2021
DOI: 10.1093/nar/gkab447
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KOBAS-i: intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis

Abstract: Gene set enrichment (GSE) analysis plays an essential role in extracting biological insight from genome-scale experiments. ORA (overrepresentation analysis), FCS (functional class scoring), and PT (pathway topology) approaches are three generations of GSE methods along the timeline of development. Previous versions of KOBAS provided services based on just the ORA method. Here we presented version 3.0 of KOBAS, which is named KOBAS-i (short for KOBAS intelligent version). It introduced a novel machine learning-… Show more

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Cited by 984 publications
(664 citation statements)
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“…ClusterProfiler package in Bioconductor was used to perform GO analysis ( Yu et al, 2012 ) and q -values < 0.05 were considered statistically significant. KEGG pathways were enriched by KOBAS online software 2 ( Bu et al, 2021 ) and the corrected P -values < 0.05 were considered statistically significant.…”
Section: Methodsmentioning
confidence: 99%
“…ClusterProfiler package in Bioconductor was used to perform GO analysis ( Yu et al, 2012 ) and q -values < 0.05 were considered statistically significant. KEGG pathways were enriched by KOBAS online software 2 ( Bu et al, 2021 ) and the corrected P -values < 0.05 were considered statistically significant.…”
Section: Methodsmentioning
confidence: 99%
“…genome.jp/kegg, accessed on 15 May 2021). For the KEGG enrichment or pathway analysis, the KOBAS3.0 [29] method was used, and visualized by Pathview package of R/Bioconductor.…”
Section: Genome Wide Identification Of the Mshsp90 Gens And Gene Sequence Analysismentioning
confidence: 99%
“…We use the GAQ score to determine the value added to functional information, particularly when compared with well-annotated model species, such as D. melanogaster, and to a lesser extent, Apis mellifera and Triboleum castaneum. [26,27] assigns input proteins to known pathways in KEGG. It also includes a gene set enrichment function (Table S3) to find statistically enriched genes in a disease or experimental condition with respect to the background of all annotated proteins in the organism.…”
Section: Combining and Qc Of Go Annotationsmentioning
confidence: 99%