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1,363 results for “phenotypic data”
Phenotypic differences between interfertile Chlamydomonas species- timelapse microscopy data, part 1
<p>This repository contains timelapse microscopy data of two interfertile <i>Chlamydomonas</i> algal species. The protocol to generate this data is described in the associated publication, <a href="https://doi.org/10.57844/arcadia-35f0-3e16">"Phenotypic differences between interfertile <i>Chlamydomonas</i> species"</a>, and summarized here. Cells were collected from agar plates and suspended in water, then left to sit overnight to encourage gamete formation. During this time, non-motile cells settled, allowing for the enrichment of motile cells in the supernatant. These enriched cells were then loaded onto agar microchambers (100 micron diameter and 40 micron depth) for imaging. We collected videos on a Nikon Ti2-E microscope equipped with a Photometrics Kinetix digital scMos camera. We performed differential interference contrast (DIC) imaging using a Plan Apo 10× 0.45 Air objective. We collected videos with a 5.1 ms exposure with acquisition every 50 ms for three minutes. We placed a red light filter [IR longpass, 610 nm (ThorLabs)] in the light path to maintain swimming behavior of cells. The procedure was standardized and repeated four times to ensure consistency. Timelapse data of <i>C. reinhardtii </i>or C<i>. smithii </i>cells in agar microchamber wells from experiments "1" and "2" are shared here.</p><h4>Reference</h4><p><a href="https://doi.org/10.57844/arcadia-35f0-3e16">Essock-Burns T, Garcia III G, MacQuarrie CD, Mets DG, York R. (2023). Phenotypic differences between interfertile <i>Chlamydomonas </i>species</a></p><h4>Notes</h4><p>Experiment 1, performed on 230509: This experiment was meant to include DIC timelapse data, but a DIC polarizer was not inserted during the data collection. The resulting data was effectively brightfield data.</p><p>Experiment 2, performed on 230516: DIC timelapse data of <i>Chlamydomonas</i> cells swimming in agar microchamber wells.</p><p>"Cr" indicates <i>Chlamydomonas reinhardtii</i></p><p>"Cs" indicates <i>Chlamydomonas smithii</i></p><p>Timelapse frames: 3601 frames</p><p>Frame rate: 20 frames per second (fps)</p><p>Pixel size: 0.6398 microns/pixel<br> </p>
From Pixels to Phenotypes: Integrating Image-Based Profiling with Cell Health Data Improves Interpretability
<p>Code: https://github.com/srijitseal/BioMorph_Space<br> <br> Cell Painting assays generate morphological profiles that are versatile descriptors of biological systems and have been used to predict <em>in vitro</em> and <em>in vivo</em> drug effects. However, Cell Painting features are based on image statistics, and are, therefore, often not readily biologically interpretable. In this study, we introduce an approach that maps specific Cell Painting features into the BioMorph space using readouts from comprehensive Cell Health assays. We validated that the resulting BioMorph space effectively connected compounds not only with the morphological features associated with their bioactivity but with deeper insights into phenotypic characteristics and cellular processes associated with the given bioactivity. The BioMorph space revealed the mechanism of action for individual compounds, including dual-acting compounds such as emetine, an inhibitor of both protein synthesis and DNA replication. In summary, BioMorph space offers a more biologically relevant way to interpret cell morphological features from the Cell Painting assays and to generate hypotheses for experimental validation.</p> <p> </p> <p>The following datasets are released:<br> </p> <p>Cell_Health_median_357_profiles_70_labels.csv :<br> The Cell Heath dataset for CRISPR perturbations. Contains median consensus signatures for the 357 consensus profiles (119 CRISPR perturbations × 3 cell lines) Ref: Way et al.</p> <p>Cell_Painitng_CRISPR_Perturbations_357_profiles_827_features_scaled.csv:<br> The Cell Painting dataset for CRISPR perturbations. Contains 827 morphology features (and metadata annotation) for 357 consensus profiles (119 CRISPR perturbations × 3 cell lines). Ref: Way et al.