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788 results for “genotypic data”
Microsatellite genotyping data for habitat-linked genetic structure for white-crowned sparrow (Zonotrichia leucophrys): local factors shape population genetic structure
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Expression data from fully-expanded leaflet of Bambara groundnut (S19-3 genotype)
GEO Series GSE75982. Vigna subterranea. 6 samples. Type: Expression profiling by high throughput sequencing.
Mechanisms and disease associations of haplotype-dependent allele specific DNA methylation: genotyping data for the identification of mQTL
GEO Series GSE79254. Homo sapiens. 138 samples. Type: Genome variation profiling by SNP array.
Analyzing whole genome bisulfite sequencing data from highly divergent genotypes
GEO Series GSE87101. Mus musculus. 8 samples. Type: Methylation profiling by high throughput sequencing.
Prediction of antibiotic resistance by large-scale phenotypic and genotypic data
GEO Series GSE59408. Escherichia coli. 42 samples. Type: Expression profiling by array.
Genomic and phenotypic stability of fusion-driven pediatric sarcoma cell lines [Infinium genotyping data]
GEO Series GSE270195. Homo sapiens. 29 samples. Type: Genome variation profiling by genome tiling array.
Genotype data from early passage UACC melanoma cell lines
GEO Series GSE99193. Homo sapiens. 67 samples. Type: SNP genotyping by SNP array; Genome variation profiling by SNP array.
Single-cell eQTL mapping identifies cell type specific genetic control of autoimmune disease [Genotype_data]
GEO Series GSE196829. Homo sapiens. 1104 samples. Type: Genome variation profiling by SNP array.
Affymetrix Mouse Diversity Genotyping Array Data for p53 deficient mice
GEO Series GSE61660. Mus musculus. 162 samples. Type: Genome variation profiling by SNP array; SNP genotyping by SNP array.
Data from: Temperature-dependent development and survival of an invasive genotype of wheat curl mite, Aceria tosichella
<p><strong>Filename: Development.xlsx</strong></p> <p>Variables:</p> <p>1. id_spec - specimen ID<br> 2. temp - temperature of incubation<br> 3. trial - replication ID<br> 4. larv - number of days needed to reach larva stage <br> 5. q_larv - number of days needed to reach quiescent larva stage <br> 6. nymph - number of days needed to reach nymph stage <br> 7. q_nymph - number of days needed to reach quiescent nymph stage <br> 8. adult - number of days needed to reach adult stage <br> 9. egg - number of days needed to oviposit egg of next generation </p> <p><strong>Filename: Survival.xlsx</strong></p> <p>Variables:</p> <p>1. id_spec - specimen ID<br> 2. temp - temperature of incubation<br> 3. time - number of days when individual was observed alive<br> 4. stage - developmental stage which individual reached before death<br> 5. sex - sex of an individual (F - female; M - male; NA - unknown)<br> 6. status - 0 - censored observation; 1 - observed event of death</p>
Genotype_data_NBPGR
<p><strong>Genotyping for the manuscript entitled "Identification of QTLs/defense genes effective at seedling stage against prevailing races of wheat stripe rust in India."</strong></p>
Data from: Interaction of serum vitamin B12 and folate with MTHFR genotypes on risk of ischemic stroke
<p>Abstract Objective We evaluated the interaction of serum folate and vitamin B12 (B12) with methylenetetrahydrofolate reductase (MTHFR) C677T genotypes, on the risk of first ischemic stroke, and on the efficacy of folic acid (FA) treatment in prevention of first ischemic stroke. Methods A total of 20,702 hypertensive adults were randomized to a double-blind treatment of daily enalapril 10mg and FA 0.8mg or enalapril 10mg alone. Participants were followed-up every three months. Results Median values of folate and B12 concentrations at baseline were 8.1 ng/mL and 280.2 pmol/L, respectively. Over a median of 4.5 years, among those not receiving FA, participants with baseline serum B12 and/or serum folate above the median had a significantly lower risk of first ischemic stroke (HR, 0.74; 95%CI: 0.57-0.96), especially in those with MTHFR 677 CC genotype (wild type) (HR, 0.49; 95%CI: 0.31-0.78). FA treatment significantly reduced the risk of first ischemic stroke in participants with both folate and B12 below the median (2.3% in enalapril-folic acid group vs. 3.6% in enalapril-only group; HR, 0.62; 95%CI: 0.46-0.86), particularly in MTHFR 677 CC carriers (1.6% vs. 4.9%; HR, 0.24; 95%CI: 0.11-0.55). However, carriers of TT responded better with both folate and B12 levels above the median (HR, 0.28; 95%CI: 0.10-0.75). Conclusions The risk of first ischemic stroke was significantly higher in hypertensive patients with low levels of both folate and B12. Effect of FA treatment was greatest in patients with low folate and B12 with the CC genotype, and with high folate and B12 with the TT genotype.</p>
Data from: Estimating genotyping errors from genotype and reconstructed pedigree data
