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56 results for “phenomics”
UCLA Consortium for Neuropsychiatric Phenomics LA5c Study
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Supporting Data: ontophylo: Reconstructing the evolutionary dynamics of phenomes using new ontology-informed phylogenetic methods
<p>This dataset contains all scripts and data for reproducing the analyses of the paper. The README files contain additional information.</p>
Phenome-wide association studies across large population cohorts support drug target validation
<p>Summary-level data generated by Genomics plc as presented in:<br> Diogo, D. et al. Phenome-wide association studies across large population cohorts support drug target validation. Nat. Commun. 9, 4285 (2018). https://doi.org/10.1038/s41467-018-06540-3</p> <p>If you have any questions or comments regarding these files, please contact Genomics plc at <a href="mailto:research@genomicsplc.com">research@genomicsplc.com</a></p> <p>NOTES<br> -----------------------------<br> These analyses were carried out using the interim UK Biobank imputation data release. Analyses were restricted to a subset of "white-British" unrelated samples with a maximum sample size of 112,337 individuals. </p> <p>Case control phenotypes were defined based on categorical datafields as listed in the accompanying file. <br> Quantitative phenotypes were either rank-normalised before analysis, or beta/se values were standardised after analysis using the variance of the phenotype. The normalisation value is indicated in the accompanying file.<br> <br> All analyses included Age at assessment, sex, genotyping chip, and 10 principal components as covariates. </p> <p>We used plink1.9 linear/logistic regression as appropriate. For chromosome X variants males were treated as having 0 or 2 alternative alleles. </p> <p>The results are not adjusted for genomic control.</p> <p>DATA FILE CONTENT DESCRIPTION<br> -----------------------------<br> CHR - Chromosome<br> SNP - Variant rsID<br> ALT - Alternative allele (effect allele)<br> REF - Reference Allele (non-effect allele)<br> BP - Position in base pairs (b37, 1-based)<br> NMISS - Number of samples with non-missing genotypes<br> BETA - Effect size (log odds ratio or standardised effect size)<br> SE - Standard error<br> P - P-value<br> F_MISS - genotype missing rate<br> P_hwe - Hardy-weinberg p-value<br> MAF - ALT allele frequency</p>
Prokaryote: Prokaryote Phenome Data
Phenomic data about prokaryote taxa. Data from Blank CE (2009) Data from: Not so old Archaea - the antiquity of biogeochemical processes in the archaeal domain of life. Dryad Digital Repository. <p></p>http://dx.doi.org/10.5061/dryad.71r61. Please cite the original publication and the dryad data package.<p></p>Phenomic data about prokaryote taxa. Data from Blank CE (2009) Data from: Not so old Archaea - the antiquity of biogeochemical processes in the archaeal domain of life. Dryad Digital Repository. <p></p>http://dx.doi.org/10.5061/dryad.71r61. Please cite the original publication and the dryad data package.
Data from: Applied phenomics and genomics for improving barley yellow dwarf resistance in winter wheat
<div> <div> <p>Barley yellow dwarf is one of the major viral diseases of cereals. Phenotyping barley yellow dwarf in wheat is extremely challenging due to similarities to other biotic and abiotic stresses. Breeding for resistance is additionally challenging as the wheat primary germplasm pool lacks genetic resistance, with most of the few resistance genes named to date originating from a wild relative species. The objectives of this study were to (1) evaluate the use of high-throughput phenotyping to improve barley yellow dwarf assessment; (2) identify genomic regions associated with barley yellow dwarf resistance, and (3) evaluate the ability of genomic selection models to predict barley yellow dwarf resistance. Up to 107 wheat lines were phenotyped during each of 5 field seasons under both insecticide treated and untreated plots. Across all seasons, barley yellow dwarf severity was lower within the insecticide treatment along with increased plant height and grain yield compared with untreated entries. Only 9.2% of the lines were positive for the presence of the translocated segment carrying the resis- tance gene Bdv2. Despite the low frequency, this region was identified through association mapping. Furthermore, we mapped a poten- tially novel genomic region for barley yellow dwarf