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1,007 results for “single use”
Data and code info for: Reducing single-use cutlery with green nudges: Evidence from China’s food delivery industry
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Assessing gene flow between Dicranum scoparium Hedw. and D. bonjeanii De Not. (Dicranaceae) using single nucleotide polymorphisms (SNPs)
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High-density single-unit human cortical recordings using the Neuropixels probe
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Synthetic Datasets for Using synthetic datasets to bridge the gap between the promise and reality of basing health-related decisions on common single nucleotide polymorphisms
<p>Synthetic Dataset for Using synthetic datasets to bridge the gap between the promise and reality of basing health-related decisions on common single nucleotide polymorphisms, as published on F1000Research.</p>
Predicting plasmid contigs from assemblies using single copy marker genes, plasmid genes, kmers
<p>Introduction: Antimicrobial resistant (AMR) genes in bacteria are often carried on plasmids. Since these plasmids can spread the AMR genes between bacteria, it is important to know if the genes are located on highly transferable plasmids or in the more stable chromosomes. Whole genome sequence (WGS) analysis makes it easy to determine if a strain contains a resistance gene, however, it is not easy to determine if the gene is located on the chromosome or on a plasmid as genome sequence assembly generally results in 50-300 DNA fragments (contigs). With our newly developed prediction tool, we analyze the composition of these contigs to predict their likely source, plasmid or chromosomal. This information can be used to determine if a resistant gene is chromosomally located or on a plasmid. The tool is optimized for 19 different bacterial species, including Campylobacter, E. coli, and Salmonella, and can also be used for metagenomic assemblies.</p> <p>Methods: The tool identifies the number of chromosomal marker genes, plasmid replication genes and plasmid typing genes using CheckM and DIAMOND Blast, and determines pentamer frequencies and contig sizes per contig. A prediction model was trained using Random Forest on an extensive set of plasmids and chromosomes from 19 different bacterial species and validated on separate test sets of known chromosomal and plasmid contigs of the different bacteria. Results: Prediction of plasmid contigs was nearly perfect when calculated based on number of correctly predicted bases, with up to 99% specificity and 99% sensitivity. Prediction of small contigs remains difficult, since these contigs consists primarily of repeated sequences present in both plasmid and chromosome, e.g. transposases.</p> <p>Conclusion: The newly developed tool is able to determine if contigs are chromosomal or plasmid with a very high specificity and sensitivity (up to 99%) and can be very useful to analyze WGS data of bacterial genomes and their antimicrobial resistance genes.</p> <p>Plasmid databases can be downloaded from: http://klif.uu.nl/download/plasmid_db/</p> <p>Data used for training can be downloaded here: http://klif.uu.nl/download/plasmid_db/trainingsets2/</p>
Data for: Model-Based Reconstruction for Simultaneous Multi-Slice T1 Mapping using Single-Shot Inversion-Recovery Radial FLASH
<p>Magnetic Resonance Imaging measurement data used in our paper about "Model-based reconstruction for simultaneous multi-slice T1 mapping using single-shot inversion-recovery radial FLASH" (DOI: <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/mrm.28497">10.1002/mrm.28497</a>). The data is provided in a file format used by the BART toolbox (DOI: <a href="http://doi.org/10.5281/zenodo.592960">10.5281/zenodo.592960</a>).</p>
Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis
<p>Native cattle breeds can carry specific signatures of selection reflecting their adaptation to the local environmental conditions and response to the breeding strategy used. In this study, we comprehensively analysed high-density single nucleotide polymorphism (SNP) genotypes to characterise the population structure and detect the selection signatures in Russian native Yaroslavl and Kholmogor dairy cattle breeds, which have been little influenced by introgression with transboundary breeds. Fifty-six samples of pedigree-recorded purebred animals, originating from different breeding farms and representing different sire lines, of the two studied breeds were genotyped using a genome-wide bovine genotyping array (Bovine HD BeadChip). Three statistical analyses—calculation of fixation index (<i>F</i><sub>ST</sub>) for each SNP for the comparison of the pairs of breeds, hapFLK analysis, and estimation of the runs of homozygosity (ROH) islands shared in more than 50% of animals—were combined for detecting the selection signatures in the genome of the studied cattle breeds. We confirmed nine and six known regions under putative selection in the genomes of Yaroslavl and Kholmogor cattle, respectively; the flanking positions of most of these regions were elucidated. Only two of the selected regions (localised on BTA 14 at 24.4–25.1 Mbp and on BTA 16 at 42.5–43.5 Mb) overlapped in Yaroslavl, Kholmogor and Holstein breeds. In addition, we detected three novel selection sweeps in the genome