</p> <p>Cell_Painting_data_658_compounds_827_Features_scaled.csv<br> The Cell Painting dataset for compound perturbations. Contains 658 structurally unique compounds with 827 Cell Painting features. Ref: Bray et al</p> <p>Endpoints_9_Mitotox_biological_activities_658_compounds.csv<br> The biological assay activity labels for compound perturbations. Contains 658 structurally unique compounds with 9 biological activity consensus hit calls. Ref: ToxCast/MoleculeNet</p> <p>BioMoprh_pvalue_658_compunds_398_BioMorph_terms.csv:<br> The dataset of standardised BioMorph term p-values. Contains 398 BioMorph terms for the 658 compounds in the biological activity dataset. <br> <br> References: <br> Way et al. Predicting cell health phenotypes using image-based morphology profiling. Mol Biol Cell. 2021;32(9):995-1005.<br> Bray et al. A dataset of images and morphological profiles of 30 000 small-molecule treatments using the Cell Painting assay. Gigascience. 2017;6(12):1-5. <br> MoleculeNet: Wu et al. MoleculeNet: A benchmark for molecular machine learning. Chem Sci. 2018;9(2):513-530. <br> ToxCast: Exploring ToxCast Data | US EPA https://www.epa.gov/chemical-research/exploring-toxcast-data (accessed Jul 9, 2023).</p>
Data from: In vivo functional phenotypes from a computational epistatic model of evolution
<p><span>Computational models of evolution are valuable for understanding the dynamics of sequence variation, to infer phylogenetic relationships or potential evolutionary pathways, and for biomedical and industrial applications. Despite these benefits, few have validated their propensities to generate outputs with <em>in vivo </em>functionality, which would enhance their value as accurate and interpretable evolutionary algorithms. Utilizing the Hamiltonian of the joint probability of sequences in the family as fitness metric, we sampled and experimentally tested for <em>in vivo</em> beta-lactamase activity in E. coli TEM-1 variants. These variants retain family-like functionality while being more active than their WT predecessor. We found that depending on the inference method used to generate the epistatic constraints, different parameters simulate diverse selection strengths. Under weaker selection, local Hamiltonian fluctuations reliably predict relative changes to variant fitness, recapitulating neutral evolution. In this dataset, we include input datasets, simulation trajectories as well as experimental data to support the publication: "In vivo functional phenotypes from a computationa epistatic model of evolution".</span></p>
Phenotypic, weather, soil, and imputed genomic data for the apple REFPOP
<p>Supporting datasets for the article "Integrative multi-environmental genomic prediction in apple" by Jung et al. (2024)<em>.</em></p> <p>Pheno_raw.xlsx – Eleven traits were assessed during up to five years from 2018 to 2022 (Year) at up to five locations* (Country). The traits evaluated were floral emergence (Flowering_begin), flowering intensity (Flowering_intensity), harvest date (Harvest_date),<strong> </strong>total fruit weight (Fruit_weight), fruit number (Fruit_number), single fruit weight (Fruit_weight_single), titratable acidity (Acidity), soluble solids content (Sugar), fruit firmness (Firmness), red over color (Color_over), and russet frequency (Russet_freq_all).</p> <p>Weather_raw.xlsx – Hourly measurements from 2018 to 2022 (Date) of temperature (Temperature), relative humidity (Humidity), and global radiation (Radiation) were obtained at five locations* (Location).</p> <p>Soil_raw.xlsx – Soil characteristics (Variable) were measured at five locations* (Group.1) and two soil depths (Group.2) in 2016.</p> <p>SNPs_final_2022.bed, SNPs_final_2022.bim, SNPs_final_2022.fam – imputed genomic dataset of 303,239 biallelic SNPs in the PLINK format.</p> <p>*The locations correspond to Belgium (BEL), Switzerland (CHE), Spain (ESP), France (FRA) and Italy (ITA).</p>
Phenotype Driven Data Augmentation Methods for Transcriptomic Data
<p>This repository contains the data and associated results of all experiments conducted in our work "<em>Phenotype Driven Data Augmentation Methods for Transcriptomic Data</em>". In this work, we introduce two classes of phenotype driven data augmentation approaches – signature-dependent and signature-independent. The signature-dependent methods assume the existence of distinct gene signatures describing some phenotype and are simple, non-parametric, and novel data augmentation methods. The signature-independent methods are a modification of the established Gamma-Poisson and Poisson sampling methods for gene expression data. We benchmark our proposed methods against random oversampling, SMOTE, unmodified versions of Gamma-Poisson and Poisson sampling, and unaugmented data. <br> </p> <p>This repository contains data used for all our experiments. This includes the original data based off which augmentation was performed, the cross validation split indices as a