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118 results for “Panel Data”
Data from: The Drosophila Genetic Reference Panel (DGRP) on locomotor activity across different environmental conditions
<p>In nature, organisms are exposed to variable and occasionally stressful environmental conditions. Responses to diurnal and seasonal fluctuations, such as temperature and food accessibility, involve adaptive behavioral and physiological changes. While much work has been done on understanding the genetic architecture and evolutionary potential of stress tolerance traits under constant thermal conditions, there has been less focus on the quantitative genetic background in variable environments. In this study, we use the <em>Drosophila</em> Genetic Reference Panel (DGRP) to investigate locomotor activity, a key behavioral trait, under variable natural thermal conditions during the summer in a temperate environment. Male flies from 100 DGRP lines were exposed to natural thermal and light conditions in <em>Drosophila</em> activity monitors across three experimental days. We found that activity was highly temperature- and time-dependent and varied between lines both within and between days. Further, we observed variation in genetic and environmental variance components, with low to moderate estimates of the heritability for locomotor activity, consistently peaking in the afternoons. Moreover, we showed that the estimated genetic correlations of locomotor activity between two time points decreased as the absolute differences in ambient temperature was increased. In conclusion, we find that the genetic background for locomotor activity is environment specific and we conclude that more variable and unpredictable future temperatures will likely have a strong impact on the evolutionary trajectories of behavioral traits in ectotherms.</p>
Data from: Phenotypic resources immortalized in a panel of wild-derived strains of five species of house mice
<p>The house mouse, <em>Mus musculus</em>, is a widely used animal model in biomedical research, with classical laboratory strains (CLS) being the most frequently employed. However, the limited genetic variability in CLS hinders their applicability in evolutionary studies. Wild-derived strains (WDS), on the other hand, provide a suitable resource for such investigations. To assess the proportion of variation added by wild progenitors, we estimated phenotypic variation in 84 WDS representing 5 species (<em>M. musculus</em>, <em>M. spretus</em>, <em>M. spicilegus</em>, <em>M. macedonicus</em>, <em>M. caroli</em>), 3 subspecies (<em>M. m. musculus</em>, <em>M. m. domesticus</em>, <em>M. m. castaneus</em>), and compared it with 5 CLS. The spectrum of WDS captures long-term mouse evolution, estimated to be over 5 million years ago since the split of <em>M. caroli</em> from the remaining mouse species. All mice are housed in a conventional breeding facility (without a nanofilter barrier or specific-pathogen free condition) at the Institute of Vertebrate Biology, Czech Academy of Sciences, in Studenec. They are maintained under standard conditions: light/dark regime of 14/10 hours, temperatures of 23 ± 1 °C during summer (April-September) and 22 ± 1 °C during winter (October-March), respectively, and relative humidity within 40-70 %. Mice have access to food pellets and tap water <em>ad libitum</em>. Further data on this mouse repository and WDS can be obtained at <a href="https://housemice.cz/en/strains/">https://housemice.cz/en/strains/</a>.</p> <p>Morphological traits were measured in 4335 mice and include body weight, spleen weight, body length, tail length, weight of both ovaries, sperm count, the weight of testes, left epididymis, and seminal vesicles. Reproductive ability was estimated in 87 WDS and 8 CLS. This dataset was obtained from 90,077 offspring born to 8,298 mothers in 17,049 litters recorded in Studenec studbooks between 2000 and 2023. Reproductive performance was characterized by litter size, newborn mortality (calculated as the proportion of stillborn or cannibalized mice across all litters), and the number of generations produced per year. We also estimated the time since a WDS was established from wild progenitors until completing 20 generations of strict brother-sister mating, i.e., the generation at which a strain of mice can be considered inbred.</p> <p>Although CLS resemble <em>M. m. domesticus</em> and<em> M. m. musculus </em>WDS, they differ from them in 8 and 11 out of 15 phenotypic traits, respectively. The data suggest that WDS can be a useful tool in evolutionary studies, providing a basis for comparative analyses with other mammal taxa, particularly classical laboratory mice. The detected stunning phenotypic variation supplemented by genetic variation have great potential for medical applications.</p>
Characterization data for the EtNAM population and Ethiopian durum wheat landraces diversity panel