of Yaroslavl (BTA 4 at 4.74–5.36 Mbp, BTA 15 at 17.80–18.77 Mbp, and BTA 17 at 45.59–45.61 Mbp) and Kholmogor breeds (BTA 12 at 82.40–81.69 Mbp, BTA 15 at 16.04–16.62 Mbp, and BTA 18 at 0.19–1.46 Mbp) by using at least two of the above-mentioned methods. We expanded the list of candidate genes associated with the selected genomic regions and performed their functional annotation. We discussed the possible involvement of the identified candidate genes in artificial selection in connection with the origin and development of the breeds. Our findings on the Yaroslavl and Kholmogor breeds obtained using high-density SNP genotyping and three different statistical methods allowed the detection of novel putative genomic regions and candidate genes that might be under selection. These results might be useful for the sustainable development and conservation of these two oldest Russian native cattle breeds.</p>
Multi-Domain Translation between Single-Cell Imaging and Sequencing Data using Autoencoders
<p>This record contains raw data related to the article "Multi-Domain Translation between Single-Cell Imaging and Sequencing Data using Autoencoders".</p>
Prediction of femoral osteoporosis using machine-learning analysis with radiomics features and abdomen-pelvic CT: A retrospective single center preliminary study
<p>Dataset of prediction of osteoporosis using APCT, radiomics and machine learning analysis.</p>
Data from: Identifying litchi (Litchi chinensis Sonn.) cultivars and their genetic relationships using single nucleotide polymorphism (SNP) markers
Litchi is an important fruit tree in tropical and subtropical areas of the world. However, there is widespread confusion regarding litchi cultivar nomenclature and detailed information of genetic relationships among litchi germplasm is unclear. In the present study, the potential of single nucleotide polymorphism (SNP) for the identification of 96 representative litchi accessions and their genetic relationships in China was evaluated using 155 SNPs that were evenly spaced across litchi genome. Ninety SNPs with minor allele frequencies above 0.05 and a good genotyping success rate were used for further analysis. A relatively high level of genetic variation was observed among litchi accessions, as quantified by the expected heterozygosity (He = 0.305). The SNP based multilocus matching identified two synonymous groups, 'Heiye' and 'Wuye', and 'Chengtuo' and 'Baitangli 1'. A subset of 14 SNPs was sufficient to distinguish all the non-redundant litchi genotypes, and these SNPs were proven to be highly stable by repeated analyses of a selected group of cultivars. Unweighted pair-group method of arithmetic averages (UPGMA) cluster analysis divided the litchi accessions analyzed into four main groups, which corresponded to the traits of extremely early-maturing, early-maturing, middle-maturing, and late-maturing, indicating that the fruit maturation period should be considered as the primary criterion for litchi taxonomy. Two subpopulations were detected among litchi accessions by STRUCTURE analysis, and accessions with extremely early- and late-maturing traits showed membership coefficients above 0.99 for Cluster 1 and Cluster 2, respectively. Accessions with early- and middle-maturing traits were identified as admixture forms with varying levels of membership shared between the two clusters, indicating their hybrid origin during litchi domestication. The results of this study will benefit litchi germplasm conservation programs and facilitate maximum genetic gains in litchi breeding programs.
Data from: Reliable genotyping of the koala (Phascolarctos cinereus) using DNA isolated from a single faecal pellet
The koala, an Australian icon, has been added to the threatened species list. Rationale for the listing includes proposed declines in population size, threats to populations (e.g. disease) and loss and fragmentation of habitat. There is now an urgent need to obtain accurate data to assess the status of koala populations in Australia, to ensure the long-term viability of this species. Advances in genetic techniques have enabled DNA analysis to study and inform the management of wild populations; however, sampling of individual koalas is difficult in tall, often remote, eucalypt forest. The collection of faecal pellets (scats) from the forest floor presents an opportunistic sampling strategy, where DNA can be collected without capturing or even sighting an individual. Obtaining DNA via noninvasive sampling can be used to rapidly sample a large proportion of a population; however, DNA from noninvasively collected samples is often degraded. Factors influencing DNA quality and quantity include environmental exposure, diet and methods of sample collection, storage and DNA isolation. Reduced DNA quality and quantity can introduce genotyping errors and provide inaccurate DNA profiles, reducing confidence in the ability of such data to inform management/conservation strategies. Here, we present a protocol that produces a reliable individual koala genotype from a single faecal pellet and highlight the importance of optimizing DNA isolation and analysis for the species of interest. This method could readily be adapted for genetic studies of mammals other than koalas, particularly those whose diet contains high proportions of volatile materials that are likely to induce DNA damage.
