2021
DOI: 10.1002/cpz1.90
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Gene Set Knowledge Discovery with Enrichr

Abstract: Profiling samples from patients, tissues, and cells with genomics, transcriptomics, epigenomics, proteomics, and metabolomics ultimately produces lists of genes and proteins that need to be further analyzed and integrated in the context of known biology. Enrichr (Chen et al., 2013; Kuleshov et al., 2016) is a gene set search engine that enables the querying of hundreds of thousands of annotated gene sets. Enrichr uniquely integrates knowledge from many high‐profile projects to provide synthesized information a… Show more

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Cited by 1,950 publications
(1,681 citation statements)
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References 34 publications
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“…Annotation based enrichment was performed using two sided Fisher exact tests, which was done through LOLA (v1.20.0) for the chromatin state enrichments (Sheffield and Bock 2015), and the odds ratios were converted to fold enrichments for data visualization. enrichR (v3.0) was used for gene symbol based GO, PANTHER pathway, and GEO RNA-seq disease and drug signature enrichment testing (Chen et al 2013; Jawaid 2021; Kuleshov et al 2016; Xie et al 2021). regioneR (v1.22.0) was utilized to perform permutation based genomic coordinate enrichment testing through a randomized region strategy with 10,000 permutations (Gel et al 2016).…”
Section: Methodsmentioning
confidence: 99%
“…Annotation based enrichment was performed using two sided Fisher exact tests, which was done through LOLA (v1.20.0) for the chromatin state enrichments (Sheffield and Bock 2015), and the odds ratios were converted to fold enrichments for data visualization. enrichR (v3.0) was used for gene symbol based GO, PANTHER pathway, and GEO RNA-seq disease and drug signature enrichment testing (Chen et al 2013; Jawaid 2021; Kuleshov et al 2016; Xie et al 2021). regioneR (v1.22.0) was utilized to perform permutation based genomic coordinate enrichment testing through a randomized region strategy with 10,000 permutations (Gel et al 2016).…”
Section: Methodsmentioning
confidence: 99%
“…Transcriptional regulatory relationships unraveled by sentence-based text mining (TRRUST), a bioinformatics tool provided through the TRRUST website ( www.grnpedia.org/trrust ; [ 40 ]), was used to show transcription factors associated with our gene lists of interest, using a cut-off of 1.5 for the total fold change. KEGG pathway analysis was performed on gene sets of interest using the EnrichR database ( https://maayanlab.cloud/Enrichr/# , [ 41 ]). The Venn diagram is based on differentially expressed gene lists for each LPS-stimulus condition for the BV2 shCtrl and sh Atg7 , respectively.…”
Section: Methodsmentioning
confidence: 99%
“…SE and MXE, AS event types focused on in this work, composed approximately 50% and 20% of all AS events, respectively. Gene ontology (GO) analysis was performed to reveal enriched functional pathways affected by significant gene expression changes as well as alternative splicing changes using EnrichR (Chen et al, 2013; Kuleshov et al, 2016; Xie et al, 2021). The top enriched GO terms with smallest adjusted p values were visualized as bar plots.…”
Section: Methodsmentioning
confidence: 99%