resistance on chromosome 5AS. Given the variable heritability of the trait (0.211–0.806), we obtained a predictive ability for barley yellow dwarf severity ranging between 0.06 and 0.26. Including the presence or absence of Bdv2 as a covariate in the genomic selection models had a large effect for predicting barley yellow dwarf but almost no effect for other ob- served traits. This study was the first attempt to characterize barley yellow dwarf using field-high-throughput phenotyping and apply geno- mic selection to predict disease severity. These methods have the potential to improve barley yellow dwarf characterization, additionally identifying new sources of resistance will be crucial for delivering barley yellow dwarf resistant germplasm.</p> </div> </div>
Figure 6 in Genomic-Phenomic Reciprocal Illumination: Desyopone hereon gen. et sp. nov., an Exceptional Aneuretine-like Fossil Ant from Ethiopian Amber (Hymenoptera: Formicidae: Ponerinae)
Figure 6. Diagrammatic summary of male mandibular development across the Formicidae at subfamily level. Subfamilies with asterisks (*) have genera or genus groups which are diagnosable by male mandibular vestigiality. In the legend, "w" = worker/female, "m" = male. Images from the top left to the bottom right are from AntWeb [30] with the exception of the Aneuretinae (after [51]) and the †Desyopone (this study): †Sphecomyrminae (ANTWEB1032637, J. Chaul), Martialis (ANTWEB1041466, B. Boudinot), Protanilla th01 (CASENT0119776, M. Esposito), Paraponera clavata (CASENT0902407, R. Perry), Tatuidris pa01 (CASENT0102681, A. Nobile), Proceratium sc02 (CASENT0160796, E. Prado), Apomyrma zm01 (CASENT0068418, M. Esposito), Fulakora (CASENT0727874, M. Esposito), Platythyrea lamellose (CASENT0257315, B. Reynolds), Pseudoponera stigma (CASENT0178182, A. Nobile), Chrysapace sauteri (CASENT0179567, E. Prado), Myrmecia auriventris (CASENT0902789, Z. Lieberman), Nothomyrmecia macrops (CASENT0902784, Z. Lieberman), Pseudomyrmex denticollis (CASENT0173749, A. Nobile), Dolichoderus pustulatus (CASENT0103853, A. Nobile), Lasius flavus (CASENT0173150, A. Nobile), Typhlomyrmex rogenhoferi (CASENT0006787, A. Nobile), Myrmica glacialis (CASENT0862350, A. Nobile).
Figure 5 in Genomic-Phenomic Reciprocal Illumination: Desyopone hereon gen. et sp. nov., an Exceptional Aneuretine-like Fossil Ant from Ethiopian Amber (Hymenoptera: Formicidae: Ponerinae)
Figure 5. Diagrammatic representations of wing venation (top) and cell identities (bottom) based on the MAIG 6016 paratype 1 of †Desyopone hereon gen. et sp. nov. Cell names: CC = costal cell; RC1-2/SMC1 = first and second radial cells or submarginal cell 1; RC3/MC1 = third radial or first marginal cell; MC1/DC1 = first medial or first discal cell; RsC2/SMC2 = second sectorial or second submarginal cell; CuC1/SBC = first cubital or first subbasal cell; CuC2/SDC = second cubital or first subdiscal cell.
Figure 3 in Genomic-Phenomic Reciprocal Illumination: Desyopone hereon gen. et sp. nov., an Exceptional Aneuretine-like Fossil Ant from Ethiopian Amber (Hymenoptera: Formicidae: Ponerinae)
Figure 3. Amira volume renders of the raw data from the †Desyopone hereon gen. et sp. nov. holotype MAIG 6016. (A) body in lateral view; (B) mesosoma in dorsal view; (C) head, prothorax, and mesothorax in ventral view; (D) petiole in dorsal view; (E) petiole in ventral view, highlighting the petiolar tergum, laterotergites, and sternum, and the helcial tergite and sternite.
Figure 4 in Genomic-Phenomic Reciprocal Illumination: Desyopone hereon gen. et sp. nov., an Exceptional Aneuretine-like Fossil Ant from Ethiopian Amber (Hymenoptera: Formicidae: Ponerinae)
Figure 4. Volume renders of the segmented data from the head of †Desyopone hereon gen. et sp. nov., holotype MAIG 6016, showing the highly unusual mandibles. (A) full-face view; (B) ventral view; (C) dorsolateral anterior oblique view; (D) oral view. Scale bar approximate due to slightly unequal scaling of images for depiction.
Figure 1 in Genomic-Phenomic Reciprocal Illumination: Desyopone hereon gen. et sp. nov., an Exceptional Aneuretine-like Fossil Ant from Ethiopian Amber (Hymenoptera: Formicidae: Ponerinae)
Figure 1. Photograph of entire amber piece MAIG 6016, with indication of type specimens (labeled H for holotype, P1–P12 for paratypes) of †Desyopone hereon gen. et sp. nov., and with detailed views of seven of them (A–D). (A) paratype 4; (B) holotype; (C) paratypes 1–3; (D) paratypes 5–6. Scale bars: 0.5 mm.
