Avoiding the pitfalls of gene set enrichment analysis with setrank. BMC Bioinformatics, 18(1):151, 2017.Cedric Simillion, Robin Liechti, Heidi EL Lischer, Vassilios Ioannidis, and R´emy Bruggmann. Avoiding th
Rank orderplot (or rank-plot) is used to visualize the results of gene set enrichment analysis (Fig. 4.5A and B). Genes are sorted according to their expression change fromdownregulated at the left to upregulated at the right, and then the proportion of genes from the set of annotated ge...
Recently, microarray data analyses using functional pathway information, e.g., gene set enrichment analysis (GSEA) and significance analysis of function and expression (SAFE), have gained recognition as a way to identify biological pathways/processes associated with a phenotypic endpoint. In these anal...
Supervised methods such as gene set enrichment analysis (GSEA)18 use previously described information in their search for associations, while unsupervised methods aim to identify novel signatures in an unbiased manner based on GE data only. Generally, any gene subset showing significant co-expression ...
Gene set enrichment and tissue analyses were carried out with GENE2FUNC implemented in FUMA45 (http://fuma.ctglab.nl/). We used genes identified in the gene-based analysis after polygene pruning as input data. Enrichment of the identified genes in biological pathways and functional categories ...
Gene Set Analysis (GSA) has proven to be a useful approach to microarray analysis. However, most of the method development for GSA has focused on the statistical tests to be used rather than on the generation of sets that will be tested. Existing methods of set generation are often overly ...
To distinguish them, it may be helpful to study the variance explained per gene by each of the sets. ‘ABC Transporters’ and ‘Lysosome’ were the two most highly ranked gene sets using this way of ranking. However, neither of these was identified in a hypergeometric gene set enrichment ...
To observe the difference of pathway between high- and low-risk groups, we carried out gene set enrichment analysis (GSEA) using the “clusterProfiler” R package. The enrichment analysis of KEGG and HALLMARK was done on TCGA and GSE62254 cohort, respectively, and the enriched pathways were di...
analysis time points compared to unactivated T-cell populations (time series of gene expression arrays and RNA-seq data). To find DE genes with a significant combined effect size (FDR < 0.05) across CD4+T-cell populations from theDiscovery Set(highlighted in blue), we conducted a meta-...
Gene Set Enrichment Analysis - Bioconductor - Home:基因集富集分析- Bioconductor回家 热度: IntegratingMultiple-PlatformExpressionData throughGeneSetFeatures MatˇejHolec 1 ,Filip ˇ Zelezn´y 1 ,Jiˇr´ıKl´ema 1 ,andJakubTolar 2