Find research datasets worth reusing

opencc-by-4.0Jan 2024View details →

GWAS Summary Statistics from "Sex and statin-related genetic associations at the PCSK9 gene locus – results of genome-wide association meta-analysis"

GWAMA summary statistics of PCSK9 levels stratified by sex and statin useage in Europeans. When using this data, please cite: Pott, J., Kheirkhah, A., Gadin, J.R. et al. Sex and statin-related genetic associations at the PCSK9 gene locus: results of genome-wide association meta-analysis. Biol Sex Differ 15, 26 (2024). https://doi.org/10.1186/s13293-024-00602-6 All txt files contain the following columns: <ul> <li>markername (unique SNP ID)</li> <li>chr</li> <li>bp_hg19 (base position according to hg19)</li> <li>EA (effect allele)</li> <li>OA (other allele)</li> <li>EAF (effect allele frequency)</li> <li>info (minimal info score across all used studies)</li> <li>nSamples (sample size per SNP)</li> <li>nStudies (in case of double-stratified data: number of studies; in case of single-stratified data: 2, as it is a meta-analysis of the two double-stratified data sets)</li> <li>beta (effect estimate)</li> <li>SE (standard error)</li> <li>pval (p-value)</li> <li>I2 (SNP heterogeneity across studies)</li> <li>invalidAssoc (TRUE/FALSE flag if this variant was excluded in our analysis)</li> <li>reason4exclusion (reason why this SNP was excluded)</li> <li>phenotype (phenotyp setting)</li> </ul>

opencc-by-4.0Jun 2022View details →

Genome-wide association study suggests that variation at the RCOR1 locus is associated with tinnitus in UK Biobank

The dataset contains results of a genome-wide association studies for age-related hearing impairment (ARHI)-related traits as described in the following publication: 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

opencc-by-4.0Aug 2022View details →

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)

Summary statistics for genome-wide association studies reported in: 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. Scientific Reports, DOI: <a href="https://dx.doi.org/10.1038/s41598-022-19106-7">10.1038/s41598-022-19106-7</a>.  Abstract 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.   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.

opencc-by-4.0May 2023View details →

Genome-wide association study of full body nevus count in the Brisbane Twin Nevus Study (BTNS)

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. Sample: GWAS analysis only includes samples of European ancestry. total nevus count were counted by trained research nurse. 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 Columns include: CHR: Chromosome BP: Base pair SNP: rsID A1: Effect allele A2: Non-effect allele A1FQ: Effect allele frequency HWE: Hardy-Weinberg Equilibrium BETA: Effect estimate (of effect allele_ SEB: Standard error of beta PRB: P value N: Per SNP sample size

opencc-by-4.0May 2020View details →

Genome-wide association summary statistics of chronic musculoskeletal pain at four anatomic sites and their genetically independent components

The dataset contains results of a genome-wide association study of distinct chronic musculoskeletal pain conditions: back pain, knee pain, neck pain, and hip pain. Additionally, there are genome-wide association summary statistics for four genetically independent components of pain conditions, listed above. For more details, please, read the paper XXX. All files contain association summary statistics for genome-wide association meta-analysis of the 265,000 white British individuals from the UK Biobank and additional 191,580 individuals of European Ancestry from the UK biobank (total N = 456,580). Cases and controls were defined based on questionnaire responses. First, participants responded to “Pain type(s) experienced in the last months” followed by questions inquiring if the specific pain had been present for more than 3 months. Those who reported back, neck or shoulder, hip, or knee pain lasting more than 3 months were considered chronic back, neck/shoulder, hip, and knee pain cases, respectively. Participants reporting no such pain lasting longer than 3 months were considered controls (regardless of whether they had another regional chronic pain, such as abdominal pain, or not). Individuals who preferred not to answer were excluded from the study. Besides this, we excluded individuals who reported more than 3 months of pain all over the body. The data are provided on an "AS-IS" basis, without warranty of any type, expressed or implied, including but not limited to any warranty as to their performance, merchantability, or fitness for any particular purpose. If investigators use these data, any and all consequences are entirely their responsibility. By downloading and using these data, you agree that you will cite the appropriate publication in any communications or publications arising directly or indirectly from these data; for utilization of data available prior to publication, you agree to respect the requested responsibilities of resource users under 2003 Fort Lauderdale principles; you agree that you will never attempt to identify any participant. This research has been conducted using the UK Biobank Resource and the use of the data is guided by the principles formulated by the UK Biobank. When using downloaded data, please cite the corresponding paper and this repository: <ol> <li>Tsepilov et al 2020</li> </ol> Funding: The work of YSA and SZS was supported by the Russian Ministry of Education and Science under the 5-100 Excellence Programme and by the Federal Agency of Scientific Organizations via the Institute of Cytology and Genetics (project 0324-2019-0040). The work of YAT, ASSh, and EEE was supported by the Russian Foundation for Basic Research (project 19-015-00151). The contribution of LСK was funded by PolyOmica.  Dr. Suri was supported by VA Career Development Award # 1IK2RX001515 from the United States (U.S.) Department of Veterans Affairs Rehabilitation Research and Development (RR&D) Service. Dr. Suri is a Staff Physician at the VA Puget Sound Health Care System. The contents of this work do not represent the views of the U.S. Department of Veterans Affairs or the United States Government. List of files: <ol> <li>Back_output_done.csv: GWAS summary statistics for the chronic back pain</li> <li>gpc1_output_done.csv: GWAS summary statistics for the GIP1</li> <li>gpc2_output_done.csv: GWAS summary statistics for the GIP2</li> <li>gpc3_output_done.csv: GWAS summary statistics for the GIP3</li> <li>gpc4_output_done.csv: GWAS summary statistics for the GIP4</li> <li>Hip_output_done.csv: GWAS summary statistics for the chronic hip pain</li> <li>Knee_output_done.csv: GWAS summary statistics for the chronic knee pain</li> <li>Neck_output_done.csv: GWAS summary statistics for the chronic neck pain</li> </ol> Column headers: <ol> <li>gwas_id: uninformative field</li> <li>rs_id: dbSNP rsID (GRCh37 build) </li> <li>snp_num: uninformative field</li> <li>chr: chromosome (GRCh37 build) </li> <li>bp: position (GRCh37 build) </li> <li>ea: effect allele (coded as "1")</li> <li>ra: reference allele (coded as "0")</li> <li>eaf: effect allele frequency</li> <li>af_ref: uninformative field</li> <li>beta: effect size of effect allele</li> <li>se: standard error of effect size</li> <li>p: P-value of association (without GC correction)</li> <li>n:Total sample size</li> <li>z: Z-statistic of association</li> <li>info: uninformative field</li> <li>af_outlier: uninformative field</li> <li>pz_outlier: uninformative field</li> </ol>