<p>In smallholder, low-input farming systems diffused in the Global South, farmers select and propagate crop varieties based on their traditional knowledge and experience. A quantitative integration of their knowledge into breeding pipelines may support the sustainable intensification of local farming. This data entry combines genomics with socioeconomics to tap into traditional knowledge in smallholder farming systems, focusing on durum wheat (<em>Triticum durum </em>Desf.). Data refer to a large nested association mapping (EtNAM) population that we developed by recombining elite international breeding line with Ethiopian traditional varieties maintained by local farmers. This entry carries also molecular and phenotypic data produced on a diversity panel (DP) of Ethiopian landraces previously characterized in four year-location combinations and published in Mengistu et al 2016 (<a href="https://doi.org/10.1111/pbi.12538">https://doi.org/10.1111/pbi.12538</a>). </p> <p>EtNAM lines and DP genotypes were evaluated for agronomic performances and farmers' appreciation in multiple locations, reveailing that gender and location can influence farmers' preference and that women and men farmers can consistently identify the best durum wheat genotypes. We used this data to train a genomic selection (GS) model with farmer scores to show that their prediction accuracy over grain yield was higher than that of the benchmark GS model trained on grain yield. The data was also used in a genome wide association mapping (GWAS) and quantitative trait locus (QTL) mapping to identify genetic determinants of agronomic traits and farmer scores. Our data shows that farmers' traditional knowledge can be integrated in a quantitative framework to increase genetic gain in pre-breeding programs, supporting genomics-driven breeding for local adaptation.</p> <p>The Rdata files contain phenotypic and molecular characterization data for 1,200 recombinant inbred lines (RILs) deriving from the EtNAM and phenotypic and molecular characterization data for 400 durum wheat genotypes in the Ethiopian DP.</p>
Data from: A genotyping-in-thousands by sequencing panel to inform invasive deer management using non-invasive fecal and hair samples
<p>Studies in ecology, evolution, and conservation often rely on non-invasive samples, making it challenging to generate large amounts of high-quality genetic data for many elusive and at-risk species. We developed and optimized a Genotyping-in-Thousands by sequencing (GT-seq) panel using non-invasive samples to inform the management of invasive Sitka black-tailed deer (<em>Odocoileus hemionus sitkensis</em>) in Haida Gwaii (Canada). We validated our panel using paired high-quality tissue and non-invasive fecal and hair samples to simultaneously distinguish individuals, identify sex and reconstruct kinship among deer sampled across the archipelago, then provided a proof-of-concept application using field-collected feces on SGang Gwaay, an island of high ecological and cultural value. Genotyping success across 244 loci was high (90.3%) and comparable to that of high-quality tissue samples genotyped using restriction-site associated DNA sequencing (92.4%), while genotyping discordance between paired high-quality tissue and non-invasive samples was low (0.50%). The panel will be used to inform future invasive species operations (culls or eradications) in Haida Gwaii by providing individual and population information to inform management. More broadly, our GT-seq workflow that includes quality control analyses for targeted SNP selection and a modified protocol may be of wider utility for other studies and systems where non-invasive genetic sampling is employed.</p>
Control panel created from 30-40 Nanopore or PacBio HiFi sequencing data from the Human Pangenome Reference Consortium
<p>This is control panel for <a href="https://github.com/friend1ws/nanomonsv">nanomonsv</a> software, which is expected to exclude many false positives as well as improve computational cost. This is made by aligning 30-40 Nanopore or PacBio HiFi sequencing data from Human Pangenome Reference Consortium (HPRC) to the GRCh38 or CHM13 reference genomes with <a href="https://github.com/lh3/minimap2">minimap2</a> version 2.24.</p> <p><strong>When you use these control panels and publish, do not forget to credit to <a href="https://humanpangenome.org/data-use-protocol/">HPRC</a>!</strong></p> <div> <div> <div> <p>Reference genomes:</p> <ul> <li>GRCh38: <a href="https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/001/405/GCA_000001405.15_GRCh38/seqs_for_alignment_pipelines.ucsc_ids/GCA_000001405.15_GRCh38_no_alt_analysis_set.fna.gz">Download GRCh38</a></li> <li>CHM13: <a href="https://s3-us-west-2.amazonaws.com/human-pangenomics/T2T/CHM13/assemblies/analysis_set/chm13v2.0_maskedY_rCRS.fa.gz">Download CHM13</a> <div> <div> <div> <div> </div> </div> </div> </div> </li> </ul> </div> </div> </div>