json file, the training and validation data augmented by the various augmentation methods mentioned in our study, a test set (containing only real samples) and an external test set standardised accordingly with respect to each augmentation method and training data per CV split. </p> <p>The compressed files <code>5x5stratified_{x}percent.zip</code> contains data that were augmented on <code>x%</code> of the available real data. <code>brca_public.zip</code> contains data used for the breast cancer experiments. <code>distribution_size_effect.zip</code> contains data used for hyperparameter tuning the reference set size for the modified Poisson and Gamma-Poisson methods. </p> <p>The compressed file <code>results.zip</code> contains all the results from all the experiments. This includes the parameter files used to train the various models, the metrics (balanced accuracy and auc-roc) computed including p-values, as well as the latent space of train, validation and test (for the (N)VAE) for all 25 (5x5) CV splits.</p> <p><strong>PLEASE NOTE:</strong> If any part of this repository is used in any form for your work, please <strong>attribute</strong> the following, in addition to attributing the original data source - TCGA, CPTAC, GSE20713 and METABRIC, accordingly:</p> <pre>@article{janakarajan2025phenotype,<br> title={Phenotype driven data augmentation methods for transcriptomic data},<br> author={Janakarajan, Nikita and Graziani, Mara and Rodr{\'\i}guez Mart{\'\i}nez, Mar{\'\i}a},<br> journal={Bioinformatics Advances},<br> volume={5},<br> number={1},<br> pages={vbaf124},<br> year={2025},<br> publisher={Oxford University Press}<br>}</pre> <p> </p>
Genotyping and phenotyping data for Genome-wide analyses of body fat reserves in ewes
<p><strong>Among the adaptive capacities of animals, the management of energetic body reserves (BR) through the BR mobilization and accretion processes (BR dynamics, BRD) has become an increasingly valuable attribute for livestock sustainability, allowing animals to cope with more variable environments. BRD has previously been reported to be heritable in ruminants. In the present study, we conducted genome-wide studies (GWAS) in sheep to determine genetic variants associated with BRD. BR levels and BR changes over time were obtained through body condition score measurements at eight physiological stages throughout each productive cycle in Romane ewes (n=1034) and were used as phenotypes for GWAS. After quality controls and imputation, 48,513 single nucleotide polymorphisms (SNP) were included in the GWAS. Among the QTLs identified, a major QTL associated with BR levels during pregnancy and lactation was identified on chromosome 1. In this region, several significant SNPs mapped to the leptin receptor gene (LEPR), among which one SNP mapped to the coding sequence. The point mutation induces the p.P1019S substitution in the cytoplasmic domain, close to tyrosine phosphorylation sites. The frequency of the SNP associated with increased BR levels was 32%, and the LEPR genotype explained up to 5% of the variance of the trait. These results provide strong evidence for involvement of LEPR in the regulation of BRD in sheep and highlight it as a major candidate for improving adaptive capacities.</strong></p>
A case-study for improved reusability of plant phenotyping data with MIAPPE
<p>Accompanying datasets for manuscript, "A case-study for improved reusability of plant phenotyping data with MIAPPE".</p> <p>The ZIP archives in this repository contain the source files and the output files that this manuscript refers to.</p>
Data and scripts for: Genetic dissection of seasonal vegetation index dynamics in maize through aerial based high-throughput phenotyping
<p>Plant phenotyping under field conditions plays an important role in agricultural research. Efficient and accurate high-throughput phenotyping strategies enable a better connection between genotype and phenotype. Unmanned aerial vehicle-based high-throughput phenotyping platforms (UAV-HTPPs) provide novel opportunities for large-scale proximal measurement of plant traits with high efficiency, high resolution, and low cost. The objective of this study was to use time series normalized difference vegetation index (NDVI) extracted from UAV-based multispectral imagery to characterize its pattern across development and conduct genetic dissection of NDVI in a large maize population. The time series NDVI data from the multispectral sensor were obtained at 5 time points across the growing season for 1,752 diverse maize accessions with a