Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
29
datasets available to search
ShareScore release 0.9.0
Dataset results
29 results for “Complex Traits Genetics”
Genetic Architecture Reconciles Linkage and Association Studies of Complex Traits
<p>This (zipped) folder contains 3 sub-folders:</p> <p>#**********************************************************************************************************<br>The "bin" folder contains fuctions and gentic maps needed for analyes<br>bin \<br> predLink.R - function to predict linkage <br> sibREML_v0.1.1.R - function to run SibREML<br> sim-sib-array.R - script to simulate sib-pairs from parental haplotypes<br> Summarised_genetic_map_bcf.txt - genetic map per 0.5-cM long segments, based on map from bcftools <br> (BCFtools: https://samtools.github.io/bcftools/bcftools.html)<br> Summarised_genetic_map_OMNI.txt - genetic map per 0.5-cM long segments, based on OMNI map <br> (https://github.com/joepickrell/1000-genomes-genetic-maps/tree/master/interpolated_OMNI)<br>#**********************************************************************************************************</p> <p> </p> <p>#**********************************************************************************************************<br>The "SIM" folder contains the simulation pipeline (scripts 01-15) as well as IBD sharing and simulated phenotypes for Simulated sib-pairs.<br>SIM \<br> 01_sim-sib-array.sh *pre-run*<br> 02_bed_recode_bcf_map.sh *pre-run*<br> 03_make_merlin.R *pre-run*<br> 04_error_merlin.sh *pre-run*<br> 05_merlin_IBD.sh *pre-run*<br> 06_sample_causal_snps.R *pre-run*<br> 07_simulate_pheno.sh *pre-run*<br> 08_bhat_gwas.R *can be run using provided data* <br> 09_Linkage_VH.R *can be run using provided data* <br> 10_predLink.R *can be run using provided data*<br> 11_phi_hat.R *can be run using provided data*<br> 12_IBD_Mb.R *can be run using provided data*<br> 13_IBD_cM_recombrate_stratified.R *can be run using provided data*<br> 14_SibREML.R *can be run using provided data*<br> 15_SibREML_stratified_Q4.R *can be run using provided data*<br> causal_snps \ *provided causal SNPs*<br> IBD_results \ *provided IBD-probabilities for 1000 simulated sib-pairs*<br> Linkage_VH_results \ <br> pheno \ *provided simulated phenotypes (h2=1) for 8 genetic architectures*<br> Phi_hat_results.txt<br> predicted \<br> README<br> SibREML_results.txt<br> SibREML_stratified_Q4.txt</p> <p>The data can be used to run Linkage analysis, predict linkage, estimate phi_hat, <br>as well as estimate non-stratified and recombination rate stratified sib-heritability (h2_FS and c).<br>The README is provided within the folder. <br>#**********************************************************************************************************</p> <p> </p> <p>#**********************************************************************************************************<br>The "HT_BMI" folder contains data and scripts to predict linkage and estimate phi_hat for height and BMI.<br>HT_BMI \<br> 01_predLink_HT_BMI.R<br> 02_phi_hat_HT_BMI.R<br> gws_sumstats \ *provided summary GWAS summary statistics to predict linkage for height and BMI*<br> Linkage_results \ *provided linkage meta-analysis results for height and BMI from this study*<br> Phi_hat_results_HT_BMI.txt<br> PREDLINK_bmi.txt<br> PREDLINK_height.txt<br> README<br>The README is provided within the folder.<br>#**********************************************************************************************************</p> <p><strong> </strong></p>
Probabilistic inference of the genetic architecture of functional enrichment of complex traits
<p>We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only $\leq$ 10\% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32-44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having >95% probability of contributing >0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data.</p>
Trans-eQTL effects on risk of type 1 diabetes: a test of the sparse effector (omnigenic) hypothesis of complex trait genetics (supplementary data)
<p>This repository contains summary-level data generated by performing <a href="https://github.com/molepi-precmed/trans-qtls">Genomewide aggregated trans- effects (GATE) analysis</a> in case-control study of Type 1 Diabetes (T1D).</p>
Probabilistic inference of the genetic architecture of functional enrichment of complex traits
Open the record for dataset details and reuse information.
