates for surgical resection because of synchronous metastases, age, and/or comorbidities were considered eligible. The sample size was calculated based on the 2-stage design of Simon. Short-course radiation therapy was delivered with an isocentric 4-field box technique (total, 25 Gy; 5 fractions in 5 days). Chemotherapy was suspended during radiation treatment. Clinical outcome measures were symptomatic response rate, toxicity, colostomy-free survival, and overall survival. Results: From October 2003 to November 2012, 18 patients (median age, 77.5 years) were enrolled. The median follow-up was 11.5 months (range, 3-36 months). Four weeks after treatment, a complete response (ie, complete symptom resolution) was observed in 38.9% of patients and a partial response in 50.0% cases, whereas 11.1% had no response. The rates of reduction or resolution of pain and bleeding were 87.5% and 100%, respectively. The 1-, 2-, and 3-year colostomy-free survival rates were 100%, 71.4%, and 47.6%, respectively (median, 30 months). The 1-, 2-, and 3-year cumulative overall survival rates were 85.2%, 53%, and 39.8%, respectively (median, 25 months). No patients stopped treatment because of gastrointestinal or genitourinary toxicities: 38.9% of patients had grade 1 to 2 toxicity, and 16.7% had grade 3 toxicity. Only 1 patient had hematologic grade 2 toxicity, and 2 patients had grade 2 skin toxicity. Conclusions: Short-course radiation therapy may represent a safe and effective alternative treatment option in patients with obstructing rectal cancer not eligible for curative treatment, allowing colostomy to be avoided in a substantial proportion of patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2013

Coordinated In Situ Analyses of Organic Nanoglobules in the Sutter's Mill Meteorite

The Sutter s Mill meteorite is a newly fallen carbonaceous chondrite that was collected and curated quickly after its fall [1]. Preliminary petrographic and isotopic investigations suggest affinities to the CM2 carbonaceous chondrites. The primitive nature of this meteorite and its rapid recovery provide an opportunity to investigate primordial solar system organic matter in a unique new sample. Organic matter in primitive meteorites and chondritic porous interplanetary dust particles (CP IDPs) is commonly enriched in D/H and N-15/N-14 relative to terrestrial values [2-4]. These anomalies are ascribed to the partial preservation of presolar cold molecular cloud material [2]. Some meteorites and IDPs contain gm-size inclusions with extreme H and N isotopic anomalies [3-5], possibly due to preserved primordial organic grains. The abundance and isotopic composition of C in Sutter's Mill were found to be similar to the Tagish Lake meteorite [6]. In the Tagish Lake meteorite, the principle carriers of large H and N isotopic anomalies are sub-micron hollow organic spherules known as organic nanoglobules [7]. Organic nanoglobules are commonly distributed among primitive meteorites [8, 9] and cometary samples [10]. Here we report in-situ analyses of organic nano-globules in the Sutter's Mill meteorite using UV fluorescence imaging, Fourier-transform infrared spectroscopy (FTIR), scanning transmission electron microscopy (STEM), NanoSIMS, and ultrafast two-step laser mass spectrometry (ultra-L2MS).

Nakamura--Messenger, K.↗
NASA NTRS2015

Lunar Processing Cabinet 2.0: Retrofitting Gloveboxes into the 21st Century

In 2014, the Apollo 16 Lunar Processing Glovebox (cabinet 38) in the Lunar Curation Laboratory at NASA JSC received an upgrade including new technology interfaces. A Jacobs - Technology Innovation Project provided the primary resources to retrofit this glovebox into the 21st century. NASA Astromaterials Acquisition & Curation Office continues the over 40 year heritage of preserving lunar materials for future scientific studies in state-of-the-art facilities. This enhancement has not only modernized the contamination controls, but provides new innovative tools for processing and characterizing lunar samples as well as supports real-time exchange of sample images and information with the scientific community throughout the world.

