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1,981 results for “association study”
Environmental and biological data associated with captive-reared Delta Smelt Study, Sacramento-San Joaquin Delta, CA, January-March 2019
The endangered Delta Smelt Hypomesus transpacificus is an osmerid fish endemic to the upper San Francisco Estuary. A captive breeding program for the species led by the Fish Culture and Conservation Laboratory (FCCL), University of California, Davis, began in 1996 to create a refuge population. In order to better understand how captive Delta Smelt would fare in conditions outside of the hatchery, we placed captive-reared fish in enclosures in the Sacramento San-Joaquin Delta, and evaluated their ability to survive, feed, and maintain condition. Fish were acclimated in the hatchery at FCCL, tagged, swabbed, weighed, measured, and transferred to enclosures in the field. There were three types of enclosures (n=2 for each type), varying in mesh size and wrap condition. In January 2019, 384 adult Delta Smelt (243 days post hatch) were transferred to enclosures in Rio Vista. In February 2019, 360 adult Delta Smelt (278 days post hatch) were transferred to enclosures in the Deepwater Shipping Channel. For each deployment, fish remained in enclosures for approximately one month, then were retrieved from enclosures, euthanized, identified, weighed and measured. A subset were also analyzed for diet contents. During the one-month long deployments, cages were checked for biofouling, damage, and dead fish, and water quality measurements and zooplankton samples were collected.
Data associated with the 2019 Freshwater Oil Spill Remediation Study (FOReSt) assessing the use of enhanced Monitored Natural Recovery (eMNR) and shoreline washing agent (SWA) of diluted bitumen spills conducted in shoreline enclosures at the IISD Experimental Lakes Area, ON, Canada from 2019 to 2020
The following package includes data from the 2019 Freshwater Oil spill Remediation Study (FOReSt) at the IISD Experimental Lakes Area studying the use of enhanced monitored natural recovery (eMNR) and shoreline washing agent (SWA) as a secondary remediation method for diluted bitumen spills in freshwater shoreline enclosures. This package includes data tables on polycyclic aromatic compound chemistry in water and sediments, basic water quality, nutrient chemistry, and tritium chemistry monitored in the experimental and reference enclosures, and lake reference sites over the duration of the study. Data included in this package was first collected and used in the paper by Palace et al., titled Polycyclic aromatic compounds in freshwater ecosystems following non-invasive remediation of controlled diluted bitumen spills: The Freshwater Oil Spill Remediation Study (FOReSt) at the Experimental Lakes Area, Canada.
Associated data from: An end-to-end workflow to study newly synthesized mRNA following rapid protein depletion in Saccharomyces cerevisiae
<p>This dataset includes two custom BED files described in "An end-to-end workflow to study newly synthesized mRNA following rapid protein depletion in <em>Saccharomyces cerevisiae</em>" (Ridenour and Donczew, submitted), which were used to define counting windows for processing SLAM-seq data in SLAM-DUNK (version 0.4.3) [1]. The BED files contain all annotated open reading frames (ORFs) in the<em> Saccharomyces cerevisiae</em> genome or the <em>Schizosaccharomyces</em><em> pombe</em> genome and were created using BEDOPS (version 2.4.3) [2]. All ORFs were then extended 250 bp beyond their stop position to capture 3′ untranslated regions (UTRs) using SAMtools (version 1.14) [3] and BEDTools (version 2.30.0) [4]. The reference genome annotations for <em>S. cerevisiae</em> strain S288C (version R64-3-1, RefSeq Assembly GCF_000146045.2) and <em>S. pombe</em> strain 972h- (version ASM294v2, RefSeq Assembly GCF_000002945.1) were retrieved from the NCBI Datasets repository. The <em>S. cerevisiae </em>chromosome names were modified to reflect standard nomenclature (https://www.yeastgenome.org/).</p>
Genome-wide association study suggests that variation at the RCOR1 locus is associated with tinnitus in UK Biobank
