Find research datasets worth reusing

opencc-by-4.0Aug 2021View details →

Simulated genetic data in a hierarchical metapopulation structure

The data are linked to a research article entitled: “Interactions between microenvironment, selection and genetic architecture drive multiscale adaptation in a simulation experiment” in Journal of Evolutionary Biology (see References). In this research on multiscale adaptation, we simulated a hierarchical metapopulation structure with four populations, two environments per population and three patches per environment, in a two-step procedure: <ul> <li>an initialization step without selection, with eight combinations of mutation type, selfing rate and QTL number parameters (2 modes each); out of 200,000 simulated generations in each case, we chose one with appropriate characteristics as a starting point for the next step;</li> <li>a selection step with all possible combinations of the following parameters: environmental pattern (4 modes), environmental range (5 modes), selection intensity (4 modes), fecundity (3 modes).</li> </ul> This resulted in 240 scenarios for each initialized metapopulation, i.e. 1,920 scenarios in total. Each scenario was replicated 10 times, i.e. 19,200 simulation runs. The archive includes all data needed to reproduce the simulations and analyses, or to re-use the simulated metapopulations for other analyses. It has the following structure (further detailed below): <ol> <li>NemoScripts directory contains the Nemo input files used to perform simulations for the initialization step and the selection step;</li> <li>RScripts directory contains the R scripts to read the Nemo output files, compute synthetic variables(*), and produce the figures as they appear in the publication and supplementary material (*: long computations, therefore we also directly provide those synthetic variables in the Data directory);</li> <li>Data directory contains the Nemo output files, the synthetic variables, and other data needed to reproduce the figures; this directory can be used as a working directory for the R scripts (recommended).</li> </ol> Running the following command in a terminal tar –xzvf Archive_PC_SOM_IS_FL.tar  will create a directory named Archive_PC_SOM_IS_FL, which detailed content is described in the README.pdf file. Warning: the extracted archive is large (460Go, >40,000 files) and extraction may take some time.

opencc-by-4.0Mar 2022View details →

Data from: Absence of genetic isolation across highly fragmented landscape in the ant Temnothorax nigriceps

This README accompanies data_genotyping.txt   Associate publication : Absence of genetic isolation across highly fragmented landscape in the ant Temnothorax nigriceps M. Cordonniera, D. Feltena, A. Trindla, J. Heinzea*, A. Bernadoua* aLehrstuhl für Zoologie / Evolutionsbiologie, Univ. Regensburg *Equal contribution   ****************************** CONTENTS ******************************* The data can be readily imported in any statistical package or spreadsheet program. Please, contact me if you need the file formatted in other ways.   This file includes a description of the variables. *********************************************************************** Variable names and descriptions   Sample:       ID of the sampled nest Location:     Population of the sampled nest   List of genotypes Microsatellite primers used in the study <table> <tbody> <tr> <td> </td> <td> Annealing temperature [°C] </td> <td> Orientation </td> <td> Sequence of primers </td> </tr> <tr> <td> LX GT218 </td> <td> 57 </td> <td> Forward </td> <td> 5’-GTTCTTGCGCGGATGCATAC-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-TGTACTCGCGTGTCTATCGG-3’ </td> </tr> <tr> <td> Ant3993 </td> <td> 57 </td> <td> Forward </td> <td> 5’-TGATCCGCTCTTAAAATTTAGATGGA-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-ACTTTCCGCRGCATTAAACATTTTCTT-3’ </td> </tr> <tr> <td> L-18 </td> <td> 57 </td> <td> Forward </td> <td> 5’-TGAATTTGGATGGCGGTAGAC-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-ACCTAATGCACGCTTTAGAAT-3’ </td> </tr> <tr> <td> LXA GT1 </td> <td> 57 </td> <td> Forward </td> <td> 5’-GTGGCGACCAATTCTGCAAG-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-GCAGGACCAGCATCAAATGACAG-3’ </td> </tr> <tr> <td> 2MS17 </td> <td> 55 </td> <td> Forward </td> <td> 5’-CAGCCTCTATTTTGTTCGAAG-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-TTTACTGCGGCTCCATAATC-3’ </td> </tr> <tr> <td> 2MS46 </td> <td> 55 </td> <td> Forward </td> <td> 5’-GCTCACTACTATGCTGCCAGC-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-CTTTCCTGCAAACCACGTGT-3’ </td> </tr> <tr> <td> 2MS60 </td> <td> 55 </td> <td> Forward </td> <td> 5’-TATGCGCCGGACAATAATCGC-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-GTTCATTGTCCGAGGCGCAGC-3’ </td> </tr> <tr> <td> 2MS67 </td> <td> 55 </td> <td> Forward </td> <td> 5’-GAAGATTCGTCAGGATGCAGC-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-AACTCTCGCTGGCAAGCGAGC-3’ </td> </tr> <tr> <td> 2MS82 </td> <td> 55 </td> <td> Forward </td> <td> 5’-AAAAGAGCATGCAACAGGTCAGC-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-TTTCTTAAGTCGCAAGCGAGC-3’ </td> </tr> <tr> <td> 2MS87 </td> <td> 55 </td> <td> Forward </td> <td> 5’-GGAACCTCACTCAACCTCGGT-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-ACGCGGACTACTTTAACCGGA-3’ </td> </tr> <tr> <td> 2MS91 </td> <td> 55 </td> <td> Forward </td> <td> 5’-AAAGTCTCGGAGTGGCTTTGC-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-ATTCTCGTCCATTTGTTCTAA-3’ </td> </tr> <tr> <td> Ant11893 </td> <td> 55 </td> <td> Forward </td> <td> 5’-CAGGCTCGGRACGTTAATGC-3’ </td> </tr> <tr> <td> Reverse </td> <td> 5’-GGTGCCGACGTCTAGCTAGC-3’ </td> </tr> </tbody> </table>   Missing data are encoded “-9”.   ****************************** CONTACTING ***************************** Contact me at:   Marion Cordonnier e-mail: marion.cordonnier@hotmail.com   ***********************************************************************