Original Data of Paper: Novel lncRNA-panel as biomarkers for prognosis in breast cancer via Ce-RNA Network analysis
<p>Paper title: Novel lncRNA-panel as biomarkers for prognosis in breast cancer via Ce-RNA Network analysis. Our paper was submitted to PeerJ recently. This data file is the original data of this study which contains all the original data involved in this work.</p>
Panel: Dataverse Community and CoreTrustSeal: Certifying generalist data repositories
<p>CoreTrustSeal Certification is an important tool that helps researchers and practitioners evaluate the trustworthiness of a dataset and a data repository, yet its certification model can be challenging for generalist repositories to meet. This panel will discuss strategies for meeting certification standards for Trustworthy Data Repositories (TDR) across a variety of repositories with different methods of appraisal, curation, preservation, and organization. The audience will be encouraged to add to the discussion and invited to provide feedback on the concepts presented by the panelists.</p>
Data about of the performance of a building attached photovoltaic panel on different orientations_Ecuador.
<p>Data about of the performance of a building attached photovoltaic panel on different orientations_Ecuador.</p>
Data for: Russian honey bee genotype identification through enhanced marker panel set
<p>Russian honey bees (RHB) are a breeding population developed by USDA-ARS as an effort to provide Varroa-resistant honey bees to beekeepers. The selection strategy for this breeding population was the first in honey bees to incorporate genetic stock identification (GSI). The original GSI approach has been in use for over a decade, and though effective, novel technologies and analytical approaches recently developed provide an opportunity for improvement. Here we outline a novel genotyping assay that capitalizes on the markers used in the GSI as well as novel loci recently identified in a whole genome pooled study of commercial honey bee stocks. Our approach utilizes a microfluidic platform and machine learning analyses to arrive at an accurate, high throughput assay. This novel approach provides an improved tool that can be readily incorporated into breeding decisions towards healthier more productive bees.</p>
Pakistani historical wheat panel 37K SNP data
<p>A collection of 196 historical wheat cultivars of Pakistan released between 1911 to 2022 were subjected to DNA fingerprinting using 16K genotyping-by-targeted sequencing (GBTS) platform. This platform is based on NGS and the 16K probes were resequenced. The resequencing data was aligned to Chinese Spring RefSeq version 1.1 and SNPcalling was performed. This resulted in 37K mSNP (multiple SNPs) DNA fingerprinting data. This is thus far the most comprehensive DNA fingerprinting data of all released cultivars of wheat so far. This data is publically available and can be used in research and publications subject to the acknowledgement. </p>
Data from: Solar panels as novel nest sites for the European paper wasp Polistes dominula
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Data from: Time is of the essence: using archived samples to develop a GT-seq panel to preserve continuity of ongoing genetic monitoring
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Data from: Validation of grain yield QTL from soft winter wheat using a CIMMYT spring wheat panel
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Data from: RapidRat: development, validation and application of a genotyping-by-sequencing panel for rapid biosecurity and invasive species management
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Data from: The Drosophila Genetic Reference Panel (DGRP) on locomotor activity across different environmental conditions
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Data from: Preventable trauma deaths in the Western Cape of South Africa: A consensus-based panel review
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Data from: One panel to rule them all: DArTcap genotyping for population structure, historical demography, and kinship analyses, and its application to a threatened shark
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Data for: Information accessibility, accounting manipulation, and sustainable development of digital enterprises: Based on double moderating effect model and panel PSM-DID method
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Data from: multi-level determinants of land use land cover change in Tigray, Ethiopia: a mixed-effects approach using socioeconomic panel and satellite data
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Data from: Phenotypic resources immortalized in a panel of wild-derived strains of five species of house mice
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.