Data from: Using ABC and microsatellite data to detect multiple introductions of invasive species from a single source
The introduction of invasive species to new locations (that is, biological invasions) can have major impact on biodiversity, agriculture and public health. As such, determining the routes and modality of introductions with genetic data has become a fundamental goal in molecular ecology. To assist with this goal, new statistical methods and frameworks have been developed, such as approximate Bayesian computation (ABC) for inferring invasion history. Here, we present a model of invasion accounting for multiple introductions from a single source (MISS), a heretofore largely unexplored model. We simulate microsatellite data to evaluate the power of ABC to distinguish between single and multiple introductions from the same source, under a range of demographic parameters. We also apply ABC to microsatellite data from three invasions of bumblebee in New Zealand. In addition, we assess the performance of several methods of summary statistics selection. Our simulated results suggested good ability to distinguish between one- and two-wave models over much but not all of the parameter space tested, independent of summary statistics used. Globally, parameter estimation was good except for bottleneck timing. For one of the bumblebee species, we clearly rejected the MISS model, while for the other two we found inconclusive results. Since a second wave may provide genetic reinforcement to initial colonists, help relieve inbreeding among founders, or increase the hazard of the invasion, its detection may be crucial for managing invasions; we suggest that the MISS model could be considered as a potential model in future theoretical and empirical studies of invasions.
Data from: Monitoring the effective population size of a brown bear (Ursus arctos) population using new single-sample approaches
The effective population size (Ne) could be the ideal parameter for monitoring populations of conservation concern as it conveniently summarizes both the evolutionary potential of the population and its sensitivity to genetic stochasticity. However, tracing its change through time is difficult in natural populations. We applied four new methods for estimating Ne from a single sample of genotypes to trace temporal change in Ne for bears in the Northern Dinaric Mountains. We genotyped 510 bears using 20 microsatellite loci, and determined their age. The samples were organized into cohorts with regard to the year when the animals were born and yearly samples with age categories for every year when they were alive. We used the Estimator by Parentage Assignment (EPA) to directly estimate both Ne and generation interval for each yearly sample. For cohorts, we estimated the effective number of breeders (Nb) using Linkage Disequilibrium, Sibship Assignment and Approximate Bayesian Computation methods, and extrapolated these estimates to Ne using the generation interval. The Ne estimate by EPA is 276 (183-350 95% CI), meeting the inbreeding-avoidance criterion of Ne > 50 but short of the long-term minimum viable population goal of Ne > 500. The results obtained by the other methods are highly consistent with this result, and all indicate a rapid increase in Ne probably in the late 1990s and early 2000s. The new single-sample approaches to estimation of Ne provide efficient means for including Ne in monitoring frameworks, and will be of great importance for future management and conservation.
Data from: Development of nuclear microsatellite loci and mitochondrial single nucleotide polymorphisms for the natterjack toad, Bufo (Epidalea) calamita (Bufonidae), using next generation sequencing and Competitive Allele Specific PCR (KASPar)
Amphibians are undergoing a major decline worldwide and the steady increase in the number of threatened species in this particular taxa highlights the need for conservation genetics studies using high-quality molecular markers. The natterjack toad, Bufo (Epidalea) calamita, is a vulnerable pioneering species confined to specialized habitats in Western Europe. To provide efficient and cost-effective genetic resources for conservation biologists, we developed and characterized 22 new nuclear microsatellite markers using next-generation sequencing. We also used sequence data acquired from Sanger sequencing to develop the first mitochondrial markers for KASPar assay genotyping. Genetic polymorphism was then analyzed for 95 toads sampled from 5 populations in France. For polymorphic microsatellite loci, number of alleles and expected heterozygosity ranged from 2 to 14 and from 0.035 to 0.720, respectively. No significant departures from panmixia were observed (mean multilocus F IS = −0.015) and population differentiation was substantial (mean multilocus F ST = 0.222, P < 0.001). From a set of 18 mitochondrial SNPs located in the 16S and D-loop region, we further developed a fast and cost-effective SNP genotyping method based on competitive allele-specific PCR amplification (KASPar). The combination of allelic states for these mitochondrial DNA SNP markers yielded 10 different haplotypes, ranging from 2 to 5 within populations. Populations were highly differentiated (G ST = 0.407, P < 0.001). These new genetic resources will facilitate future parentage, population genetics and phylogeographical studies and will be useful for both evolutionary and conservation concerns, especially for the set-up of management strategies and the definition of distinct evolutionary significant units.