opencc-by-4.0Jan 2022View details →

First genetic data for the Critically Endangered Cuban endemic Zapata Rail Cyanolimnas cerverai, and the taxonomic implications

Data associated with the publication First genetic data for the Critically Endangered Cuban endemic Zapata Rail Cyanolimnas cerverai, and the taxonomic implications.

opencc-by-4.0May 2024View details →

Data for 'Genetic variation in trophic avoidance shows fruit flies are generally attracted to bacterial pathogens'

Raw data dn R code for the analysis of data dn generation of all figures in the above referenced paper. Descriptions of each data file are included wihtin the R script.

opencc-by-4.0Feb 2019View details →

Processed data for the study on "Chromatin 3D interactions mediate genetic effects on gene expression"

This repository contains the processed data that was generated as part of the following study: Delaneau et al. (2019) Chromatin 3D interactions mediate genetic effects on gene expression. Abstract: Studying the genetic basis of gene expression and chromatin organization is key to characterize the effect of genetic variability on the function and structure of the human genome. Here, we unravel how genetic variation perturbs gene regulation using a dataset combining activity of regulatory elements, gene expression and genetic variants across 317 individuals and two cell types. We show that variability in regulatory activity is structured at the intra- and inter-chromosomal levels within 12,583 Cis Regulatory Domains and 30 Trans Regulatory Hubs that highly reflect the local (i.e. Topologically Associating Domains) and global (i.e. open/close chromatin compartments) nuclear chromatin organization. These structures delimit cell type specific regulatory networks that control gene expression/co-expression and mediate the genetic effects of cis- and trans-acting regulatory variants on genes.   This repository contains: <ol> <li>Chromatin QTLs for H3K27ac, H3K4me1 and H3K4me3 discovered in 317 Lymphoblastoids Cell Lines (LCLs) and 78 Fibroblasts.</li> <li>Molecular QTLs affecting the activity and structure of Cis Regulatory Domains (CRDs) in LCLs.</li> <li>Basic information about the full set of genetic variants being analyzed in the study.</li> <li>The peak coordinates, their hierarchy based on inter-individual correlation and the CRD calls for both LCLs and Fibroblasts.</li> <li>The functional links discovered in LCLs between CRDs and genes.</li> <li>eQTLs for LCLs.</li> <li>A README file containing the description of the file format for each file.</li> </ol>

opencc-by-4.0Mar 2019View details →

RDF Linked Data representation of GC-MS data from the 'Rose Genome' article published in Nature genetics, June, 2018