1. Genotyping errors are rules rather than exceptions in reality, and are found in virtually all but very small datasets. These errors, even when occurring at an extremely low rate, can derail many genetic analyses such as parentage/sibship assignments and linkage/association studies. 2. Nonetheless, few robust and accurate methods are available for estimating the rate of occurrence of genotyping errors and for identifying individual erroneous genotypes at a locus. Methods based on duplicate genotyping are expensive, and estimate genotype inconsistency rather than error rate at a locus. Methods based on Hardy-Weinberg equilibrium tests have low robustness and low power, and apply only to those particular errors that cause excessive homozygosity. Methods based on pedigrees are powerful, robust and accurate. However, they rely on known and complete pedigrees that are unfortunately rarely available from natural populations in the wild. 3. I proposed a maximum likelihood method to reconstruct pedigrees from genotype data with errors occurring at a roughly estimated (presumed) rate. In this paper, I describe how to use the method and inferred pedigree in estimating allelic dropout (or null allele) rate and false allele rate jointly at each marker locus, in identifying the erroneous genotypes, and in inferring the most likely genotypes at each locus of each individual. I examine the power, accuracy and robustness of the method by extensive simulations, and demonstrate the usefulness of the method by analysing three empirical datasets. 4. It is concluded that, both pedigrees and the rates of genotyping errors at each locus can be reliably estimated from the same genotype data by the same likelihood method, when marker information is sufficient and some sampled individuals are first-degree relatives. The erroneous genotypes are however inferred conservatively, and are reliably detected only when they occur in large families and/or at highly polymorphic loci. Estimation of genotyping error rates per locus and identification of erroneous genotypes of each individual at each locus should be routinely conducted to assess and improve data quality, to highlight markers for optimization of genotyping protocols or for replacement, and to enable the integration of genotyping errors in a robust statistical analysis.
Data from: Using partial genotyping to estimate the genetic and maternal determinants of adaptive traits in a progeny trial of Fagus sylvatica
Understanding the determinants of phenotypic variation is critical to evaluate the ability of traits to evolve in a changing environment. In trees, the genetic component of the phenotypic variance is most often estimated based on maternal progeny tests. However, the lack of knowledge about the paternal relatedness hampers the accurate estimation of additive genetic and maternal effects. Here, we investigate how different methods accounting for paternal relatedness allow the estimation of heritability and maternal determinants of adaptive traits in a natural population of Fagus sylvatica L., presenting non-random mating. Twelve potentially adaptive functional traits were measured in 60 maternal families in a nursery. We genotyped a subset of offspring and of all the potentially reproductive adults in the population at 13 microsatellite markers to infer paternal relationships and to estimate average relatedness within and between maternal families. This relatedness information was then used in family and animal models to estimate the components of phenotypic variance. All the studied traits displayed significant genetic variance and moderate heritability. Maternal effects were detected for the diameter increment, stem volume and bud burst. Comparison of family and animal models showed that unbalanced mating system led to only slight departures from maternal family assumptions in the progeny trial. However, neglecting the significant maternal effects led to an overestimation of the heritability. Overall, we highlighted the usefulness of relatedness pattern analyses using polymorphic molecular markers to accurately analyse tree sibling designs.
Illumina SNP Chip and Sequenom MassARRAY genotype data of Swedish Giant Schnauzers with and without hypothyroidism
<p>In this study, we sought to identify the genetic risk factors potentially involved in the susceptibility to hypothyroidism in the high-risk Giant Schnauzer dog breed. The genotype data generated in the study (Illumina 170k CanineHD Bead Chip, Sequenom MassARRAY high-throughput re-genotyping) proved to be essential for the identification and fine-mapping of a locus associated with protection against canine hypothyroidism.</p>
Data and R scripts for: Variation in phenotypic plasticity across age-at-maturity genotypes in wild Atlantic salmon
<p>Data and R-scripts underlying the statistical analyses of the study. </p>
Genotype data for 91 Braunvieh and 161 Fleckvieh individuals
<h2>Context and methodology </h2> <p>This dataset was created as part of a research project focusing on investigating recombination rates and genomic features for two Swiss cattle breeds and it offers genotypic data for 91 Braunvieh and 161 Fleckvieh individuals, specifically focusing on chromosome 25. </p> <p>Through this dataset, researchers gain insight into genetic variations, including single nucleotide polymorphism (SNPs) and insertions and deletions (INDELs), enabling deeper investigations into breed-specific characteristics.</p> <p>The genotypic data was generated via high-throughput sequencing and genotyping techniques, involving blood sample collection, DNA extraction, and sequencing using Illumina HiSeq X platform. Analysis pipelines, starting with data preprocessing and alignment, followed by variant calling and quality filtering, were employed. The resulting VCF files contain detailed genotype information, serving as a foundation for population genetics studies. These genotype data serve as the foundation for downstream analyses, including the estimation of recombination rates and the investigation of genomic features such as SNP density and GC content in the respective cattle breeds.</p> <h2>Technical details </h2> <p>The dataset consists of four VCF files, each representing genotypic information for a specific subset of individuals within the Braunvieh and Fleckvieh cattle breeds. The VCF files are named according to the breed (Braunvieh or Fleckvieh) and the part number, along with the date of creation (e.g., braunvieh_part1_20072019.vcf). Furthermore, there is a README file describing the VCF files. </p> <p>The VCF files can be opened and viewed using standard text editors, such as Notepad on Windows or TextEdit on macOS. This allows researchers to inspect the contents of the files and understand the structure of the genetic variant data. </p> <p>For more advanced analysis and manipulation of the genotype data, researchers may require bioinformatics software capable of handling VCF files, such as Genome Analysis Toolkit (GATK), SAMtools, or Variant Call Format (VCF) tools. </p> <p>Additionally, software for statistical analysis and visualization, such as R or Python with relevant libraries, may be needed for downstream analysis of the genotype data. </p> <h2>Further details </h2> <p>Please note that the dataset is restricted, and access must be requested for data reuse. </p>