UAV-HTPP. Cluster analysis of the acquired measurements classified 1,752 maize accessions into 2 groups with distinct NDVI developmental trends. To capture the dynamics underlying these static observations, penalized-splines (P-splines) model was used to obtain genotype-specific curve parameters. Genome-wide association study (GWAS) using static NDVI values and curve parameters as phenotypic traits detected signals significantly associated with the traits. Additionally, GWAS using the projected NDVI values from the P-splines models revealed the dynamic change of genetic effects, indicating the role of gene-environment interplay in controlling NDVI across the growing season. Our results demonstrated the utility of ultra-high spatial resolution multispectral imagery, as that acquired using a UAV-based remote sensing, for genetic dissection of NDVI.</p>
Data for the Manuscript 'Phenotypic Variation from Waterlogging in Multiple Perennial Ryegrass Varieties under Climate Change Conditions'
<p>Experimental data supporting the findings of the manuscript 'Phenotypic Variation from Waterlogging in Multiple Perennial Ryegrass Varieties under Climate Change Conditions'. This dataset will be made publicly available when the manuscript has been accepted for journal publication unless exceptional conditions become apparent. </p>
Data_Figure1(A-D)_AKR1D1 knockout mice develop a sex dependent metabolic phenotype
<p>Data of Fig1 Pannel A-D, “AKR1D1 knockout mice develop a sex dependent metabolic phenotype”</p> <p>The Dataset contains the original figure 1 (Pannel A-D) as PNG-format (10.1530JOE-21-0280_Fig1A-D.PNG). Corresponding raw from LC-MS/MS measurements are provided as one file in CSV format (31003A-179400_10.1530_JOE-21-0280_AKR1D1_SS_DVK_4_Fig1.csv), all further experiment related information (meta-data) as one file in TXT format (31003A-179400_10.1530_JOE-21-0280_AKR1D1_SS_DVK_4_Fig1_M1.txt), one file in PDF format (31003A-179400_10.1530_JOE-21-0280_AKR1D1_SS_DVK_4_Fig1_M2.pdf) and one file as CSV format (31003A-179400_10.1530_JOE-21-0280_AKR1D1_SS_DVK_4_Fig1_M3.csv).</p>
Data and Scripts from: Bayesian prediction of multivariate ecology from phenotypic data yields novel insights into the diets of extant and extinct taxa
<p>Morphology often reflects ecology, enabling the prediction of ecological roles for taxa that lack direct observations such as fossils. In comparative analyses, ecological traits, like diet, are often treated as categorical, which may aid prediction and simplify analyses but ignores the multivariate nature of ecological niches. Futhermore, methods for quantifying and predicting multivariate ecology remain rare. Here, we ranked the relative importance of 13 food items for a sample of 88 extant carnivoran mammals, and then used Bayesian multilevel modeling to assess whether those rankings could be predicted from dental morphology and body size. Traditional diet categories fail to capture the true multivariate nature of carnivoran diets, but Bayesian regression models derived from living taxa have good predictive accuracy for importance ranks. Using our models to predict the importance of individual food items, the multivariate dietary niche, and the nearest extant analogs for a set of data-deficient extant and extinct carnivoran species confirms long-standing ideas for some taxa, but yields new insights about the fundamental dietary niches of others. Our approach provides a promising alternative to traditional dietary classifications. Importantly, this approach need not be limited to diet, but serves as a general framework for predicting multivariate ecology from phenotypic traits.</p>
Data and code of "Post-trauma behavioral phenotype predicts the degree of vulnerability to fear relapse after extinction in male rats"
<p>This dataset contains behavioral and transcriptomic data, and the original code related to the following article:</p> <p>Post-trauma behavioral phenotype predicts the degree of vulnerability to fear relapse after extinction in male rats. Fanny Demars, Ralitsa Todorova, Gabriel Makdah, Antonin Forestier, Marie-Odile Krebs, Bill P Godsil, Thérèse M Jay, Sidney I Wiener, & Marco N Pompili (2022) Current Biology <em>32. https://doi.org/10.1016/j.cub.2022.05.050</em></p>
Data from: Evolution of fungal phenotypic disparity