This dataset corresponds to the RDF Linked Data representation of the measurements of 61 known metabolites (all annotated with resolvable CHEBI identifiers and InChi strings), measured by gas chromatography mass-spectrometry (GC-MS) in 6 different Rose cultivars (all annotated with resolvable NCBITaxonomy Identifiers) and 3 organism parts (all annotated with resolvable Plant Ontology identifiers). The quantitation types are annotated with resolvable <a href="https://github.com/ISA-tools/stato">STATO</a> terms. Most of the semantics resources belong to the <a href="http://obofoundry.org">OBO foundry</a>. The transformation to RDF was performed on a Frictionless Tabular Data Package (<a href="https://frictionlessdata.io/specs/tabular-data-package/">https://frictionlessdata.io/specs/tabular-data-package/)</a>, holding the data extracted from a supplementary material table, available from <a href="https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip">https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip</a>  and published alongside the Nature Genetics manuscript identified by the following doi: <a href="https://doi.org/10.1038/s41588-018-0110-3">https://doi.org/10.1038/s41588-018-0110-3</a>, published in June 2018. This supplementary material table was deposited to Zenodo and is identified by the following doi: <a href="https://doi.org/10.5281/zenodo.2598799">https://doi.org/10.5281/zenodo.2598799</a> This dataset is used to demonstrate how to make data Findable, Accessible, Discoverable and Interoperable (FAIR) and how Frictionless Tabular Data Package representations can be easily mobilised for reanalysis and data science. It is associated to the following project: <a href="https://github.com/proccaserra/rose2018ng-notebook">https://github.com/proccaserra/rose2018ng-notebook</a> with all the necessary information, executable code and tutorials in the form of Jupyter notebooks.

opencc-by-4.0Aug 2024View details →

Example Dataset for npstat: Population genetics from Pooled NGS data NPStat v1: User guide

Example Dataset for npstat to test the program and the different options. The example dataset contains a pileup file with sequences of of the 2L chromosome from fifteen pooled inbreed individuals of Drosophila melanogaster (doi: 10.1038/nature10811). The dataset also contains the sequence reference of the 2L chromosome  in fasta format, an outgroup sequence in fasta format of D. yakuba (SRR26246471), a GFF3 annotation file and a file with a brief list of selected SNPs to be analyzed.

opencc-by-4.0Nov 2022View details →

Supplemental data from: Nature or nurture: A genetic basis for the behavioral selection of depth in siscowet and lean lake charr (Salvelinus namaycush) ecomorphs

These files contain the raw depth and temperature sensor data from siscowet and lean lake charr (Salvelinus namaycush) ecomorphs tagged with pop-up satellite archival tags (PSATs). These fish were produced from wild gametes taken from Lake Superior and reared in a common garden study for nine years and then tagged with PSATs and released in southern Lake Superior. The dataset is supplemental to: Goetz, F., Sitar, S., Seider, M., and Jasonowicz, A. 2022. Nature or nurture: A genetic basis for the behavioral selection of depth in siscowet and lean lake charr (Salvelinus namaycush) ecomorphs. Canadian Journal of Fisheries and Aquatic Sciences. (in press). Data description for metadata.csv: This file contains the metadata associated with each tag deployment. This includes biological data as well as key mission paramters. <table> <thead> <tr> <td>Column</td> <td>Type</td> <td>Description</td> </tr> </thead> <tbody> <tr> <td>mission_id</td> <td>integer</td> <td>mission identifier</td> </tr> <tr> <td>tag_sn</td> <td>integer</td> <td>tag serial number</td> </tr> <tr> <td>ecotype</td> <td>string</td> <td>lake trout ecotype</td> </tr> <tr> <td>release_date</td> <td>string</td> <td>date of tag release</td> </tr> <tr> <td>length_mm</td> <td>float</td> <td>total length in mm</td> </tr> <tr> <td>weight_g</td> <td>float</td> <td>weight in g</td> </tr> <tr> <td>lipid</td> <td>float</td> <td>lipid level meadured by Distell fatmeter set in research mode</td> </tr> <tr> <td>release_site</td> <td>string</td> <td>release site (deep or shallow site)</td> </tr> <tr> <td>sampling_rate</td> <td>string</td> <td>sampling interval of tag (format=HH:MM:SS)</td> </tr> <tr> <td>mission_end_utc</td> <td>datetime</td> <td>programmed tag pop off date and time in UTC time (format=YYYY-MM-DD HH:MM:SS)</td> </tr> <tr> <td>notes</td> <td>string</td> <td>notes and comments</td> </tr> </tbody> </table>   Data description for the raw sensor data files: The raw sensor data is found in the files that are prefixed with "raw-sensor-data". The data for each tag is in contained in a seperate file and the files are named as follows "raw-sensor-data-{mission_identifier}-{tag_serial_number}.csv". <table> <thead> <tr> <td>Column</td> <td>Type</td> <td>Description</td> </tr> </thead> <tbody> <tr> <td>mission_id</td> <td>integer</td> <td>mission identifier</td> </tr> <tr> <td>tag_sn</td> <td>integer</td> <td>tag serial number</td> </tr> <tr> <td>timestamp_utc</td> <td>datetime</td> <td>timestamp of sensor reading (format=YYYY-MM-DD HH:MM:SS)</td> </tr> <tr> <td>depth_m</td> <td>string</td> <td>depth in meters</td> </tr> <tr> <td>temperature_c</td> <td>string</td> <td>temperature in degrees celcius</td> </tr> </tbody> </table>

