Gene Set Knowledge Discovery with Enrichr

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.,...

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Bibliographic Details
Main Authors: Bailey, A. (Author), Clarke, D.J.B (Author), Evangelista, J.E (Author), Jagodnik, K.M (Author), Jenkins, S.L (Author), Jeon, M. (Author), Kropiwnicki, E. (Author), Kuleshov, M.V (Author), Lachmann, A. (Author), Ma'ayan, A. (Author), Wojciechowicz, M.L (Author), Xie, Z. (Author)
Format: Article
Language:English
Published: Blackwell Publishing Inc. 2021
Subjects:
Online Access:View Fulltext in Publisher
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020 |a 26911299 (ISSN) 
245 1 0 |a Gene Set Knowledge Discovery with Enrichr 
260 0 |b Blackwell Publishing Inc.  |c 2021 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1002/cpz1.90 
520 3 |a 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 about mammalian genes and gene sets. The platform provides various methods to compute gene set enrichment, and the results are visualized in several interactive ways. This protocol provides a summary of the key features of Enrichr, which include using Enrichr programmatically and embedding an Enrichr button on any website. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Analyzing lists of differentially expressed genes from transcriptomics, proteomics and phosphoproteomics, GWAS studies, or other experimental studies. Basic Protocol 2: Searching Enrichr by a single gene or key search term. Basic Protocol 3: Preparing raw or processed RNA-seq data through BioJupies in preparation for Enrichr analysis. Basic Protocol 4: Analyzing gene sets for model organisms using modEnrichr. Basic Protocol 5: Using Enrichr in Geneshot. Basic Protocol 6: Using Enrichr in ARCHS4. Basic Protocol 7: Using the enrichment analysis visualization Appyter to visualize Enrichr results. Basic Protocol 8: Using the Enrichr API. Basic Protocol 9: Adding an Enrichr button to a website. © 2021 Wiley Periodicals LLC 
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650 0 4 |a bioinformatics 
650 0 4 |a bioinformatics 
650 0 4 |a biology 
650 0 4 |a Computational Biology 
650 0 4 |a disease 
650 0 4 |a drug discovery 
650 0 4 |a embedding 
650 0 4 |a enrichment analysis 
650 0 4 |a epigenetics 
650 0 4 |a experimental study 
650 0 4 |a gene expression 
650 0 4 |a gene sets 
650 0 4 |a genome-wide association study 
650 0 4 |a genomics 
650 0 4 |a Genomics 
650 0 4 |a human 
650 0 4 |a human tissue 
650 0 4 |a Humans 
650 0 4 |a knowledge discovery 
650 0 4 |a Knowledge Discovery 
650 0 4 |a mammal 
650 0 4 |a metabolomics 
650 0 4 |a nonhuman 
650 0 4 |a phosphoproteomics 
650 0 4 |a protein fingerprinting 
650 0 4 |a RNA sequencing 
650 0 4 |a RNA-Seq 
650 0 4 |a search engine 
650 0 4 |a software 
650 0 4 |a Software 
650 0 4 |a transcriptomics 
650 0 4 |a visualization 
650 0 4 |a web application 
700 1 |a Bailey, A.  |e author 
700 1 |a Clarke, D.J.B.  |e author 
700 1 |a Evangelista, J.E.  |e author 
700 1 |a Jagodnik, K.M.  |e author 
700 1 |a Jenkins, S.L.  |e author 
700 1 |a Jeon, M.  |e author 
700 1 |a Kropiwnicki, E.  |e author 
700 1 |a Kuleshov, M.V.  |e author 
700 1 |a Lachmann, A.  |e author 
700 1 |a Ma'ayan, A.  |e author 
700 1 |a Wojciechowicz, M.L.  |e author 
700 1 |a Xie, Z.  |e author 
773 |t Current Protocols