<p><span>Organismal grade multicellularity has been achieved only in animals, plants, and fungi. All three kingdoms manifest phenotypically disparate body plans, but their evolution has only been considered in detail for animals. Here we seek to test the general relevance of hypotheses on the evolution of animal body plans by characterising the evolution of fungal phenotypic variety (disparity). The distribution of living fungal form is defined by four distinct morphotypes: flagellated, zygomycetous, sac-bearing, and club-bearing. The discontinuity between morphotypes is a consequence of the extinction of phylogenetic intermediates, indicating that a complete record of fungal disparity would present a much more homogeneous distribution of form. Fungal phenotypic variety gradually expands through time for the most part but sharply increases with the emergence of multicellular body plans. Simulations show these temporal trends to be decidedly non-random, and at least partially shaped by hierarchical contingency. Fungal phenotypic distance is decoupled from changes in gene number, genome size, and taxonomic diversity. Only differences in organismal complexity, the number of traits that constitute an organism, at the cellular and multicellular levels present a meaningful relationship with fungal disparity. Both animals and fungi exhibit a gradual increase in disparity through time, resulting in distributions of form made discontinuous by the extinction of phylogenetic intermediates. These congruences hint at a common mode of multicellular body plan evolution.</span></p>
Egg size and offspring phenotype data at early life stages in seven Arctic charr morphs
<p>Maternal effects have the potential to alter early developmental processes of offspring and contribute to adaptive diversification. Egg size is a major contributor to offspring phenotype, which can influence developmental trajectories and potential resource use. However, to what extent intraspecific variation in egg size facilitates evolution of resource polymorphism is poorly understood. We studied multiple resource morphs of Icelandic Arctic charr, ranging from an anadromous morph – with a phenotype similar to the proposed ancestral phenotype – to sympatric morphs that vary in their degree of phenotypic divergence from the ancestral anadromous morph. We characterised variation in egg size and tested whether egg size influenced offspring phenotype at early-life stages (i.e. timing of- and size at- hatching and first feeding [FF]). We predicted that egg size would differ among morphs and be less variable as morphs diverge away from the ancestral anadromous phenotype. We also predicted that egg size would correlate with offspring size and developmental timing. We found morphs had different egg size, developmental timing and size at hatching and FF. Egg size increased as phenotypic proximity to the ancestral anadromous phenotype decreased, with larger eggs generally giving rise to larger offspring, especially at FF, but egg size had no effect on developmental rate. The interaction between egg size and the environment may have a profound impact on offspring fitness, where the resulting differences in early-life history traits may act to initiate and/or maintain resource morphs diversification. </p>
Data for: Associations between leaf developmental stability, canalization and phenotypic plasticity in an architectural perspective
<p class="MsoNormal"><span>Associations between developmental stability, canalization and phenotypic plasticity have been predicted, but rarely supported by direct evidence. Architectural analysis may provide a more powerful approach to finding correlations among these mechanisms in plants. T</span><span>o investigate the relationships among the three mechanisms in architectural perspective, w</span><span>e </span><span>subjected plants of </span><em><span>Abutilon theophrasti</span></em><span> to three densities, measured and calculated </span><span>fluctuating asymmetry (FA), coefficients of variation (CV)</span><span> and </span><span>plasticity (PI) of three leaf traits, to analyze the </span><span>correlations among these variables.</span><span> As density increased, mean leaf size, petiole length and angle of most layers and mean leaf FA of some layers decreased (at both stages), CV of petiole angle increased (at day 50), and PI of petiole length and angle across all layers decreased (at day 70); leaf FA and CV of traits generally increased with higher layers at all densities. At both stages, there were more positive correlations between FA and CV at lower vs. high densities; at day 50, little correlation of plasticity with FA or CV was found; at day 70, more positive correlations between FA and PI occurred for response to high vs. low density than for response to medium vs. low density, and more positive correlations between CV and PI occurred at lower vs. high densities. Results suggested that developmental instability, decreased canalization and plasticity can be cooperative and the relationships between decreased canalization and plasticity are more likely to be positive if decreased canalization is due to vibrant growth rather than stressful effects. The relationships of plasticity with developmental instability differed from its relationship with decreased canalization in the way of variation. Decreased canalization should be more beneficial for possible plasticity in the future, while canalization may result from already-expressed plasticity.</span></p>