opencc-by-4.0Apr 2023View details →

Microsatellite genotype data and leaf morphological data of the publication "Bidirectional gene flow between Fagus sylvatica L. and F. orientalis Lipsky despite strong genetic divergence"

These data sets were used for analyses in the publication "Bidirectional gene flow between Fagus sylvatica L. and F. orientalis Lipsky despite strong genetic divergence" accepted in Forest Ecology and Management <a href="https://www.sciencedirect.com/journal/forest-ecology-and-management/vol/537/suppl/C">Volume 537</a>, 1 June 2023, 120947, <a href="https://doi.org/10.1016/j.foreco.2023.120947">https://doi.org/10.1016/j.foreco.2023.120947</a> For details about the data, please read the corresponding ReadMe files.

opencc-by-4.0May 2023View details →

Supplementary data and summary statistics - Genetic influences on circulating retinol and its relationship to human health

Summary statistics from the circulating retinol GWAS See - GWAS_summary_stats_README.txt for details of these files and the header names. METSIM+INTERVAL meta-analyses have a sample size of 17268. The full meta-analysis that includes ATBC+PLCO has a sample size of 22274. Please cite the following if you use any of these data - Reay, W.R. et al. Genetic influences on circulating retinol and its relationship to human health. Nature Communications (2024). By downloading these summary statistics, investigators agree to the following: <ol> <li>Investigators acknowledge that these 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.</li> <li>Investigators will not cross-post these data or make them available elsewhere – this website is the definitive source for these data without express written permission from the study corresponding authors.</li> <li>Investigators will never attempt to identify any participant who contributed to these data.</li> <li>Any commercial or for-profit use of these data is forbidden unless express permission is sought from the study corresponding authors.</li> <li>Investigators will cite the associated manuscript when using these data.</li> </ol> Supplementary data from the circulating retinol GWAS phenome-wide Mendelian randomisation study 1. MR_retinol_as_exp - full output from the MR-pheWAS using circulating retinol as the exposure

edi44/100

Descriptive data file for information regarding microbial genetic research in the environs of Plum Island Sound watersheds, PIE LTER, Massachusetts.

This is a descriptive, tabular dataset of publications related to microbial or genomic research conducted within PIE. Assession numbers for genetic sequences generated from PIE samples are provided where available, followed by a very brief description of analysis type and study objectives. Sampling locations within PIE, sampling dates, and habitat type (sea water, fresh water, sediment, marsh) are also given. Environmental data are included in some publications and are listed here (if brief) or availability is described. Links to sequence archives are given in Methods.

openCC (other)Jul 2021View details →

opencc-by-4.0May 2020View details →

Genetic data and underlying taxa and GenBank sources of diatoms used in phylogenetic analysis for the diatom genus Nupela