<p>The dataset contains results of a genome-wide association studies for age-related hearing impairment (ARHI)-related traits as described in the following publication:<br> Wells, H.R.R., Abidin, F.N.Z., Freidin, M.B. et al. Genome-wide association study suggests that variation at the RCOR1 locus is associated with tinnitus in UK Biobank. Sci Rep 11, 6470 (2021). https://doi.org/10.1038/s41598-021-85871-6</p>
Summary statistics accompanying the article "Genome-wide association study of the human brain functional connectome reveals strong vascular component underlying global network efficiency" in Scientific Reports (2022)
<p>Summary statistics for genome-wide association studies reported in:</p> <p>Bell, S., Tozer, D.J., & Markus H.S. (2022). Genome-wide association study of the human brain functional connectome reveals strong vascular component underlying global network efficiency. <em>Scientific Reports</em>, DOI: <a href="https://dx.doi.org/10.1038/s41598-022-19106-7">10.1038/s41598-022-19106-7</a>. </p> <p><strong>Abstract</strong></p> <p>Complex brain networks play a central role in integrating activity across the human brain, and such networks can be identified in the absence of any external stimulus. We performed 10 genome-wide association studies of resting state network measures of intrinsic brain activity in up to 36,150 participants of European ancestry in the UK Biobank. We found that the heritability of global network efficiency was largely explained by blood oxygen level-dependent (BOLD) resting state fluctuation amplitudes (RSFA), which are thought to reflect the vascular component of the BOLD signal. RSFA itself had a significant genetic component and we identified 24 genomic loci associated with RSFA, 157 genes whose predicted expression correlated with it, and 3 proteins in the dorsolateral prefrontal cortex and 4 in plasma. We observed correlations with cardiovascular traits, and single-cell RNA specificity analyses revealed enrichment of vascular related cells. Our analyses also revealed a potential role of lipid transport, store-operated calcium channel activity, and inositol 1,4,5-trisphosphate binding in resting-state BOLD fluctuations. We conclude that that the heritability of global network efficiency is largely explained by the vascular component of the BOLD response as ascertained by RSFA, which itself has a significant genetic component.</p> <p> </p> <p>Further information on the files uploaded here can be found in the README. Users interested in bulk downloading these summary statistics may find <a href="https://github.com/dvolgyes/zenodo_get">zenodo_get</a> helpful.</p>
Genome-wide association study of full body nevus count in the Brisbane Twin Nevus Study (BTNS)
<p>The project uses the Brisbane Twin Nevus Study (BTNS) (N=3863)) to compare nevus counts on different anatomical sites to assess which anatomical site serves as best proxy for counting nevi on the whole body.In the project, a GWAS of nevus count on the whole body and GWAS of nevus count on the outer arm are performed.Here is the GWAS of total nevus count.</p> <p>Sample: GWAS analysis only includes samples of European ancestry. total nevus count were counted by trained research nurse.</p> <p>Genotype: All genotypes were imputed to a human haplotype map (HapMap) reference panel. Genome-wide association analyses were performed using Genome-wide Efficient Mixed model Association (GEMMA), which can account for genetically related individuals such as twins and siblings. Sex, age, age2, sex*age, sex*age2, sunburn, BSA, sun exposed hours weighted by UV index and 5 PCs, additionally two batch effect variables; were included as covariates. SNP imputation quality filter retained SNP with an INFO > 0.3. minor allele frequency frequency filter was applied to retain SNP MAF > 0.1</p> <p>Columns include:</p> <p>CHR: Chromosome</p> <p>BP: Base pair</p> <p>SNP: rsID</p> <p>A1: Effect allele</p> <p>A2: Non-effect allele</p> <p>A1FQ: Effect allele frequency</p> <p>HWE: Hardy-Weinberg Equilibrium</p> <p>BETA: Effect estimate (of effect allele_</p> <p>SEB: Standard error of beta</p> <p>PRB: P value</p> <p>N: Per SNP sample size</p>