Calaway, M. J.↗
NASA NTRS2007

Decontamination of Genesis Array Materials by UV Ozone Cleaning

Shortly after the NASA Genesis Mission sample return capsule returned to earth on September 8, 2004, the science team discovered that all nine ultra-pure semiconductor materials were contaminated with a thin molecular organic film approximately 0 to 100 angstroms thick. The organic contaminate layer, possibly a silicone, situated on the surface of the materials is speculated to have formed by condensation of organic matter from spacecraft off-gassing at the Lagrange 1 halo orbit during times of solar exposure. While the valuable solar wind atoms are safely secured directly below this organic contamination and/or native oxide layer in approximately the first 1000 angstroms of the ultra-pure material substrate, some analytical techniques that precisely measure solar wind elemental abundances require the removal of this organic contaminate. In 2005, Genesis science team laboratories began to develop various methods for removing the organic thin film without removing the precious material substrate that contained the solar wind atoms. Stephen Sestak and colleagues at Open University first experimented with ultraviolet radiation ozone (UV/O3) cleaning of several non-flight and flown Genesis silicon wafer fragments under a pure flowing oxygen environment. The UV/O3 technique was able to successfully remove organic contamination without etching into the bulk material substrate. At NASA Johnson Space Center Genesis Curation Laboratory, we have installed an UV/O3 cleaning devise in an ambient air environment to further experimentally test the removal of the organic contamination on Genesis wafer materials. Preliminary results from XPS analysis show that the UV/O3 cleaning instrument is a good non-destructive method for removing carbon contamination from flown Genesis array samples. However, spectroscopic ellipsometry results show little change in the thickness of the surface film. All experiments to date have shown UV/O3 cleaning method to be the best non-destructive method for removing organic contamination from the surface of the Genesis materials. The UV/O3 cleaning process can also clean carbon contamination to levels below non-flight standards. This can be seen by comparing sample 60260's carbon 10667 cps with non-flight Si carbon 21675 cps. Therefore, surface carbon contamination should not hinder the analysis of solar wind.

Calaway, Michael J.↗
DOE OSTI2024

Generalization Across Experimental Parameters in Neural Network Analysis of High-Resolution Transmission Electron Microscopy Datasets

Neural networks are promising tools for high-throughput and accurate transmission electron microscopy (TEM) analysis of nanomaterials, but are known to generalize poorly on data that is “out-of-distribution” from their training data. Given the limited set of image features typically seen in high-resolution TEM imaging, it is unclear which images are considered out-of-distribution from others. Here, we investigate how the choice of metadata features in the training dataset influences neural network performance, focusing on the example task of nanoparticle segmentation. We train and validate neural networks across curated, experimentally collected high-resolution TEM image datasets of nanoparticles under various imaging and material parameters, including magnification, dosage, nanoparticle diameter, and nanoparticle material. Overall, we find that our neural networks are not robust across microscope parameters, but do generalize across certain sample parameters. Additionally, data preprocessing can have unintended consequences on neural network generalization. Our results highlight the need to understand how dataset features affect deployment of data-driven algorithms.

42 ENGINEERING↗
DOE OSTI2021

Nutritional markers and proteome in patients undergoing treatment for pulmonary tuberculosis differ by geographic region

Contemporary phase 2 TB disease treatment clinical trials have found that microbiologic treatment responses differ between African versus non-African regions, the reasons for which remain unclear. Understanding host and disease phenotypes that may vary by region is important for optimizing curative treatments. We characterized clinical features and the serum proteome of phase 2 TB clinical trial participants undergoing treatment for smear positive, culture-confirmed TB, comparing host serum protein expression in clinical trial participants enrolled in African and Non-African regions. Serum samples were collected from 289 participants enrolled in the Centers for Disease Control and Prevention TBTC Study 29 (NCT00694629) at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). After a peptide level proteome analysis utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS) and subsequent statistical analysis, a total of 183 core proteins demonstrated significant differences at both baseline and at week 8 timepoints between participants enrolled from African and non-African regions. The majority of the differentially expressed proteins were upregulated in participants from the African region, and included acute phase proteins, mediators of inflammation, as well as coagulation and complement pathways. Downregulated proteins in the African population were primarily linked to nutritional status and lipid metabolism pathways. We have identified differentially expressed nutrition and lipid pathway proteins by geographic region in TB patients undergoing treatment for pulmonary tuberculosis, which appear to be associated with differential treatment responses. Future TB clinical trials should collect expanded measures of nutritional status and further evaluate the relationship between nutrition and microbiologic treatment response.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Mapping Rare Earths and Toxics in E-Waste via Hyperspectral Imaging and Machine Learning