Data from: Conserved genetic regions across angiosperms as tools to develop single copy nuclear markers in gymnosperms: an example using cycads
Several individuals of the Caribbean Zamia clade and other cycad genera were used to identify single copy nuclear genes for phylogeographic and phylogenetic studies in Cycadales. Two strategies were employed to select target loci: 1) a tblastX search of Arabidopsis conserved ortholog sequence (COS) set and, 2) a tblastX search of Arabidopsis-Populus-Vitis-Oryza Shared Single Copy genes (APVO SSC) against the EST Zamia databases in Genbank. From the first strategy, 30 loci were selected, and from the second, 16 loci. In both cases the matching Genbank accessions of Zamia were used as a query for retrieving highly similar sequences from Cycas, Picea, Pinus species or Ginko biloba. After retrieving and aligning all the sequences in each locus, intron predictions were completed to assist in primer design. PCR was carried out in three rounds to detect paralogous loci. A total of 29 loci were successfully amplified as a single band of which 20 were likely single copy loci. These loci showed different diversity and divergence levels. A preliminary screening allowed us to select 8 promising loci (40S, ATG2, BG, GroES, GTP, LiSH, PEX4 and TR) for the Z. pumila complex and 4 loci (COS26, GroES, GTP and HTS) for all other cycad genera.
Data from: Genome-wide single nucleotide polymorphism (SNP) identification and characterization in a non-model organism, the African buffalo (Syncerus caffer), using next generation sequencing
This study aimed to develop a set of SNP markers with high resolution and accuracy within the African buffalo. Such a set can be used, among others, to depict subtle population genetic structure for a better understanding of buffalo population dynamics. In total, 18.5 million DNA sequences of 76 bp were generated by next generation sequencing on an Illumina Genome Analyzer II from a reduced representation library using DNA from a panel of 13 African buffalo representative of the four subspecies. We identified 2534 SNPs with high confidence within the panel by aligning the short sequences to the cattle genome (Bos taurus). The average sequencing depth of the complete aligned set of reads was estimated at 5x, and at 13x when only considering the final set of putative SNPs that passed the filtering criterion. Our set of SNPs was validated by PCR amplification and Sanger sequencing of 15 SNPs. Of these 15 SNPs, 14 amplified successfully and 13 were shown to be polymorphic (success rate: 87%). The fidelity of the identified set of SNPs and potential future applications are finally discussed.
Synthesis of arbitrary interference patterns using a single galvanometric mirror
<h3>Version 1</h3> <p>CAD model</p> <p>Speed accessment images (images of fluorescent beads using 100 X microscope) and postprocessing code in MATLAB</p> <p>Laser interference images and postprocessing code in MATLAB</p> <ul> <li>Two beam and hexagonal pattern images were repeated multiple times</li> <li>Three beam images were taken at different axial positions</li> </ul> <p>2D SIM data with 100 nm fluorescent beads (two examples, <em>2D 1ms 980Hz 400mW.tiff </em>and <em>2D 1ms 980Hz 400mW.tiff</em>, not TIRF) and reconstruction code in MATLAB (<em>SIM_reconstrcution_2D.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>The camera jittered during the measurements. The images were shifted to cancel the jitter using <a href="https://uk.mathworks.com/matlabcentral/fileexchange/18401-efficient-subpixel-image-registration-by-cross-correlation">Efficient subpixel image registration by cross-correlation - File Exchange - MATLAB Central</a>. For comparison, two images are reconstructed, with and without cancelling the jitter </li> <li>Each set of measurement contain multiple cycles of 11 frames, of which the 4th and 8th frames are discarded</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2_KG.m</em></li> <li>For reference, the images are averaged and have the PSF deconvolved using <em>deconv_Wiener_KG.m</em></li> </ul> <p>3D SIM data (<em>3D cell cropped.tiff), </em>widefield reference data (<em>WF cropped.tiff</em>) and reconstruction code in MATLAB (<em>SIM3D_cells.