Unique genetic signatures of local adaptation over space and time for diapause, an ecologically relevant complex trait, in Drosophila melanogaster
<p>Organisms living in seasonally variable environments utilize cues such as light and temperature to induce plastic responses, enabling them to exploit favorable seasons and avoid unfavorable ones. Local adapation can result in variation in seasonal responses, but the genetic basis and evolutionary history of this variation remains elusive. Many insects, including <i>Drosophila melanogaster,</i> are able to undergo an arrest of reproductive development (diapause) in response to unfavorable conditions. In <i>D. melanogaster</i>, the ability to diapause is more common in high latitude populations, where flies endure harsher winters, and in the spring, reflecting differential survivorship of overwintering populations. Using a novel hybrid swarm-based genome wide association study, we examined the genetic basis and evolutionary history of ovarian diapause. We exposed outbred females to different temperatures and day lengths, characterized ovarian development for over 2800 flies, and reconstructed their full phased genomes. We found that diapause scored at two different developmental cutoffs has modest heritability, and we identified hundreds of SNPs associated with each of the two phenotypes. Alleles associated with one of the diapause phenotypes tend to be more common at higher latitudes, but these alleles do not show predictable seasonal variation. The collective signal of many small-effect, clinally varying SNPs can plausibly explain latitudinal phenotypic variation seen in North America. SNPs associated with diapause do not exhibit signs of recent selective sweeps, but most are segregating at relatively high frequencies in Africa, suggesting that variation in diapause relies on ancestral polymorphisms. Finally, we utilized outdoor mesocosms to track diapause under natural conditions. We found that hybrid swarms reared outdoors evolved increased propensity for diapause in late fall, whereas indoor control populations experienced no such change. Our results indicate that diapause is a complex, quantitative trait with different evolutionary patterns across time and space.</p>
Supplementary Tables for Paper "Hidden genetic regulation of human complex traits via brain isoforms"
<p>Supplementary Tables for Paper "Hidden genetic regulation of human complex traits via brain isoforms".</p>
Data from: Limits to behavioral evolution: the quantitative genetics of a complex trait under directional selection
Open the record for dataset details and reuse information.
Data from: Genetic constraints on wing pattern variation in Lycaeides butterflies: a case study on mapping complex, multifaceted traits in structured populations
Open the record for dataset details and reuse information.
Unique genetic signatures of local adaptation over space and time for diapause, an ecologically relevant complex trait, in Drosophila melanogaster
Open the record for dataset details and reuse information.
Data for "Accurate Estimation of Marker-Associated Genetic Variance and Heritability in Complex Trait Analyses"
<p>This data is associated with the manuscript titled "Accurate Estimation of Marker-Associated Genetic Variance and Heritability in Complex Trait Analyses".</p> <p>9 files are contained. These files contain the summary statistics from the linear mixed model analyses in the simulations</p> <p>data_fig1a - all data for recreating Figure 1A</p> <p>data_fig1b - all data for recreating Figure 1B</p> <p>data_fig1c - all data for recreating Figure 1C</p> <p>data_fig1d - all data for recreating Figure 1D</p> <p>data_fig1e - all data for recreating Figure 1E</p> <p>data_fig1f - all data for recreating Figure 1F</p> <p>data_fig2 - all data for recreating Figure 2</p> <p>data_fig3 - all data for recreating Figure 3</p> <p>data_fig4 - all data for recreating Figure 4</p>
Data from: Genetic dissection of complex behaviour traits in German Shepherd dogs.
A favourable genetic structure and diversity of behavioural features highlights the potential of dogs for studying the genetic architecture of behaviour traits. However, behaviours are complex traits, which have been shown to be influenced by numerous genetic and non-genetic factors, complicating their analysis. In this study, the genetic contribution to behaviour variation in German Shepherd dogs (GSDs) was analysed using genomic approaches. GSDs were phenotyped for behaviour traits using the established Canine Behavioral Assessment and Research Questionnaire (C-BARQ). Genome-wide association study (GWAS) and regional heritability mapping (RHM) approaches were employed to identify associations between behaviour traits and genetic variants, while accounting for relevant non-genetic factors. By combining these complementary methods we endeavoured to increase the power to detect loci with small effects. Several behavioural traits exhibited moderate heritabilities, with the highest identified for Human-directed playfulness, a trait characterised by positive interactions with humans. We identified several genomic regions associated with one or more of the analysed behaviour traits. Some candidate genes located in these regions were previously linked to behavioural disorders in humans, suggesting a new context for their influence on behaviour characteristics. Overall, the results support dogs as a valuable resource to dissect the genetic architecture of behaviour traits and also highlight the value of focusing on a single breed in order to control for background genetic effects and thus avoid limitations of between-breed analyses.