opencc-by-4.0Apr 2024View details →

GWAS summary stats in "Genome-wide association meta-analysis identifies two novel loci associated with dental caries."

Summary stats of the genome-wide meta-analysis for dental caries and periodontal diseases in our study (population A and B). Article "Genome-wide association meta-analysis identifies two novel loci associated with dental caries." https://doi.org/10.1186/s12903-024-04799-1

opencc-by-4.0Dec 2021View details →

Genome-wide association analyses identify novel Brugada syndrome risk loci and highlight a new mechanism of sodium channel regulation in disease susceptibility

The Brugada syndrome GWAS summary statistics Brugada syndrome is a cardiac arrhythmia disorder associated with sudden death in young adults. With the exception of SCN5A, encoding the cardiac sodium channel NaV1.5, susceptibility genes remain largely unknown. We performed a genome-wide association meta-analysis comprising 2,820 unrelated cases with Brugada syndrome and 10,001 controls.

opencc-by-4.0Sep 2017View details →

False discovery rate calculations for genome-wide association study of reproductive fitness in Drosophila melanogaster (Sussex LHM sample)

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. 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. 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.

opencc-by-4.0Jul 2018View details →

Genome-wide association summary statistics for varicose veins of lower extremities

The dataset contains summary statistics for the discovery and the replication stages of the large-scale genome-wide associations study for varicose veins of lower extremities. The discovery stage was based on genetic association data provided by the Neale Lab (<a href="https://vk.com/away.php?to=http%3A%2F%2Fwww.nealelab.is%2F&cc_key=">http://www.nealelab.is/</a>) for 337,199 UK biobank individuals. Phenotype “varicose veins of lower extremities” was defined based on International Classification of Disease (ICD-10) billing code “I83” present in the electronic patient record. Data were adjusted for two potential confounders – body mass index and deep venous thrombosis. A replication cohort (N=71,256) was generated by means of reverse meta-analysis of two overlapping datasets: genetic association data for 408,455 UK Biobank participants provided by the Gene ATLAS database (<a href="https://vk.com/away.php?to=http%3A%2F%2Fgeneatlas.roslin.ed.ac.uk%2F&cc_key=">http://geneatlas.roslin.ed.ac.uk/</a>), and the above mentioned data provided by the Neale Lab. Please, note, that in Shadrina et al (PLOS Genetics 2019) we only used "discovery" dataset, while in biorxiv preprint (https://doi.org/10.1101/368365) both discovery and replication datasets were used.  The data are provided on an "AS-IS" basis, without warranty of any type, expressed or implied, including but not limited to any warranty as to their performance, merchantability, or fitness for any particular purpose. If investigators use these data, any and all consequences are entirely their responsibility. By downloading and using these data, you agree that you will cite the appropriate publication in any communications or publications arising directly or indirectly from these data; for utilisation of data available prior to publication, you agree to respect the requested responsibilities of resource users under 2003 Fort Lauderdale principles; you agree that you will never attempt to identify any participant.  When using downloaded data, please cite corresponding paper and this repository: <ol> <li> Shadrina, A. S., Sharapov, S. Z., Shashkova, T. I. & Tsepilov, Y. A. Varicose veins of lower extremities: Insights from the first large-scale genetic study. PLOS Genet. 15, e1008110 (2019). </li> <li>Alexandra S. Shadrina, Sodbo Zh. Sharapov, Tatiana I. Shashkova, & Yakov A. Tsepilov. (2018). Genome-wide association summary statistics for varicose veins of lower extremities (Version 1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1323484</li> </ol> Funding: The work of ASS was supported by the Russian Science Foundation [Project No 17-75-20223].  The work of YAT was supported by the Russian Ministry of Science and Education under the 5-100 Excellence Programme.  