Figure 2 in Genomic-Phenomic Reciprocal Illumination: Desyopone hereon gen. et sp. nov., an Exceptional Aneuretine-like Fossil Ant from Ethiopian Amber (Hymenoptera: Formicidae: Ponerinae)
Figure 2. Photographs of †Desyopone hereon gen. et sp. nov., MAIG 6016. (A,B) holotype, anterodorsolateral views of head and metasoma; (C) paratype 1, wing view; (D) paratype 4, wing view. AtIII/MtII: abdominal tergite III/metasomal tergite II; AsIX/MsVIII: abdominal sternite IX/metasomal sternite VIII. Note that the specimen figured in D has a duplicated crossvein 2rs-m on right fore wing. Scale bars: 0.25 mm.
Meta-analysis reveals challenges and gaps for genome-to-phenome research underpinning plant drought response.
<p>Data used to identify species occurring in hyperarid environments for analyses described in "Meta-analysis reveals challenges and gaps for genome-to-phenome research underpinning plant drought response." The "PlantsLackingHumanUse_PrelimQCd_Data.csv" contains data for all plants queried, while "HyperArid_Occurrences.csv" contains the subset of data corresponding to plants occurring in hyperarid environments.</p>
Summary statistics for: Phenome-wide analyses identify an association between the parent-of-origin effects dependent methylome and the rate of aging in humans
<p>Summary statistics of single POE-CpG based and POE-CpG co-methylation module based phenome-wide association analyses for the manuscript "Phenome-wide analyses identify an association between the parent-of-origin effects dependent methylome and the rate of aging in humans"</p>
Data from: Applied phenomics and genomics for improving barley yellow dwarf resistance in winter wheat
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Data From: TERRA-REF, An open reference data set from high resolution genomics, phenomics, and imaging sensors
<p>The ARPA-E funded TERRA-REF project is generating open-access reference datasets for the study of plant sensing, genomics, and phenomics. Sensor data were generated by a field scanner sensing platform that captures color, thermal, hyperspectral, and active flourescence imagery as well as three dimensional structure and associated environmental measurements. This dataset is provided alongside data collected using traditional field methods in order to support calibration and validation of algorithms used to extract plot level phenotypes from these datasets.</p> <p>Data were collected at the University of Arizona Maricopa Agricultural Center in Maricopa, Arizona. <br> This site hosts a large field scanner with fifteen sensors, many of which are capable of capturing mm-scale images and point clouds at daily to weekly intervals.</p> <p>These data are intended to be re-used, and are accessible as a combination of files and databases linked by spatial, temporal, and genomic information. In addition to providing open access data, the entire computational pipeline is open source, and we enable users to access high-performance computing environments.</p> <p>The study has evaluated a sorghum diversity panel, biparental cross populations, and elite lines and hybrids from structured sorghum breeding populations. <br> In addition, a durum wheat diversity panel was grown and evaluated over three winter seasons.<br> The initial release includes derived data from from two seasons in which the sorghum diversity panel was evaluated.<br> Future releases will include data from additional seasons and locations.</p> <p>The TERRA-REF reference dataset can be used to characterize phenotype-to-genotype associations, on a genomic scale, that will enable knowledge-driven breeding and the development of higher-yielding cultivars of sorghum and wheat. <br> The data is also being used to develop new algorithms for machine learning, image analysis, genomics, and optical sensor engineering.</p>
Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health
<p>This repository houses fully-adjusted methylome-wide association study (MWAS) summary statistics for 4,231 SomaScan protein measurements. These were generated as part of the study titled ‘Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health’ by Gadd <em>et al</em>. The Stratifying Resilience and Depression Longitudinally (STRADL) cohort used in this study is a subset of individuals from Generation Scotland: The Scottish Family Health Study. There were 744 individuals with complete protein and DNA methylation measurements available at 772,619 CpG probes. MWAS were performed with protein residuals as the outcome and DNA methylation as the exposure, using the Omics-data-based complex trait analysis (OSCA) software.</p> <p>Fully-adjusted models were run using M-values that were adjusted for age, sex, DNA methylation-derived immune cell estimates, depression status, DNA methylation batch and set, body mass index and a DNA methylation-derived smoking score. Protein levels were rank-based inverse normalised and scaled to have a mean of 0 and standard deviation of 1. Protein levels were residualised by age, sex, available pQTLs, technical covariates and 20 genetic principal components.