Electronic waste (e-waste) presents a mounting challenge to environmental sustainability due to its complex composition, which includes high-value rare earth elements, hazardous organic compounds, and non-recyclable plastics. Accurate and scalable material classification is essential for enabling efficient resource recovery and safe recycling practices. This study introduces a confidence-aware classification pipeline that combines mid-infrared hyperspectral imaging (HSI), spectral angle mapping (SAM), and iterative machine learning to perform pixel-level material identification across e-waste devices. A curated spectral library encompassing artificial materials (e.g., plastic iron oxide, galvanized metals), minerals (e.g., allanite, hematite), and organic compounds (e.g., benzanthracene, toluene) was used to generate pseudo-labels, each assigned a confidence score based on SAM-derived spectral similarity. High-confidence samples from seven consumer electronics—digital cameras, keyboards, laptop fans, modems, motherboards, TV remotes, and speakers—were iteratively expanded and classified using models such as Support Vector Machine (SVM), Random Forest, Gradient Boosting Classifier, Partial Least Squares Discriminant Analysis (PLSDA) and Logistic Regression. The best-performing classifiers achieved macro F1 scores approaching 1.0. Results revealed widespread plastic content (dominated by plastic iron oxide), the presence of rare earth-bearing minerals like cerium-containing allanite, and pervasive detection of hazardous organics such as benzanthracene. Principal Component Analysis (PCA) visualizations and confusion matrices confirmed high separability and robust classification performance. This methodology enables precise, non-destructive, and scalable classification of heterogeneous e-waste streams. It supports automated, hazard-aware sorting in recycling workflows, facilitating selective recovery of critical materials and compliance with circular economy goals. The confidence-aware framework provides a foundation for real-time deployment in industrial settings, offering significant implications for smart e-recycling infrastructure and policy-driven material stewardship.

Circular economy↗
DOE OSTI2016

Genomes OnLine Database (GOLD) v.6: data updates and feature enhancements

The Genomes Online Database (GOLD) (https://gold.jgi.doe.gov) is a manually curated data management system that catalogs sequencing projects with associated metadata from around the world. In the current version of GOLD (v.6), all projects are organized based on a four level classification system in the form of a Study, Organism (for isolates) or Biosample (for environmental samples), Sequencing Project and Analysis Project. Currently, GOLD provides information for 26 117 Studies, 239 100 Organisms, 15 887 Biosamples, 97 212 Sequencing Projects and 78 579 Analysis Projects. These are integrated with over 312 metadata fields from which 58 are controlled vocabularies with 2067 terms. The web interface facilitates submission of a diverse range of Sequencing Projects (such as isolate genome, singlecell genome, metagenome, metatranscriptome) and complex Analysis Projects (such as genome from metagenome, or combined assembly from multiple Sequencing Projects). GOLD provides a seamless interface with the Integrated Microbial Genomes (IMG) system and supports and promotes the Genomic Standards Consortium (GSC) Minimum Information standards. Here, this paper describes the data updates and additional features added during the last two years.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

STARDUST Curation and Science at JSC

Dust particles released from comet 81P/Wild-2 were captured in silica aerogel on-board the STARDUST spacecraft and returned to Earth on January 15, 2006. STARDUST recovered thousands of particles ranging in size from 1 to 100 micrometers. During the six month Preliminary Examination period an international consortium of 180 scientists investigated their mineralogy/petrology, organic/inorganic chemistry, optical properties and isotopic compositions. Stardust samples are now available for research by the entire research community.

Nakamura-Messenger, K.↗
NASA NTRS2018

NASA GeneLab Project: Bridging Space Radiation Omics with Ground Studies

Accurate assessment of risk factors for long-term space missions is critical for human space exploration: therefore it is essential to have a detailed understanding of the biological effects on humans living and working in deep space. Ionizing radiation from Galactic Cosmic Rays (GCR) is one of the major risk factors factor that will impact health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. Currently there are gaps in our knowledge of the health risks associated with chronic low dose, low dose rate ionizing radiation, specifically ions associated with high (H) atomic number (Z) and energy (E). The GeneLab project (genelab.nasa.gov) aims to provide a detailed library of Omics datasets associated with biological samples exposed to HZE. The GeneLab Data System (GLDS) currently includes datasets from both spaceflight and ground-based studies, a majority of which involve exposure to ionizing radiation. In addition to detailed information for ground-based studies, we are in the process of adding detailed, curated dosimetry information for spaceflight missions. GeneLab is the first comprehensive Omics database for space related research from which an investigator can generate hypotheses to direct future experiments utilizing both ground and space biological radiation data. In addition to previously acquired data, the GLDS is continually expanding as Omics related data are generated by the space life sciences community. Here we provide a brief summary of space radiation related data available at GeneLab.

Genelab↗
DOE OSTI2021

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation

Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs). The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k -mer- and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k -mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ~5% for virome and ~75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. Furthermore, for viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ~95% (whole genomes) down to ~80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes. Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses ‘hidden’ in diverse sequence datasets.

59 BASIC BIOLOGICAL SCIENCES↗