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92 results for “pedigrees”
Characterization of expression quantitative trait loci in extensively phenotyped pedigrees from Colombia and Costa Rica
GEO Series GSE82042. Homo sapiens. 786 samples. Type: Expression profiling by array.
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.
Characterization Of Coronary Prone Pedigrees
ClinicalTrials.gov study NCT00005139. IPD Sharing: Not stated. Countries: 0. Publications: 48.
Data from: Measuring individual inbreeding in the age of genomics: marker-based measures are better than pedigrees
Open the record for dataset details and reuse information.
Data from: Estimating genotyping errors from genotype and reconstructed pedigree data
Open the record for dataset details and reuse information.
Whole genome sequence, SNP chips and pedigree structure
GEO Series GSE90441. Canis lupus familiaris; Canis lupus. 795 samples. Type: SNP genotyping by SNP array; Genome variation profiling by SNP array.
Transcriptome analysis of a breeding program pedigree
GEO Series GSE24534. Hordeum vulgare. 90 samples. Type: Expression profiling by array.
Gene expression levels in immortalized B cells from members of 45 CEPH-Utah pedigrees
GEO Series GSE16778. Homo sapiens. 695 samples. Type: Expression profiling by array.
Transcriptome-based profiling reveals a macrophage pedigree and identifies Irf8 as pivotal for macrophage homeostasis and function
GEO Series GSE73125. Mus musculus. 81 samples. Type: Expression profiling by array.
Pedigreed Primate Embryonic Stem Cells Express Homogeneous Familial Gene Profiles
GEO Series GSE7534. Macaca mulatta. 27 samples. Type: Expression profiling by array.
Pedigree Study and Functional Analysis of Novel Germline p. R21Afs MEN1 Mutation in a Multiple Endocrine Neoplasia Type 1 Family
GEO Series GSE221993. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Preliminary assemblies of the three-generational pedigree of African-American ancestry
<p>Monika Cechova<sup>1</sup>, Sergey Koren<sup>2</sup>, Julian K. Lucas<sup>1</sup>, Rebecca Serra Mari<sup>3</sup>, Mobin Asri<sup>1</sup>, David Porubsky<sup>4</sup>, Jordan M. Eizenga<sup>1</sup>, Brandy McNulty<sup>1</sup>, Andrey Bzikadze<sup>5</sup>, Christopher Markovic<sup>6</sup>, Tamara Potapova<sup>7</sup>, Jennifer L. Gerton<sup>7</sup>, Pavel A. Pevzner<sup>8</sup>, Evan E. Eichler<sup>4</sup>, Benedict Paten<sup>1</sup>, Adam M. Phillippy<sup>2</sup>, Ting Wang<sup>9</sup>, Nathan O. Stitziel<sup>10</sup> , Robert S. Fulton<sup>6</sup>, Tobias Marschall<sup>3</sup>, Karen H. Miga<sup>1</sup></p> <p> </p> <p><sup>1</sup> UC Santa Cruz Genomics Institute, University of California, Santa Cruz, 1156 High St, Santa Cruz, CA, USA</p> <p><sup>2</sup> Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA</p> <p><sup>3</sup> Institute for Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany</p> <p><sup>4</sup> Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA</p> <p><sup>5</sup> Graduate Program in Bioinformatics and Systems Biology, University of California San Diego, San Diego, CA, USA</p> <p><sup>6</sup> McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO 63108, USA</p> <p><sup>7</sup> Stowers Institute for Medical Research, Kansas City, MO, USA</p> <p><sup>8</sup> Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA</p> <p><sup>9 </sup>Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA</p> <p><sup>10</sup> Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA</p>
ScienceDex guides
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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.