Phenotypic data from: from buds to shoots: insights into grapevine development from the Witch's Broom bud sport
<p><strong>Background </strong></p> <p>Bud sports occur spontaneously in plants when new growth exhibits a distinct phenotype from the rest of the parent plant. The Witch's Broom bud sport occurs occasionally in various grapevine (<em>Vitis vinifera</em>) varieties and displays a suite of developmental defects, including dwarf features and reduced fertility. While it is highly detrimental for grapevine growers, it also serves as a useful tool for studying grapevine development. We used the Witch's Broom bud sport in grapevine to understand the developmental trajectories of the bud sports, as well as the potential genetic basis. We analyzed the phenotypes of two independent cases of the Witch's Broom bud sport, in the Dakapo and Merlot varieties of grapevine, alongside wild type counterparts. To do so, we quantified various shoot traits, performed 3D X-ray Computed Tomography on dormant buds, and landmarked leaves from the samples. We also performed Illumina and Oxford Nanopore sequencing on the samples and called genetic variants using these sequencing datasets.</p> <p><strong>Results</strong></p> <p>The Dakapo and Merlot cases of Witch's Broom displayed severe developmental defects, with no fruit/clusters formed and dwarf vegetative features. However, the Dakapo and Merlot cases of Witch's Broom studied were also phenotypically different from one another, with distinct differences in bud and leaf development. We identified 968–974 unique genetic mutations in our two Witch's Broom cases that are potential causal variants of the bud sports. Examining gene function and validating these genetic candidates through PCR and Sanger-sequencing revealed one strong candidate mutation in Merlot Witch's Broom impacting the gene GSVIVG01008260001.</p> <p><strong>Conclusions</strong></p> <p>The Witch's Broom bud sports in both varieties studied had dwarf phenotypes, but the two instances studied were also vastly different from one another and likely have distinct genetic bases. Future work on Witch's Broom bud sports in grapevine could provide more insight into development and the genetic pathways involved in grapevine.</p>
Phenotype variation in Niphargus (Amphipoda: Niphargidae): possible explanations and open challenges: data and R code
<p>Data and R code for performing the analyses of phylogenetic signal presented in the manuscript titled "Phenotype variation in Niphargus (Amphipoda: Niphargidae): possible explanations and open challenges. Data contains phylogenetic tree (Delić et al., 2023) and functional trait data in the RDS format (Premate & Fišer, 2024). The R code is available in the html format.</p> <p>References/data sources:</p> <p>Delić, T., Borko, S., Premate, E., Rexhepi, B., Alther, R., Knuesel, M., ... & Altermatt, F. (2023). Evolutionary origin of morphologically cryptic species imprints co-occurrence and sympatry patterns. <em>bioRxiv</em>, 2023-09.</p> <p>Premate, E., & Fišer, C. (2024). Functional trait dataset of European groundwater Amphipoda: Niphargidae and Typhlogammaridae. <em>Scientific Data</em>, <em>11</em>(1), 188.</p>
Drosophila serrata mutation accumulation lines: Phenotypic data on survival following infection with Drosophila C virus and reproduction
