SNP analysis to results (SNPator): a web-based environment oriented to statistical genomics analyses upon SNP data

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SNP analysis to results (SNPator): a web-based environment oriented to statistical genomics analyses upon SNP data

UNLABELLED Single nucleotide polymorphisms (SNPs) are the most widely used marker in studies to assess associations between genetic variants and complex traits or diseases. They are also becoming increasingly important in the study of the evolution and history of humans and other species. The analysis and processing of SNPs obtained thanks to high-throughput technologies imply the time consumin...

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GSEA-SNP: applying gene set enrichment analysis to SNP data from genome-wide association studies

The power of genome-wide SNP association studies is limited, among others, by the large number of false positive test results. To provide a remedy, we combined SNP association analysis with the pathway-driven gene set enrichment analysis (GSEA), recently developed to facilitate handling of genome-wide gene expression data. The resulting GSEA-SNP method rests on the assumption that SNPs underlyi...

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Knowledge-Based Analysis of Genome-Wide SNP Scanning Data

Many million dollar-scale genome-wide association (GWA) studies are currently underway for identifying genetic elements involved in complex disorders. However, prevailing GWA data analysis methods are focusing on the association of individual SNP alleles with a complex disease, although multiple alleles are involved by definition. Available data suggest few SNP alleles can pass the genomewide m...

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Imputed SNP analyses and meta-analysis with snpStats

The need for imputation in SNP analysis studies occurs when we have a smaller set of samples in which a large number of SNPs have been typed, and a larger set of samples typed in only a subset of the SNPs. We use the smaller, complete dataset (which will be termed the training dataset) to impute the missing SNPs in the larger, incomplete dataset (the target dataset). Examples of such applicatio...

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Correcting coalescent analyses for panel-based SNP ascertainment.

Single-nucleotide polymorphism (SNP) data are routinely obtained by sequencing a region of interest in a small panel, constructing a chip with probes specific to sites found to vary in the panel, and using the chip to assay subsequent samples. The size of the chip is often reduced by removing low-frequency alleles from the set of SNPs. Using coalescent estimation of the scaled population size p...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2008

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/btn241