</p> <p>Four of the 4,235 protein MWAS models did not converge (15509-2 - NAGLU, 15584-9 - CFHR2, 4407-10 - MST1 and 6402-8 - PILRA). Therefore, summary statistics are provided for 4,231 protein levels.</p> <p>Each protein MWAS summary statistics file has been saved with the following naming system: "MWAS_SeqId_Protein_gene.csv". For example, the protein with gene name CRYBB2 and SeqId 10000-28 has the following file name: "MWAS_10000-28_CRYBB2.csv".</p> <p>The SeqIds, UniProt codes, gene names and full UniProt names can be found in "annotation_formatted_for_paper.csv" and the full summary statistics are found within "compressed-protein-ewas.tar.gz".</p> <p>Please contact either <a href="mailto:riccardo.marioni@ed.ac.uk">riccardo.marioni@ed.ac.uk</a> or <a href="mailto:danni.gadd@ed.ac.uk">danni.gadd@ed.ac.uk</a> for any queries. All code is available at the following Github repository: <a href="https://github.com/DanniGadd/Epigenome-and-phenome-wide-study-of-brain-health-outcomes">https://github.com/DanniGadd/Epigenome-and-phenome-wide-study-of-brain-health-outcomes</a>.</p>
[DATA_SCIENCE] Interviews Plant Phenomics, 2015
<p>Here are two transcripts from a set of interviews executed by Sabina Leonelli in the fall of 2015 as part of the ERC project "The Epistemology of Data-Intensive Science", and in the context of a case study of phenotyping practices at the National Plant Phenomics Centre in Aberystwyth and collaborators. The transcripts document researchers' experience of data curation practices. Researchers have consented to have these transcripts made available as Open Data. Other interviewees did not give consent or ended up providing sensitive information in their interviews, so those transcripts cannot be made open and are held securely by the research team in Exeter. You also find the information sheet provided to interviewees, which gives you the context for this project. Further information can be found at <a href="http://www.datastudies.eu">www.datastudies.eu</a>. The transcripts have been redacted to exclude names of people who have not given consent to participate in the study, but have otherwise been left unedited and therefore contain several colloquial expressions. A paper by Sabina Leonelli which specifically makes use of these interviews will be published in 2019 in the European Journal for Philosophy of Science, under the title “What Distinguishes Data from Models?”. Freely accessible preprint here: <a href="http://philsci-archive.pitt.edu/id/eprint/15485">http://philsci-archive.pitt.edu/id/eprint/15485</a> . Several related publications can be found in Open Access formats on the project website: <a href="http://www.datastudies.eu">www.datastudies.eu</a>.</p>
A phenomics approach reveals interspecific differences in integrated developmental responses to chronic elevated temperatures
<p>Raw data for publication 'A phenomics approach reveals interspecific differences in integrated developmental responses to chronic elevated temperatures', Journal of Experimental Biology (2023) 226, jeb245612. doi:10.1242/jeb.245612.</p> <p>Developmental_Event_Timings.csv - Raw data for the timings of development of <em>Lymnaea stagnalis, Radix balthica </em>and <em>Physella acuta</em> maintained at 20 and 25C, recorded by manual observation from video of developing embryos. Data are recorded as absolute timings, and relative timings normalised between the 4-cell stage and hatching. </p> <p>EPT_Data.csv - Time series of frequency specific EPT data binned at 0.1Hz increments for embryos of <em>Lymnaea stagnalis</em>, <em>Radix balthica </em>and <em>Physella acuta </em>maintained at 20 and 25C, normalised by relative developmental time. </p> <p>EPT_data_by_physiological_window.csv - Frequency specific EPT data binned at 0.1Hz increments, and averaged across 4 key physiological windows in development (ciliary driven rotation, muscular crawling, cardiovascular function and radula function) for embryos of <em>Lymnaea stagnalis</em>, <em>Radix balthica </em>and <em>Physella acuta </em>maintained at 20 and 25C. </p> <p>Total_energy_data.csv - Time series of total energy data for embryos of <em>Lymnaea stagnalis</em>, <em>Radix balthica </em>and <em>Physella acuta </em>maintained at 20 and 25C, normalised by relative developmental time. </p>
Phenomic data-driven biological prediction of maize through field-based high throughput phenotyping integration with genomic data
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Data from: Quantifying the phenome-wide response to sex-specific selection in Drosophila melanogaster
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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.