<p>The impact of selection on host immune function genes has been widely documented. However, it remains essentially unknown how mutation influences the quantitative immune traits that selection acts on. Applying a classical mutation accumulation (MA) experimental design in <em>Drosophila serrata</em>, we found the mutational variation in susceptibility (median time of death, LT50) to Drosophila C virus (DCV) was of similar magnitude to that reported for intrinsic survival traits. Mean LT50 did not change as mutations accumulated, suggesting no directional bias in mutational effects. Maintenance of genetic variance in immune function is hypothesised to be influenced by pleiotropic effects on immunity and other traits that contribute to fitness. To investigate this, we assayed female reproductive output for a subset of MA lines with relatively long or short survival times under DCV infection. Longer survival time tended to be associated with lower reproductive output, suggesting that mutations affecting susceptibility to DCV had pleiotropic effects on investment in reproductive fitness. Further studies are needed to uncover the general patterns of mutational effect on immune responses and other fitness traits, and to determine how selection might typically act on new mutations via their direct and pleiotropic effects.</p>
Patients data for meta-analysis of genotype-phenotype associations in Bardet-Biedl Syndrome
<p>Data used for metaanalysis of the genotype-phenotype relationship in Bardet Biedl Syndrome.</p> <p>File "EV table 1 literature.xlsx" describes studies that were included in the metaanalysis. File "EV table 2 dataset.xlsx" contains individual patient data. Each row corresponds to a patient. If the same patient was reported in more than 1 study, their data were merged into one row. The columns are as follows:</p> <p>* source - a citation to the study the patient originated in</p> <p>* FamilyID - randomly generated ID of a family (unique over the dataset), two persons with the same FamilyID are related.</p> <p>* source case n. - A unique identifier of the patient within the study</p> <p>* gene - A gene carrying the principal BBSome related mutation</p> <p>* nucleotide change (allele 1,2) - description of the mutations in DNA individual alleles of the gene, in HGVS nomenclature</p> <p>* protein change (allele 1,2) - description of how the mutations in DNA change the resulting protein, in HGVS nomenclature</p> <p>* type of mut allele 1,2 - whether the given mutation is considered missense (MS) or large truncation (trunc)</p> <p>* mut/mut - combination of mutations for both alleles</p> <p>* additional mutations - mutations in other BBSome-related genes. Format is "gene: DNA mutation, protein mutation"</p> <p>* sex - "F" or "M" (where reported)</p> <p>* age group - age group (where reported)</p> <p>* age - age in years. Contains fractions, decimal values and "5 month"</p> <p>* RD, OBE, PD, CI, REP, REN, HEART, LIV, DD - presense or absence of phenotypes, if reported. RD – retinal dystrophy, OBE – obesity, PD – polydactyly, CI – cognitive impairment , REP – reproductive system anomalies, REN – renal anomalies, HRT – heart disease, LIV – liver anomalies, DD - Developmental delay. Values are "" (not reported), "0" (no phenotype), "1" (phenotype present), "1!" conflicting reports of phenotype in multiple studies (some patients were involved in multiple studies)</p> <p>* ethnicity - ethnicity of the patient, if reported</p> <p>* ethinc group - grouping of the ethnicities into 8 larger groups (see paper for details)</p> <p>* note - miscellanous text, in particular contains notes on patients merged from multiple studies</p> <p>====</p> <p>The protocol for this meta-analysis was pre-registered with PROSPERO (CRD42018096099).</p> <p>PubMed and Google Scholar databases were searched in May 2018 for the following keywords: [bardet-biedl syndrome AND (genotype phenotype OR cohort)]. Other suitable records were identified by snowball searching, in particular, by retrieving relevant articles from the references of the studied full-texts. In addition, all the references included in the publicly available Euro-Wabb database (<a href="https://lovd.euro-wabb.org/home.php">https://lovd.euro-wabb.org/home.php</a>) were covered. Our search was limited to the literature published in English language and covered the period from the inception of each database to the 21st of May 2018.</p>
Data and Analysis Scripts for "Drift in Individual Behavioral Phenotype as a Strategy for Unpredictable Worlds"
<p>This document contains the raw data and analysis scripts for the paper "Drift in Individual Behavioral Phenotype as a Strategy for Unpredictable Worlds", including <em>Drosophila melanogaster</em> circling and handedness behavior at multiple timepoints and across genotypes and experimental conditions manipulating serotonin. It also contains code used to run ecological simulations in the paper and the results of those simulations, as well as code to generate figures for the paper.</p>
ScienceDex guides
Understand access before you commit
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.