Sherbo et al. 2023 Data Package. Data associated with study assessing effects of dissolved organic matter on phytoplankton productivity in boreal lakes. The majority of data was collected in 2018 at the IISD Experimental Lakes Area in Northwestern Ontario
Allochthonous dissolved organic matter (DOM) structures many physical, chemical, and biological properties of lakes, including key variables that control productivity at the base of freshwater food webs. We examined phytoplankton biomass and productivity and their drivers, across eight pristine boreal lakes with DOM ranging from 3.5 to 9.5 mg DOC L-1. Increases in DOM were associated with significant increases in epilimnetic nitrogen, phosphorus and chlorophyll a (Chl a) concentrations suggesting that nutrients associated with DOM stimulate phytoplankton biomass and productivity. Such results were misleading; there was no significant relationship between Chl a and phytoplankton biomass measured via microscopy, and results did not incorporate the effects of DOM on thermocline and euphotic depth. Chl a:biomass and Chl a: carbon ratios indicated that increases in Chl a with DOM were driven by photo-acclimation to declining light availability. Increases. Further, increases in DOM led to large declines in thermocline (~50 %) and euphotic (~75 %) depths, and depth-integrated phytoplankton biomass and primary production (~70 %).
Crossreactive probes on Illumina DNA methylation arrays: a large study on ALS shows that a cautionary approach is warranted in interpreting epigenome-wide association studies
<p>Data corresponding to the paper "Crossreactive probes on Illumina DNA methylation arrays: a large study on ALS shows that a cautionary approach is warranted in interpreting epigenome-wide association studies."<br> <br> Corresponding scripts can be found at: <a href="https://github.com/pjhop/dnamarray_crossreactivity">https://github.com/pjhop/dnamarray_crossreactivity</a><br> All downstream analyses in <a href="https://github.com/pjhop/dnamarray_crossreactivity/blob/master/analysis/c9_analysis.Rmd">c9_analysis.Rmd</a> and in<a href="https://github.com/pjhop/dnamarray_crossreactivity/blob/master/analysis/supplementary_note.Rmd"> supplementary_note.Rmd</a> can be reproduced using the deposited data as follows:</p> <ul> <li>Clone the dnamarray_crossreactivity repository: < git clone https://github.com/pjhop/dnamarray_crossreactivity.git ></li> <li>Download the data ('data.zip') and place it in the 'dnamarray_crossreactivity' folder.</li> <li>Unzip the data.zip folder</li> </ul> <p>Scripts used to generate the data in each subdirectory can be found at:</p> <ul> <li>data/processed/c9_matches/: <a href="https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/c9_matches">https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/c9_matches</a></li> <li>data/output/ewas/: <a href="https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/ewas">https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/ewas</a></li> <li>data/output/figs/: empty folder, running 'c9_analysis.Rmd' will save figures here.</li> <li>data/misc/: <a href="https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/other">https://github.com/pjhop/dnamarray_crossreactivity/tree/master/analysis/other</a></li> <li>data/extdata: <ul> <li>Zhou <em>et al.</em> annotations (EPIC.hg19.manifest.tsv.gz, HM450.hg19.manifest.pop.tsv.gz, HM450.hg19.manifest.tsv.gz) were downloaded from: <a href="https://zwdzwd.github.io/InfiniumAnnotation">https://zwdzwd.github.io/InfiniumAnnotation</a> (downloaded at 17/09/2020)</li> <li>Naeem <em>et al.</em><em> </em>data (12864_2013_7006_MOESM2_ESM.csv) was downloaded from: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3943510/">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3943510/</a></li> <li>Chen <em>et al.