The work of SZS was supported by the Institute of Cytology and Genetics [Project No 0324-2018-0017]. Column headers - discovery <ol> <li>SNP: SNP rsID</li> <li>b: effect size of effect allele</li> <li>se: standard error of effect size</li> <li>chi2: T^2 value of effect allele</li> <li>Pval: P-value of association (without GC correction)</li> <li>N: sample size</li> <li>Chr: chromosome</li> <li>Pos: position (GRCh37 build)</li> <li>A1: effect allele (coded as "1")</li> <li>A2: reference allele (coded as "0")</li> </ol> Column headers - replication <ol> <li>SNP: SNP rsID</li> <li>A1: effect allele (coded as "1")</li> <li>A2: reference allele (coded as "0")</li> <li>N: Total sample size</li> <li>Z: Z-value of effect allele</li> <li>P: P-value of association (without GC correction)</li> </ol>

opencc-by-4.0Dec 2018View details →

Data for: Bivariate Genome-Wide Association Scan Identifies 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease.

Summary of Bivariate GWAS scan results reported in: <a href="https://pubmed.ncbi.nlm.nih.gov/30525989/">Bivariate Genome-Wide Association Scan Identifies 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease. </a>Siewert KM, Voight BF. Circ Genom Precis Med. 2018 Dec;11(12):e002239. doi: 10.1161/CIRCGEN.118.002239. PMID: 30525989

opencc-by-4.0Dec 2022View details →

Genome-wide association statistics of Hearing Problems

Genome-wide Association Statistics of Hearing Problems Citation: De Angelis F, Zeleznik OA, Wendt FR, Pathak GA, Tylee DS, De Lillo A, Koller D, Cabrera-Mendoza B, Clifford RE, Maihofer AX, Nievergelt CM, Curhan GC, Curhan SG, Polimanti R. Sex differences in the polygenic architecture of hearing problems in adults. Genome Med. https://doi.org/10.1186/s13073-023-01186-3 COLUMN HEADERS chromosome: chromosome base_pair_location: position effect_allele: effect allele (corresponds to the effect size’s sign; may not be the alternate allele) other_allele: non-effect allele beta: effect measured as beta, sign corresponds to the effect of the effect allele standard_error: standard error of the effect effect_allele_frequency: effect allele frequency in UK Biobank participants of European descent p_value: p value of the association statistic variant_id: variant identifier rs_id: rsID of the variant n: sample size per variant

opencc-by-4.0Jul 2023View details →

Variant calls for 'Genome-wide identification of lineage and locus specific variation associated with pneumococcal carriage duration'

A VCF of SNP calls used for input to GWAS in https://elifesciences.org/articles/26255

opencc-by-4.0Oct 2020View details →

Genome-wide association summary statistics for sex- and age-specific analysis of chronic back pain

The dataset comprises summary-level statistics for age- and sex-specific genome-wide association study of chronic back pain (cBP) in individuals of European descent from UK Biobank (<a href="https://www.ukbiobank.ac.uk/">https://www.ukbiobank.ac.uk/</a>). The study was carried out under UK Biobank approved project #18219.  The dataset accompanies the paper (please cite if using the dataset): <a href="https://pubmed.ncbi.nlm.nih.gov/33021770/">Freidin, Maxim B.; Tsepilov, Yakov A.; Stanaway, Ian B.; Meng, Weihua; Hayward, Caroline; Smith, Blair H.; Khoury, Samar; Parisien, Marc; Bortsov, Andrey; Diatchenko, Luda; Børte, Sigrid; Winsvold, Bendik S.; Brumpton, Ben M.; Zwart, John-Anker; HUNT All-In Pain; Aulchenko, Yurii S.; Suri, Pradeep; Williams, Frances M.K. Sex- and age-specific genetic analysis of chronic back pain. Pain. 2020. doi:10.1097/j.pain.0000000000002100.</a> The phenotype of cBP was defined as back pain for 3+ months. Linear mixed-effects additive model was fitted adjusting for age, genotyping array type, and 10 genetic PCs provided by UK Biobank. The following filters were applied: minor allele frequency >0.001, genotyping and individual call rates >0.98%, imputation quality score (INFO) >0.7. GWAS were carried out in males and females separately in the whole sample (allages) as well as in groups of younger than 65 years (under65) and 65+ years old (65plus) as detailed in the paper. Accordingly, 6 files are deposited here, corresponding to each group.  Column headers: SNP, SNP rsID  CHR, chromosome BP, genomic position (GRCh37 build) EA, effect allele (coded as "1") OTHER, other allele (coded as "0") A1FREQ, frequency of effect allele INFO, imputation quality BETA, effect size (for effect allele) SE, standard error of effect size PVAL, p-value for association

