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The list of 191 probe sets was first converted into the corresponding 180 unique Entrez Gene IDs [49] and then analyzed with the function "GOHyperG" from the BioConductor package "GOstats" that uses the hypergeometric distribution to evaluate enrichment of particular Gene Ontology functional categories [50].
The hypergeometric test uses the hypergeometric distribution to calculate the probability of obtaining the contingency table as created above by chance.
This profiling tool uses the hypergeometric distribution to determine whether individual pathways or combinations of pathways are significantly over-represented among the genes of interest.
The GENECODIS algorithm uses the hypergeometric distribution to determine whether individual pathways or combinations of pathways are significantly overrepresented among the genes of interest.
CROC [ 31] also uses the hypergeometric distribution to find genomic regions or gene clusters enriched in over/under-expressed genes, and supports calculations based on both whole genome data and individual chromosome values.
For the analysis we used the GeneMerge software [ 45], which uses the hypergeometric distribution for obtaining the rank scores for the overrepresentation of the studied gene sets (the upregulated genes) compared to the population gene sets (the full set of maize genes).
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Fisher's exact test reports the exact p value under a null hypothesis of independent categories using the hypergeometric distribution.
The GO categories and KEGG pathway enrichment analysis of DEGs was performed using the hypergeometric distribution test compared to the whole-transcriptome background.
Enrichment significance for ATAC-seq and/or Atrx ChIP-seq associated genes relative to differentially expressed transcripts was determined using the hypergeometric distribution.
We compute this value in Equation 1, for 1≤v i ≤n≤v, using the Hypergeometric distribution.
For example, [44] used the hypergeometric distribution for finding the expected link weights for bipartite networks and measured the global p-value.
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