</em> data (48639-non-specific-probes-Illumina450k.xlsx) was downloaded from <a href="https://github.com/Jfortin1/funnorm_repro/blob/master/bad_probes/48639-non-specific-probes-Illumina450k.xlsx">https://github.com/Jfortin1/funnorm_repro/blob/master/bad_probes/48639-non-specific-probes-Illumina450k.xlsx</a></li> <li>The anno_450k.txt.gz and anno_EPIC.txt.gz are subsets of the annotation files included in the following package respectively: <a href="https://bioconductor.org/packages/release/data/annotation/html/IlluminaHumanMethylation450kanno.ilmn12.hg19.html">https://bioconductor.org/packages/release/data/annotation/html/IlluminaHumanMethylation450kanno.ilmn12.hg19.html</a> and <a href="https://bioconductor.org/packages/release/data/annotation/html/IlluminaHumanMethylationEPICanno.ilm10b2.hg19.html">https://bioconductor.org/packages/release/data/annotation/html/IlluminaHumanMethylationEPICanno.ilm10b2.hg19.html</a></li> </ul> </li> <li> data/genome_bs: Scripts used to generate these data can be found at <a href="https://github.com/pjhop/DNAmCrosshyb/blob/master/data-raw/bisulfite_convert_hg19.R">https://github.com/pjhop/DNAmCrosshyb/blob/master/data-raw/bisulfite_convert_hg19.R</a> and <a href="https://github.com/pjhop/DNAmCrosshyb/blob/master/data-raw/bisulfite_convert_hg38.R">https://github.com/pjhop/DNAmCrosshyb/blob/master/data-raw/bisulfite_convert_hg38.R</a> .</li> <li> data/raw: Individual-level data is available upon access at: <a href="https://ega-archive.org/studies/EGAS00001004587">https://ega-archive.org/studies/EGAS00001004587</a></li> </ul>
General practice characteristics associated with life expectancy of practice populations: a cross-sectional study
<p>The dataset was used to investgate features of general practice associated with life expectancy of general practice populations in England for the period 2015-2019.</p>
Flood Hazard Maps and Associated Data for Case Study: Funding rules that promote equity in climate adaptation outcomes
<p>Inundation grids for multiple return periods and multiple scenarios. Please see the underlying study for more details about the methods. The data here can be reproduced following the code and instructions at this repository: https://github.com/CoRE-Lab-UCF/Pollack_et_al_2024/tree/main. Also available here: https://doi.org/10.5281/zenodo.14515896. </p>
NanoString dataset for study: Impairment of cancer-associated fibroblasts promotes CD8+ T cell infiltration and enhances sensitivity to immune checkpoint blockade
<p>Pre-processed NanoString mRNA abundance data and associated sample sheet for study:</p> <p>Impairment of cancer-associated fibroblasts promotes CD8+ T cell infiltration and enhances sensitivity to immune checkpoint blockade</p>
False discovery rate calculations for genome-wide association study of reproductive fitness in Drosophila melanogaster (Sussex LHM sample)
<p>R code and results of applying false discovery (FDR) rate calculations to establish statistical signficance in a genome-wide association study of reproductive fitness in Drosophila melanogaster. Phenotype values were generated on hemiclone female and male lines from an outbred, laboratory adapted population. Thus, GWAS were previously performed seperately on the phenotype values for each sex, and also using a bivariate GWAS implemented in the R package multiPhen.</p> <p>FDR calculations were performed using the R package 'fdrtool' on all SNPs, and on LD-independent SNPs, the latter of which was used to determine p-value thresholds for genome-wide significance when all SNPs were considered.</p> <p>This version differs from the original in that: i) Some gene positions/names have been reassigned for accuaracy in the input data. ii) A file containing the p-value thresholds corresponding to an FDR of 0.1 has been added. The 95% credible intervals for each SNP association have been added to the results data files.</p>
A longitudinal study of the associations of children's body mass index and physical activity with blood pressure – dataset
<p>B-Proact1v is a longitudinal study examining changes in children’s physical activity and sedentary behaviours as they progress through primary school. In 2012-2013, 1299 Year 1 children (median age: 6 years) were recruited from 57 schools in greater Bristol, UK (total number of eligible children: 2600; recruitment rate: 50.0%). Following this, data were collected from 1223 Year 4 children (median age: 9 years) from 47 of the original schools between March 2015 and July 2016 (total number of eligible children: 2047; recruitment rate: 59.7%). This included 685 children from the original sample.</p> <p> </p> <p>This dataset represents a subset of the B-Proact1v data to examine the longitudinal associations of children’s body mass index and physical activity with blood pressure. Included in this repository is the dataset and a data dictionary. The dataset includes the variables that underlie the findings in a manuscript entitled ‘A longitudinal study of the associations of children’s body mass index and physical activity with blood pressure’ that has been submitted to PLOS ONE. This dataset has been made available so that future researchers can replicate the study findings using the data. If you wish to use the data for any purpose other than replicating the study findings, please contact the Principal Investigator Professor Russ Jago (russ.jago@bristol.ac.uk) to discuss this.</p>