Syngnathus floridae morphometrics and genotyping data
<p>This is the raw data that corresponds to the manuscript "Sexual selection on non-ornamental traits is underpinned by evidence of genetic constraints on sex-biased expression in dusky pipefish" (DOI: <a href="https://doi.org/10.1111/mec.17550">https://doi.org/10.1111/mec.17550</a>). The three .csv datasets contain morphometric data and raw fitness data for all male and female individuals involved in the experiment and the .zip folder contains raw sequencing data.</p> <ol> <li><strong>all_fem_meso_floridae</strong>: contains raw meaures of the different morphometric traits (length, depth, etc.), info about the trial, and collection date/location for all individual female pipefish.</li> <li><strong>all_mal_meso_floridae</strong>: contains raw measures of the different morphometric traits, info about the trial, collection date/location, and pregnancy status for all individual male pipefish.</li> <li><strong>EmbryoParentage</strong>: contains the raw male/female fitness data for all pregnant pipefish. Each row represents a section of a male's pouch and contains information about who the confirmed mother was for each of the genotyped embryos and the total number of developed and undeveloped embryos in that section.</li> <li><strong>genotyping_raw_sequences</strong>: this is a folder that contains all of the raw genotyping files that correspong to all females, males, and embryos from the successful trials. Within the folder is a subfolder for each trial that contains the indivual .fsa for each pipefish adult or embryo.</li> </ol>
Data from: Cost effective microsatellite isolation and genotyping by high throughput sequencing
High throughput sequencing (HTS) has emerged as a valuable tool for the rapid isolation of genetic markers for population genetics and pedigree analysis. HTS-based SNP (single nucleotide polymorphism) genotyping protocols like RAD (Restriction-site associated DNA) sequencing or hybrid capture, allow for the isolation of thousands of markers from any non-model organism. However, these protocols are relatively laborious and expensive and the resulting high marker density is not always necessary. Since HTS technology has also greatly simplified the isolation and genotyping process of microsatellite markers, we develop microsatellite markers as a cost efficient and simple alternative to SNP genotyping. We present low coverage genome sequencing data from seven distantly related spider species (Argiope bruennichi, Larinia jeskovi, Oedothorax restusus, Pisaura mirabilis, Australomisidia ergandros, Cheiracanthium punctorium, Theridion grallator) and show the utility of HTS for microsatellite isolation. We also present a simple Illumina amplicon sequencing protocol to genotype microsatellites from multiplex PCR amplicons in the Hawaiian happy face spider T. grallator. We discuss advantages and drawbacks of the use of microsatellites for a range of research questions, and highlight an unexpectedly fast decay and gain of repeat loci for T. grallator.
Data from: The effects of genotype × phenotype interactions on transcriptional response to silver nanoparticle toxicity in organotypic cultures of murine tracheal epithelial cells
The airway epithelium is critical for maintaining innate and adaptive immune responses, and occupational exposures that disrupt its immune homeostasis may initiate and amplify airway inflammation. In our previous study, we demonstrated that silver nanoparticles (AgNP), which are engineered nanomaterials used in multiple applications but primarily in the manufacturing of many antimicrobial products, induce toxicity in organotypic cultures derived from murine tracheal epithelial cells (MTEC), and those differentiated toward a "Type 2 [T2]-Skewed" phenotype experienced an increased sensitivity to AgNP toxicity, suggesting that asthmatics could be a sensitive population to AgNP exposures in occupational settings. However, the mechanistic basis for this genotype × phenotype interaction (G×P) has yet to be defined. In the present study, we conducted transcriptional profiling using RNA-sequencing (RNA-seq) to predict the enrichment of specific canonical pathways and upstream transcriptional regulators to assist in defining a mechanistic basis for G×P effects on AgNP toxicity. Organotypic cultures were derived from MTEC across two genetically inbred mouse strains (A/J and C57BL/6J mice), two phenotypes ("Normal" and "T2-Skewed"), and one AgNP exposure (an acute 24 h exposure) to characterize G×P effects on transcriptional response to AgNP toxicity. The "T2-Skewed" phenotype was marked by increased pro-inflammatory T17 responses to AgNP toxicity, which are significant predictors of neutrophilic/difficult-to-control asthma and suggests that asthmatics could be a sensitive population to AgNP exposures in occupational settings. This study highlights the importance of considering G×P effects when identifying these sensitive populations, whose underlying genetics or diseases could directly modify their response to AgNP exposures.
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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.