Add to ORKGDescription Performs gene set analysis based on GSZ scoring function and asymptotic p-value. It is different from GSZ in that it implements asymptotic p-values instead of empirical p-values. Asymptotic p-values are calculated by fitting suitable distribution model to the null distri-bution. Unlike empirical p-values, resolution of asymptotic p-values are independent of the num-ber of permutations and hence requires considerably fewer permutations. In addition, this pack-age allows gene set analysis with seven other popular gene set analysis methods
1<p>p-values were calculated using a hypergeometric test</p><p>Distribution of genes across categori...
a<p>Size, number of genes in gene set.</p>b<p>ES, enrichment score.</p>c<p>NES, normalized enrichmen...
<p><b>Copyright information:</b></p><p>Taken from "Comparative evaluation of gene-set analysis metho...
Motivation: Gene set analysis is the analysis of a set of genes that collectively contribute to a bi...
Description Use log-linear models to perform hypergeometric and chi-squared tests for gene set enric...
Abstract Background A central task in contemporary biosciences is the identification of biological p...
A common complementary strategy in Genome-Wide Association Studies (GWAS) is to perform Gene Set Ana...
Background: Gene set analysis (in a form of functionally related genes or pathways) has become the m...
A common complementary strategy in Genome-Wide Association Studies (GWAS) is to perform Gene Set Ana...
Description The package implements methods to compare lists of genes based on comparing the cor-resp...
biological processes which are active in individual gene sets from corresponding microarray measurem...
seq, RNAseq etc.). These include MDS plots (analogues to PCA), detecting inefficient immuno-precipit...
Abstract Background Gene set a...
Description GeneAnswers provides an integrated tool for biological or medical interpreta-tion of the...
<p>Gene sets identified by only one of the three methods (CoGA, GSCA, and GSNCA) and the correspondi...
1<p>p-values were calculated using a hypergeometric test</p><p>Distribution of genes across categori...
a<p>Size, number of genes in gene set.</p>b<p>ES, enrichment score.</p>c<p>NES, normalized enrichmen...
<p><b>Copyright information:</b></p><p>Taken from "Comparative evaluation of gene-set analysis metho...
Motivation: Gene set analysis is the analysis of a set of genes that collectively contribute to a bi...
Description Use log-linear models to perform hypergeometric and chi-squared tests for gene set enric...
Abstract Background A central task in contemporary biosciences is the identification of biological p...
A common complementary strategy in Genome-Wide Association Studies (GWAS) is to perform Gene Set Ana...
Background: Gene set analysis (in a form of functionally related genes or pathways) has become the m...
A common complementary strategy in Genome-Wide Association Studies (GWAS) is to perform Gene Set Ana...
Description The package implements methods to compare lists of genes based on comparing the cor-resp...
biological processes which are active in individual gene sets from corresponding microarray measurem...
seq, RNAseq etc.). These include MDS plots (analogues to PCA), detecting inefficient immuno-precipit...
Abstract Background Gene set a...
Description GeneAnswers provides an integrated tool for biological or medical interpreta-tion of the...
<p>Gene sets identified by only one of the three methods (CoGA, GSCA, and GSNCA) and the correspondi...
1<p>p-values were calculated using a hypergeometric test</p><p>Distribution of genes across categori...
a<p>Size, number of genes in gene set.</p>b<p>ES, enrichment score.</p>c<p>NES, normalized enrichmen...
<p><b>Copyright information:</b></p><p>Taken from "Comparative evaluation of gene-set analysis metho...