Meta-analysis results of epigenome-wide association studies in neonates reveals widespread differential DNA methylation associated with birthweight
<p>Birthweight is associated with health outcomes across the life course, DNA methylation may be an underlying mechanism. In this meta-analysis of epigenome-wide association studies of 8,825 neonates from 24 birth cohorts in the Pregnancy And Childhood Epigenetics Consortium, DNA methylation in neonatal blood is associated with birthweight at 914 sites, with a difference in birthweight ranging from -183 to 178 grams per 10% increase in methylation (P<sub>Bonferroni</sub><1.06x10<sup>-7</sup>).</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>
GWAS to single cell: Intersecting single-cell transcriptomics and genome wide association studies identifies crucial cell-populations and candidate genes for atherosclerosis.
<p><strong>Background</strong></p> <p>Genome-wide association studies (GWAS) have discovered hundreds of common genetic variants for atherosclerotic disease and cardiovascular risk factors. The translation of susceptibility loci into biological mechanisms and targets for drug discovery remains challenging. Intersecting genetic and gene expression data has led to identification of candidate genes. However, the assayed tissues are often non-diseased and heterogeneous in cell composition confounding the candidate prioritization. We collected single-cell transcriptomics (scRNA-seq) from atherosclerotic plaques and aimed to identify cell-type-specific expression of disease-associated genes. </p> <p> </p> <p><strong>Methods and Results</strong></p> <p>To identify disease-associated candidate genes, we applied gene-based analyses using GWAS summary statistics from 46 atherosclerotic, cardiometabolic, and other traits. Next we intersected these candidates with single-cell transcriptomics (scRNA-seq) to identify those genes that are specifically expressed in individual cell (sub)populations of atherosclerotic plaques. We derive an enrichment score and show that loci that associated with coronary artery disease demonstrated a prominent substrate in plaque smooth muscle cells (<em>SKI</em>, <em>KANK2</em>, <em>SORT1</em>), endothelial cells (<em>SLC44A1</em>, <em>ATP2B1</em>), and macrophages (<em>APOE</em>, <em>HNRNPUL1</em>). Further sub clustering of SMC-subtypes revealed genes in risk loci for coronary calcification specifically enriched in a synthetic cluster of SMCs. To verify the robustness of our approach, we used liver-derived scRNAseq-data and showed enrichment of circulating lipids-associated loci in hepatocytes.</p> <p><br> <strong>Conclusion</strong></p> <p>We confirm known gene-cell pairs relevant for atherosclerotic disease, and discovered novel pairs pointing to new biological mechanisms amenable for therapy. We present an intuitive single-cell transcriptomics driven workflow rooted in human large-scale genetic studies to identify putative candidate genes and affected cells associated with cardiovascular traits.</p> <p> </p>
Processed data used in transcriptome- metabolome-wide association study
