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320 results for “SNP array”
Data from: SNP-array reveals genome wide patterns of geographical and potential adaptive divergence across the natural range of Atlantic salmon (Salmo salar)
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Data from: Estimation of linkage disequilibrium and interspecific gene flow in Ficedula flycatchers by a newly developed 50k SNP array
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Data from: Inferences of genetic architecture of bill morphology in house sparrow using a high‐density SNP array point to a polygenic basis
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SNP array for parentage assignment of the Manila clam, Ruditapes philippinarum
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Genome wide IStraw90 SNP array probes
<p>The University of Florida strawberry (<i>Fragaria</i> ×<i>ananassa</i>) breeding program has implemented genomic prediction (GP) as a tool for choosing outstanding parents for crosses over the last five seasons. This has allowed the use of some parents one year earlier than with traditional methods, thus reducing the duration of the breeding cycle. However, as the number of breeding cycles increases over time, greater knowledge is needed on how multiple cycles can be used in the practical implementation of GP in strawberry breeding. Advanced selections and cultivars totaling 1,558 unique individuals were tested in field trials for yield and fruit quality traits over five consecutive years and genotyped for 9,908 SNP markers. Prediction of breeding values was carried out using Bayes B models. Independent validation was carried out using separate trials/years as training (TRN) and testing (TST) populations. Single-trial predictive abilities for five polygenic traits averaged 0.35, which was reduced to 0.24 when individuals common across trials were excluded, emphasizing the importance of relatedness among training and testing populations. Training populations including up to four previous breeding cycles increased predictive abilities, likely due to increases in both training population size and relatedness. Predictive ability was also strongly influenced by heritability, but less so by changes in linkage disequilibrium and effective population size. Genotype by year interactions were minimal. A strategy for practical implementation of GP in strawberry breeding is outlined that uses multiple cycles to predict parental performance and accounts for traits not included in GP models when constructing crosses. Given the importance of relatedness to the success of GP in strawberry, future work could focus on the optimization of relatedness in the design of TRN and TST populations to increase predictive ability in the short-term without compromising long-term genetic gains.</p>
Data from: Vitis phylogenomics: hybridization intensities from a SNP array outperform genotype calls
Understanding relationships among species is a fundamental goal of evolutionary biology. Single nucleotide polymorphisms (SNPs) identified through next generation sequencing and related technologies enable phylogeny reconstruction by providing unprecedented numbers of characters for analysis. One approach to SNP-based phylogeny reconstruction is to identify SNPs in a subset of individuals, and then to compile SNPs on an array that can be used to genotype additional samples at hundreds or thousands of sites simultaneously. Although powerful and efficient, this method is subject to ascertainment bias because applying variation discovered in a representative subset to a larger sample favors identification of SNPs with high minor allele frequencies and introduces bias against rare alleles. Here, we demonstrate that the use of hybridization intensity data, rather than genotype calls, reduces the effects of ascertainment bias. Whereas traditional SNP calls assess known variants based on diversity housed in the discovery panel, hybridization intensity data survey variation in the broader sample pool, regardless of whether those variants are present in the initial SNP discovery process. We apply SNP genotype and hybridization intensity data derived from the Vitis9kSNP array developed for grape to show the effects of ascertainment bias and to reconstruct evolutionary relationships among Vitis species. We demonstrate that phylogenies constructed using hybridization intensities suffer less from the distorting effects of ascertainment bias, and are thus more accurate than phylogenies based on genotype calls. Moreover, we reconstruct the phylogeny of the genus Vitis using hybridization data, show that North American subgenus Vitis species are monophyletic, and resolve several previously poorly known relationships among North American species. This study builds on earlier work that applied the Vitis9kSNP array to evolutionary questions within Vitis vinifera and has general implications for addressing ascertainment bias in array-enabled phylogeny reconstruction.
Data from: A 34K SNP genotyping array for Populus trichocarpa: Design, application to the study of natural populations and transferability to other Populus species
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Data from: Vitis phylogenomics: hybridization intensities from a SNP array outperform genotype calls
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Genome wide IStraw90 SNP array probes
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Data from: Development of SNP genotyping arrays in two shellfish species
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SNP array for CNV calling AUTS2 project [Illumina]
GEO Series GSE37142. Homo sapiens. 1 samples. Type: Genome variation profiling by SNP array.
Affymetrix SNP array data for analysis of peanut agronomic traits
GEO Series GSE197103. Arachis hypogaea. 333 samples. Type: SNP genotyping by SNP array; Genome variation profiling by SNP array.
Affymetrix SNP array data for acute lymphoblastic leukemia samples
GEO Series GSE42056. Homo sapiens. 40 samples. Type: Genome variation profiling by SNP array.
Affymetrix SNP array data for Non-Smoking Female Lung Cancer in Taiwan
GEO Series GSE33355. Homo sapiens. 122 samples. Type: Genome variation profiling by SNP array; SNP genotyping by SNP array.
Affymetrix SNP Array data for familial coarctation of the aorta (CoA) I
GEO Series GSE67929. Homo sapiens. 70 samples. Type: Genome variation profiling by SNP array.
SNP array analysis has facilitated the identification of novel chromosomal alterations associated with disease and SNPs related to Adverse Drug Reactions in neuroblastoma
GEO Series GSE288908. Homo sapiens. 45 samples. Type: Genome variation profiling by SNP array.
A novel chordoma xenograft allows in vivo drug testing and reveals the importance of NF-kB signaling in chordoma biology [SNP array]
GEO Series GSE50136. Homo sapiens. 2 samples. Type: Genome variation profiling by SNP array.
Affymetrix SNP array data for squamous cell carcinoma of base of tongue and healthy individuals samples
GEO Series GSE46812. Homo sapiens. 98 samples. Type: SNP genotyping by SNP array.
SNP array data of breast cancer
GEO Series GSE19594. Homo sapiens. 88 samples. Type: SNP genotyping by SNP array; Genome variation profiling by SNP array.
Affymetrix SNP array data for chicken samples
GEO Series GSE127968. Gallus gallus. 1193 samples. Type: SNP genotyping by SNP array; Genome variation profiling by SNP array.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.