Gene-set distance analysis (GSDA): a powerful tool for gene-set association analysis
نویسندگان
چکیده
منابع مشابه
Gene and Gene-Set Analysis for Genome-Wide Association Studies
Genome-wide association studies (GWAS) have identified hundreds of loci at very stringent levels of statistical significance across many different human traits. However, it is now clear that very large samples (n~104-105) are needed to find the majority of genetic variants underlying risk for most human diseases. Therefore, the field has engaged itself in a race to increase study sample sizes w...
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Gene expression microarray technologies provide the simultaneous measurements of a large number of genes. Typical analyses of such data focus on the individual genes, but recent work has demonstrated that evaluating changes in expression across predefined sets of genes often increases statistical power and produces more robust results. We introduce a new methodology for identifying gene sets th...
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Genome wide association studies (GWAS) have emerged as popular tools for identifying genetic variants that are associated with disease risk. Standard analysis of a case-control GWAS involves assessing the association between each individual genotyped SNP and disease risk. However, this approach suffers from limited reproducibility and difficulties in detecting multi-SNP and epistatic effects. A...
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Although techniques of chromatin immunoprecipitation coupled with high throughput sequencing (ChIP-seq) or tiling array hybridization (ChIP-chip) have came into being for a long time, it still remains difficult to generate a quality ChIPx (i.e., ChIP-seq or ChIP-chip) data set due to the tremendous amount of effort required to develop effective antibodies and efficient protocols. Especially wit...
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Gene-set analysis aims to identify differentially expressed gene sets (pathways) by a phenotype in DNA microarray studies. We review here important methodological aspects of gene-set analysis and illustrate them with varying performance of several methods proposed in the literature. We emphasize the importance of distinguishing between 'self-contained' versus 'competitive' methods, following Go...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2021
ISSN: 1471-2105
DOI: 10.1186/s12859-021-04110-x