Data from: Integrating nonadditive genomic relationship matrices into the study of genetic architecture of complex traits
The study of genetic architecture of complex traits has been dramatically influenced by implementing genome-wide analytical approaches during recent years. Of particular interest are genomic prediction strategies which make use of genomic information for predicting phenotypic responses instead of detecting trait-associated loci. In this work, we present the results of a simulation study to improve our understanding of the statistical properties of estimation of genetic variance components of complex traits, and of additive, dominance, and genetic effects through best linear unbiased prediction methodology. Simulated dense marker information was used to construct genomic additive and dominance matrices, and multiple alternative pedigree- and marker-based models were compared to determine if including a dominance term into the analysis may improve the genetic analysis of complex traits. Our results showed that a model containing a pedigree- or marker-based additive relationship matrix along with a pedigree-based dominance matrix provided the best partitioning of genetic variance into its components, especially when some degree of true dominance effects was expected to exist. Also, we noted that the use of a marker-based additive relationship matrix along with a pedigree-based dominance matrix had the best performance in terms of accuracy of correlations between true and estimated additive, dominance, and genetic effects.
Data from: Genetic mapping of MAPK-mediated complex traits across S. cerevisiae
Signaling pathways enable cells to sense and respond to their environment. Many cellular signaling strategies are conserved from fungi to humans, yet their activity and phenotypic consequences can vary extensively among individuals within a species. A systematic assessment of the impact of naturally occurring genetic variation on signaling pathways remains to be conducted. In S. cerevisiae, both response and resistance to stressors that activate signaling pathways differ between diverse isolates. Here, we present a quantitative trait locus (QTL) mapping approach that enables us to identify genetic variants underlying such phenotypic differences across the genetic and phenotypic diversity of S. cerevisiae. Using a Round-robin cross between twelve diverse strains, we identified QTL that influence phenotypes critically dependent on MAPK signaling cascades. Genetic variants under these QTL fall within MAPK signaling networks themselves as well as other interconnected signaling pathways. Finally, we demonstrate how the mapping results from multiple strain background can be leveraged to narrow the search space of causal genetic variants.
Data from: The genetic architecture of a complex ecological trait: host plant use in the specialist moth, Heliothis subflexa
We used genetic mapping to examine the genetic architecture of differences in host plant use between two species of noctuid moths, Heliothis subflexa, a specialist on Physalis spp., and its close relative, the broad generalist H. virescens. We introgressed H. subflexa chromosomes into the H. virescens background and analyzed 1,462 backcross insects. The effects of H. subflexa-origin chromosomes were small when measured as the percent variation explained in backcross populations (0.2 to 5%), but were larger when considered in relation to the interspecific difference explained (1.5 to 165%). Most significant chromosomes had effects on more than one trait, and their effects varied between years, sexes, and genetic backgrounds. Different chromosomes could produce similar phenotypes, suggesting that the same trait might be controlled by different chromosomes in different backcross populations. It appears that many loci of small effect contribute to the use of Physalis by H. subflexa. We hypothesize that behavioral changes may have paved the way for physiological adaptation to Physalis by the generalist ancestor of H. subflexa and H. virescens.
Genetic Factors and Interrelationships for Cancer Risk-Related Behaviors and Complex Traits
ClinicalTrials.gov study NCT00001500. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Data from: Genetic dissection of complex behaviour traits in German Shepherd dogs
Open the record for dataset details and reuse information.
Data from: Genetic mapping of MAPK-mediated complex traits across S. cerevisiae
Open the record for dataset details and reuse information.
Data from: Integrating nonadditive genomic relationship matrices into the study of genetic architecture of complex traits
Open the record for dataset details and reuse information.
Data from: The genetic architecture of a complex ecological trait: host plant use in the specialist moth, Heliothis subflexa
Open the record for dataset details and reuse information.
Genetic variants affecting RNA stability influence complex traits and disease risk
GEO Series GSE276016. Homo sapiens. 36 samples. Type: Expression profiling by high throughput sequencing.
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.