opencc-by-4.0Sep 2021View details →

Genome-wide association study identifies RNF123 locus as associated with chronic widespread musculoskeletal pain

The dataset (CWP_GWAS_EU_ANCESTRY_UKB.txt) contains summary statistics for discovery GWAS of chronic widespread pain based on northern Europeans from UK Biobank comprising 6,914 cases of chronic widespread musculoskeletal pain and 242,929 controls. The sensitivity GWAS (CWP_sensitivity_GWAS_EU_ANCESTRY_UKB.txt) dataset contains summary statistics derived from 6,914 cases of chronic widespread musculoskeletal pain and 223,606 controls. Methodological details available here, https://doi.org/10.1101/2020.11.30.20241000

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Genome-wide sequence data show no evidence of hybridization and introgression among pollinator wasps associated with a community of Panamanian strangler figs

The specificity of pollinator host choice influences opportunities for reproductive isolation in their host plants. Similarly, host plants can influence opportunities for reproductive isolation in their pollinators. For example, in the fig and fig wasp mutualism, offspring of fig pollinator wasps mate inside the inflorescence that the mothers pollinate. Although often host specific, multiple fig pollinator species are sometimes associated with the same fig species, potentially enabling hybridization between wasp species. Here we study the 19 pollinator species (Pegoscapus spp.) associated with an entire community of 16 Panamanian strangler fig species (Ficus subgenus Urostigma, section Americanae) to determine whether the previously documented history of pollinator host switching and current host sharing predicts genetic admixture among the pollinator species, as has been observed in their host figs. Specifically, we use genome-wide ultraconserved element (UCE) loci to estimate phylogenetic relationships and test for hybridization and introgression among the pollinator species. In all cases, we recover well-delimited pollinator species that contain high interspecific divergence. Even among pairs of pollinator species that currently reproduce within syconia of shared host fig species, we found no evidence of hybridization or introgression. This is in contrast to their host figs, where hybridization and introgression have been detected within this community, and more generally, within figs worldwide. Consistent with general patterns recovered among other obligate pollination mutualisms (e.g., yucca moths and yuccas), our results suggest that while hybridization and introgression are processes operating within the host plants, these processes are relatively unimportant within their associated insect pollinators.

opencc-zeroFeb 2022View details →

opencc-by-4.0Dec 2021View details →

Genome-wide analysis identified candidate variants and genes associated with heat stress adaptation in Egyptian sheep breeds

The current study was conducted from 2009 to 2019 in three hot and dry agroecological zones in Egypt: Western Desert coastal zone, New Valley desert oasis, and hot-dry Upper Egypt. Within these zones, three local sheep breeds were studied: Barki (83 ewes), Wahati (55 ewes) and Saidi (68 ewes). During the study period, the animals exercised under natural heat stress (simulating summer grazing on poor pasture). Meteorological and physiological parameters were measured and recorded. The heat tolerance index of the animals was calculated to identify animals with high and low heat tolerance based on the animals' response to the five main physiological parameters (scale from 0 to 5). DNA samples were extracted for genomic analysis. The genetic diversity measurements showed a significant influence of breed and location on the populations. The influence of breed is more significant than that of location. The inbreeding analysis shows that the desert breeds (Wahati and Barki) have lower values than the urban breed (Saidi). The high rate of sub-clustering indicates the process of sub-population through inbreeding pressure. Wahati and Barki are very distinct breeds with strong identification, while Saidi breed has crosses with other breeds. The most significant SNPs associated with heat tolerance were found in MYO5A, PRKG1, GSTCD, and RTN1 genes (P < 0.0001). MYO5A had an effect of 0.74 on the trait heat tolerance in the studied population. It produces a protein that is widely distributed in the melanin-producing neural crest of the skin. Genetic association between genetic and phenotypic variations showed that OAR1 18300122.1, located in ST3GAL3, had the greatest positive effect on heat tolerance. GWAS analysis identified SNPs associated with heat tolerance in the PLCB1, STEAP3, KSR2, UNC13C , PEBP4, and GPAT2 genes.