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>Parameters are estimated from a subset of the image (which has higher SNR) using function <em>estimate_sim_parameters_3D_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim_3D_KG.m</em></li> <li>For reference, a widefield 3D image was captured by only illuminating the sample with one laser beam. The image is further processed using <em>WF3D_cells.m</em> and function <em>deconv_3D.m </em>to deconvolve the OTF</li> <li>The theorectial OTF is calculated using code from <a href="https://github.com/jdmanton/debye_diffraction_code">https://github.com/jdmanton/debye_diffraction_code</a> which is included in the package</li> </ul> <h3>Version 2</h3> <p>2D TIRF SIM data with 100 nm fluorescent beads (same as Version 3) and reconstruction code in MATLAB. I forgot to upload background noise image. Please use Version 3 to avoid error in running the code</p> <h3>Version 3 </h3> <p>2D TIRF SIM data with 100 nm fluorescent beads (same as Version 2) and reconstruction code including FRC in MATLAB (<em>main.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>Raw data include two sets of measurements (<em>TIRF beads.tiff and TIRF beads 2.tiff</em>) and background noise image (<em>bg 1ms.tiff</em>)</li> <li>Each set of measurement (e.g. <em>TIRF beads.tiff</em>) contain two cycles of 11 frames, of which the 4th and 8th frames are discarded in each cycle</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2D_KG.m</em></li> <li>For reference, the images are averaged and have the PSF deconvolved using <em>deconv_Wiener_KG.m</em></li> </ul> <p>3D SIM data (same as Version 1) and reconstruction code for FRC in MATLAB (<em>main.m</em>)</p> <ul> <li>Use <em>set_default_figure_parameters.m </em>to set the default figure unit to cm</li> <li>Two subsets of the image were taken for FRC, one with even z steps and one with odd z steps</li> <li>Parameters are estimated using function <em>estimate_sim_parameters_KG.m</em></li> <li>Images are reconstructed using function <em>reconstruct_sim2D_KG.m</em></li> <li>The two subsets are reconstructed independently (double z step size) and the centre z position of each image are used to calculate FRC</li> <li>Only subsets of the image are processed. Refer to Version 1 for larger range in z.</li> </ul> <p>Stability accessment images (two beam laser interference images taken over periods of time) and postprocessing code in MATLAB</p> <p>2D SIM (not TIRF) data with 200 nm fluorescent beads measured over the full FOV and reconstruction code in MATLAB</p> <ul> <li>Processed in almost the same way as 2D TIRF SIM</li> <li>Parameters were estimated using the centre of the FOV</li> <li>Sections with ~10 um horizontal distances are plotted to show change of quality across the FOV</li> </ul> <p>PSF data measured using 200 nm fluorescent beads and postprocessing code in MATLAB</p> <ul> <li>Individual bead images are picked and fit with theoretical PSF function to obtain resolution</li> <li>Beads with ~10 um horizontal distances are plotted to show change of quality across the FOV</li> </ul>
Datasets for MambaCpG: Accurate Imputation of Single-cell DNA Methylation Status Using Mamba
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Clustering-independent estimation of cell abundances in bulk tissues using single-cell RNA-seq data
<p>ConDecon is a clustering-independent method for inferring the likelihood for each cell in a single-cell dataset to be present in a bulk tissue. This repository contains the raw data of the benchmarking analyses presented in the original publication using the pipeline of Avila-Cobos et al. (10.1038/s41467-020-19015-1). We used this pipeline to evaluate the ability of ConDecon and 17 other deconvolution methods to infer discrete cell type abundances in bulk tissues. The compressed file in this repository contains the synthetic bulk data, ground truth cell type proportions, and the predicted cell type proportions for each method and dataset associated with these analyses. Additional details can be found in the Methods section of the ConDecon publication.</p>
Raw Data and Scripts used in Regulation of single-cell heterogeneity of capsular polysaccharide synthesis in a human gut symbiont
<p>Raw data used in this publication. Single-cell analysis of promoter inversions reveals differential inversion rates as a determinant of bacterial population heterogeneity.</p> <p> </p> <p>Libx.zip contains raw sequencing reads</p> <p>scripts.zip contains code for analysis of reads and growth curve data</p> <p>SequencingRawDataFilesIndex.xls contains a description of all the raw data in each libx.zip.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.