<p>Processed_RNASeq_RPKM.txt contains RPKM levels for 45484 genes quantified in 555 individuals from RNA-Seq of lymphoblastoid cell lines (LCLs).</p> <p>Processed_NMRpeaks_baseline.txt contains binned, normalized and standardised (z-scored) NMR peak intensities for 1276 bins quantified in 555 individuals from urine samples taken at baseline. NMR spectra were acquired at 300 K on a Bruker 16.4 T Avance II 700 MHz NMR spectrometer (Bruker Biospin, Rheinstetten, Germany) using a standard 1H detection pulse sequence with water suppression. The spectra were referenced to the TSP signal and phase and baseline corrected.</p> <p>Processed_NMRpeaks_followup.txt contains binned, normalized and standardised (z-scored) NMR peak intensities for 1289 bins quantified in 315 individuals from urine samples taken during follow-up. NMR spectra were acquired with an Avance III HD 600 NMR spectrometer. Spectra were referenced to the TSP signal and phase and baseline corrected.</p> <p>More details on the data set can be found in Sönmez Flitman et al. (doi: https://doi.org/10.1101/2020.05.22.110197).</p>
A scalable, accurate, and universal analysis framework using individual-level allele frequency for large-scale genetic association studies in an admixed population
<p>Inclusion of individuals with diverse or admixed genetic ancestries is crucial to discover novel findings that may be missed by genomics analyses rooted solely in Caucasian population. Here, we present an analysis framework, SPAmix, which is scalable to a large-scale biobank data analysis including hundreds of thousands of admixed individuals and is universally applicable to various types of complex traits including binary trait, quantitative trait, time-to-event trait, longitudinal traits, etc. For each genetic variant, SPAmix uses genotype data and genetic principal components (PCs) to estimate individual-level allele frequency, which is subsequently used to calibrate p values via a retrospective analysis. A hybrid strategy including saddlepoint approximation (SPA) can greatly increase the accuracy to analyze rare genetic variants, especially if the phenotypic distribution is unbalanced or extremely unbalanced. Compared to Tractor, SPAmix does not require local ancestry information and can be straightforwardly applicable to a multi-way admixed population. Meanwhile, SPAmix can also be extended to SPAmix<sub>local</sub> in which the local ancestry can be incorporated if available. In addition, we propose SPAmix<sub>CCT</sub> to combine the p values of SPAmix and SPAmix<sub>local</sub> via Cauchy combination (CCT). SPAmix<sub>local</sub> performs close to Tractor when analyzing quantitative traits and is more accurate when analyzing binary traits with an unbalanced case-control ratio. And SPAmix<sub>CCT </sub>is an optimal unified approach for various cross-ancestry genetic architectures. Extensive simulation studies and real data analyses of 369,314 UK Biobank individuals from multiple ancestries demonstrated that SPAmix is scalable and can discover novel hits while controlling type I error rates well.</p>
Data associated with a study on freshwater phenanthrene removal by three emergent wetland plants conducted in a microcosm experiment at the IISD Experimental Lakes Area, ON, Canada, in 2022.
The following package includes data from a study that evaluated the efficacy of three common wetland plants, Typha sp. (cattail), Carex utriculata (sedge a), and C. lasiocarpa (sedge b) in enhancing removal of phenanthrene (1 mg/L) from freshwater in a microcosm experiment conducted at the IISD Experimental Lakes Area, northwestern Ontario, Canada, in 2022. Over 21 days, microcosms were monitored for phenanthrene chemistry, basic water quality, plant growth metrics (height and final biomass), and root biofilm oxygen consumption (respirometry) and adenosine triphosphate (ATP). Data included in this package was first collected and used in the paper by Stanley et al., titled Freshwater Phenanthrene Removal by three Emergent Wetland Plants.
Observational study of post-fire mycorrhizal communities associated with resprouting Betula nana shrubs across a fire-severity gradient in the Anaktuvuk River Fire burn scar, 2009
The dataset contains fungal community data from a sampling campaign in 2009, two growing seasons after the Anaktuvuk River Fire. We used molecular tools, including ARISA and fungal ITS sequencing, to characterize the mycorrhizal communities on resprouting Betula nana shrubs across a fire-severity gradient. Summarized data can be viewed by site and provide information on richness and abundance of basidiomycetes and ascomycetes andChao1 and MaoTau estimators of richness.
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.