Supplementary material for the manuscript: Kulikovskiy M., Maltsev Y., Glushchenko A., Gusev E., Kapustin D., Kuznetsova I., Kociolek J.P. Preliminary molecular phylogeny of the diatom genus Nupela with the description of a new species and consideration of the interrelationships of taxa in the suborder Neidiineae D.G. Mann sensu E.J. Cox. Fottea Molecular investigation of diatom genera Nupela and Brachysira is conducted using strains from Indonesia and Vietnam. New species from the genus Nupela indonesica sp. nov. is described using combined approach. Nupela lesothensis (Schoeman) Lange-Bertalot is investigated using molecular data too. Phylogenetic analysis shows that Nupela and Brachysira are not closest genera. Morphology of Nupela and it differences from Brachysira is discussed. The genus Nupela is differs from all other diatom taxa by having coalescent hymenes ouside of areolae but not inside. Facultative development of raphe between different Nupela species is discussed. SUPPLEMENT S1. Taxa and DNA sequence data used in phylogenetic analysis. SUPPLEMENT S2. Final alignment of 2-gene DNA sequence data used for phylogenetic analysis in FASTA format. SUPPLEMENT S3. Maximum Likelihood tree of Nupela species (indicated in bold) constructed from a concatenated alignment of 163 partial rbcL and partial 18S rDNA sequences of 1806 characters. Values near the horizontal lines (slash) are bootstrap support from RAxML analyses (<50 are not shown). Species from the centric diatoms were used as an outgroup. Families indicated according COX (2015).

opencc-by-4.0May 2020View details →

Summary statistics data for "Genetic Analyses Support the Contribution of mRNA N6-methyladenosine (m6A) Modification to Human Diseases Heritability"

We included the summary statistics data associated with our manuscript "Genetic Analyses Support the Contribution of mRNA N6-methyladenosine (m6A) Modification to Human Diseases Heritability".  We also included the newly imputed genotype data for the 60 YRI individuals involved in our study, the joint m6A peaks tested (locations of the molecular phetnotype in BED12 format) and normalized log odds ratio (enrichment) of these joint peaks (molecular phenotype data).

opencc-zeroJul 2020View details →

Data from: Genetic and environmental canalization are not correlated among altitudinally varying populations of Drosophila melanogaster

Organisms are exposed to environmental and mutational effects influencing both mean and variance of phenotypes. Potentially deleterious effects arising from this variation can be reduced by the evolution of buffering (canalizing) mechanisms, ultimately reducing phenotypic variability. There has been interest regarding the conditions enabling the evolution of canalization. Under some models, the circumstances under which genetic canalization evolves is limited, despite apparent empirical evidence for it. It has been argued that genetic canalization evolves as a correlated response to environmental canalization (congruence model). Yet, empirical evidence has not consistently supported predictions of a correlation between genetic and environmental canalization. In a recent study, a population of Drosophila adapted to high altitude showed evidence of genetic decanalization relative to those from low altitudes. Using strains derived from these populations, we tested if they varied for multiple aspects of environmental canalization We observed the expected differences in wing size, shape, cell (trichome) density and mutational defects between high- and low-altitude populations. However, we observed little evidence for a relationship between measures of environmental canalization with population or with defect frequency. Our results do not support the predicted association between genetic and environmental canalization.

opencc-zeroJun 2020View details →

Data from: Genome wide assessment of genetic variation and population distinctiveness of the pig family in South Africa

Genetic diversity is of great importance and a prerequisite for genetic improvement and conservation programs in pigs and other livestock populations. The present study provides a genome wide analysis of the genetic variability and population structure of pig populations from different production systems in South Africa relative to global populations. A total of 234 pigs sampled in South Africa and consisting of village (n = 91), commercial (n = 60), indigenous (n = 40), Asian (n = 5) and wild (n = 38) populations were genotyped using Porcine SNP60K BeadChip. In addition, 389 genotypes representing village and commercial pigs from America, Europe and Asia were accessed from a previous study and used to compare population clustering and relationships of South African pigs with global populations. Moderate heterozygosity levels, ranging from 0.204 for Warthogs to 0.371 for village pigs sampled from Capricorn municipality in Eastern Cape province of South Africa were observed. Principal Component Analysis of the South African pigs resulted in four distinct clusters of (i) Duroc; (ii) Vietnamese; (iii) Bush pig and Warthog and (iv) a cluster with the rest of the commercial (SA Large White and Landrace), village, Wild Boar and indigenous breeds of Koelbroek and Windsnyer. The clustering demonstrated alignment with genetic similarities, geographic location and production systems. The PCA with the global populations also resulted in four clusters that where populated with (i) all the village populations, wild boars, SA indigenous and the large white and landraces; (ii) Durocs (iii) Chinese and Vietnamese pigs and (iv) Warthog and Bush pig. K= 10 (The number of population units) was the most probable ADMIXTURE based clustering, which grouped animals according to their populations with the exception of the village pigs that showed presence of admixture. AMOVA reported 19.92% – 98.62% of the genetic variation to be within populations. Sub structuring was observed between South African commercial populations as well as between Indigenous and commercial breeds. Population pairwise FSTanalysis showed genetic differentiation (P < 0.05)between the village, commercial and wild populations. A per marker per population pairwise FSTanalysis revealed SNPs associated with QTLs for traits such as meat quality, cytoskeletal and muscle development, glucose metabolism processes and growth factors between both domestic populations as well as between wild and domestic breeds. Overall, the study provided a baseline understanding of porcine diversity and an important foundation for porcine genomics of South African populations.

