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Showing 1 to 8 of 8 for “"Genotype Calling"”.

  1. Bioinformatics framework for genotyping microarray data analysis

    … analysis. Genotyping microarrays establish the genotypes of DNA sequences containing single nucleotide polymorphisms (SNPs), and can help biologists probe the functions of different genes and/or construct complex gene interaction networks. The enormous amount of data from these experiments makes …

    njit Repository record for Bioinformatics framework for genotyping microarray data analysis (opens in a new tab)

  2. Linear clustering with application to single nucleotide polymorphism genotyping

    … technologies usually involves a statistical genotype calling algorithm. Most calling algorithms in the literature, using methods such as k-means and mixturemodels, rely on elliptical structures of the genotyping data; they may fail when the minor allele homozygous cluster is small or absent, …

    ubc Repository record for Linear clustering with application to single nucleotide polymorphism genotyping (opens in a new tab)

  3. Navigating through the uncertainty of genotyping-by-sequencing data in polyploids

    … species, including polyploids. Variant and genotype calling methods have been established for autopolyploids but for a species with a complex genome, such as sugarcane, the level of uncertainty within GBS data increases making trait mapping difficult. Furthermore, variant and genotype

    uiuc Repository record for Navigating through the uncertainty of genotyping-by-sequencing data in polyploids (opens in a new tab)

  4. High-throughput Amplicon Sequencing Optimization for Downstream Prediction Purposes

    … of a commerical FDP assay, MiSeq FGx sequencing, genotype calling, and quality and ancestry inference assessments. The substantial dataset produced with this project will supply downstream applications in pigmentation and facial morphology prediction modeling. This work also advances FDP toward …

    iupui Repository record for High-throughput Amplicon Sequencing Optimization for Downstream Prediction Purposes (opens in a new tab)

  5. Variant Detection Using Next Generation Sequencing Data

    … (deletions and inversions) and to infer accurate genotypes from multiple genotype and SNP calling algorithms using NGS. For structure variant detection, we propose a model based clustering approach utilizing a set of features defined for each type of SV events. Our method, termed SVMiner, not only …

    ohiolink Repository record for Variant Detection Using Next Generation Sequencing Data (opens in a new tab)

  6. Haplotype-Informed Allelic Imbalance Detection From Rna In Cancer

    … in The Cancer Genome Atlas (TCGA), inferring genotypes directly from RNA-sequencing (RNA-seq). This resulted in an SCNA detection rate of 68%. Encouraged by this, we next leveraged large public genetic reference data and array derived germline genotypes, from matched blood samples, to impute …

    uthsc Repository record for Haplotype-Informed Allelic Imbalance Detection From Rna In Cancer (opens in a new tab)

  7. Computational methods for single cell RNA and genome assembly resolution using genetic variation

    … humans and other species and use that to link genotypes with phenotypes and infer evolutionary histories. In this thesis, I explore computational methods for using genetic variation to demultiplex and disambiguate complex data. In single cell RNAseq, problems of batch effects, doublets, and …

    cambridge Repository record for Computational methods for single cell RNA and genome assembly resolution using genetic variation (opens in a new tab)