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We calculated GO term enrichments using the GOstats package [46].
Analysis was carried out using the GoStats package, Bioconductor.
The enrichment analysis was conducted using the GOstats package in R (Falcon and Gentleman, 2007).
GO enrichment analysis was performed using the GOstats package in Bioconductor, with hypergeometric distribution testing.
GO enrichments for biological process ontology were calculated using the GOStats package under R statistical software.
Significantly over-represented Gene Ontology biological processes among differentially expressed genes were determined using the GOStats package in R 2.14.1 [ 63].
The GO enrichment analysis [ 40, 41] was performed using the GOstats package [ 136] in the R software [ 114], correcting for multiple comparisons via the Benjamini-Hochberg method [ 135].
Functional analysis of the differentially expressed genes was carried out using the GOstats package in Bioconductor [ 22] based on the Gene Ontology Consortium database [ 23].
The analysis of over- and under-represented Gene Ontology terms was performed using the GOstats package from the Bioconductor project BioC 2.0 [ 50] (containing Entrez annotation data in the humanLLMappings and mouseLLMappings packages) with R 2.5.0 [ 60].
The cluster enrichment analysis was performed using the GOStats package for R [ 33] based on the org.Mm.eg.db package [ 90]. oPOSSUM was used to search for over-represented TFBS among the genes of each cluster [ 37, 38].
It was carried out using the GOstats package in the Bioconductor [ 22] and Gene Ontology Consortium database [ 23], based on the complete list of 365 differentially expressed transcripts (Supplement Table S1 and S2).
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