opencc-zeroDec 2018View details →

Data from: Neo-sex chromosomes and demography shape genetic diversity in the critically endangered Raso lark

Generally small effective population sizes expose island species to inbreeding and loss of genetic variation. The Raso lark has been restricted to a single islet for ~500 years, with a population size of a few hundred. To investigate the factors shaping genetic diversity in the species, we assembled a reference genome for the related Eurasian skylark and then assessed genomic diversity and demographic history using RAD-seq data (26 Raso lark samples and 52 samples from its two most closely related mainland species). Genetic diversity in the Raso lark is lower than in its mainland relatives, but is nonetheless considerably higher than anticipated given its recent population size. This is partly explained by an unusual and dramatic effect of enlarged neo-sex chromosomes, which preserve high heterozygosity across 13% of the genome in females, and account for half of the overall genetic diversity in the population. In addition, by reconstructing past demography we find that genetic signatures of the recent population contraction are overshadowed by an ancient expansion and persistence of a very large population until the human settlement of Cape Verde. Nevertheless, relatedness analyses suggest that the population is at risk of inbreeding depression. Our findings are particularly important in that they reveal the hidden effects of genome architecture in shaping diversity estimates, and hence demonstrate the value of a reference genome and population genomic analyses over conventional metrics to study diversity in non-model and endangered species.

opencc-zeroDec 2019View details →

Data from: Using genetic relatedness to understand heterogeneous distributions of urban rat-associated pathogens

Urban Norway rats (Rattus norvegicus) carry several pathogens transmissible to people. However, pathogen prevalence can vary across fine spatial scales (i.e., by city block). Using a population genomics approach, we sought to describe rat movement patterns across an urban landscape, and to evaluate whether these patterns align with pathogen distributions. We genotyped 605 rats from a single neighborhood in Vancouver, Canada and used 1,495 genome-wide single nucleotide polymorphisms to identify parent-offspring and sibling relationships using pedigree analysis. We resolved 1,246 pairs of relatives, of which only 1% of pairs were captured in different city blocks. Relatives were primarily caught within 33 meters of each other leading to a highly leptokurtic distribution of dispersal distances. Using binomial generalized linear mixed models we evaluated whether family relationships influenced rat pathogen status with the bacterial pathogens Leptospira interrogans, Bartonella tribocorum, and Clostridium difficile, and found that an individual's pathogen status was not predicted any better by including disease status of related rats. The spatial clustering of related rats and their pathogens lends support to the hypothesis that spatially restricted movement promotes the heterogeneous patterns of pathogen prevalence evidenced in this population. Our findings also highlight the utility of evolutionary tools to understand movement and rat-associated health risks in urban landscapes.

opencc-by-4.0Jun 2020View details →

Experimental data to the publication "Genetic-optimised aperiodic code for distributed optical fibre sensors"

The source data underlying Figs. 3-5 and Supplementary Figs. 6, 8-14 are provided as a Source Data file.

opencc-by-4.0Nov 2020View details →

Tara Pacific 18S-based coral host genetic analysis data release version 1

This dataset contains 4 tables and 3 sets of figures related to the primary analysis of the 18S metabarcoding sequencing output. This dataset is only concerned with the identity of the coral host (i.e. not additional protist diversity). The samples included in this dataset have a 'sample-material_label' value of 'CORAL' and 'sampling-protocol_label' value of 'SEQ-CS4L'. They represent the coral samples collected at all 32 of the islands visited in the Tara Pacific expedition.