Literature DB >> 33780170

Gene Set Knowledge Discovery with Enrichr.

Zhuorui Xie1, Allison Bailey1, Maxim V Kuleshov1, Daniel J B Clarke1, John E Evangelista1, Sherry L Jenkins1, Alexander Lachmann1, Megan L Wojciechowicz1, Eryk Kropiwnicki1, Kathleen M Jagodnik1, Minji Jeon1, Avi Ma'ayan1.   

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 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.

Entities:  

Keywords:  bioinformatics; disease; drug discovery; enrichment analysis; gene sets; visualization; web application

Mesh:

Year:  2021        PMID: 33780170      PMCID: PMC8152575          DOI: 10.1002/cpz1.90

Source DB:  PubMed          Journal:  Curr Protoc        ISSN: 2691-1299


  29 in total

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Journal:  Nat Protoc       Date:  2013-07-18       Impact factor: 13.491

6.  Enrichr: a comprehensive gene set enrichment analysis web server 2016 update.

Authors:  Maxim V Kuleshov; Matthew R Jones; Andrew D Rouillard; Nicolas F Fernandez; Qiaonan Duan; Zichen Wang; Simon Koplev; Sherry L Jenkins; Kathleen M Jagodnik; Alexander Lachmann; Michael G McDermott; Caroline D Monteiro; Gregory W Gundersen; Avi Ma'ayan
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Authors:  Zichen Wang; Caroline D Monteiro; Kathleen M Jagodnik; Nicolas F Fernandez; Gregory W Gundersen; Andrew D Rouillard; Sherry L Jenkins; Axel S Feldmann; Kevin S Hu; Michael G McDermott; Qiaonan Duan; Neil R Clark; Matthew R Jones; Yan Kou; Troy Goff; Holly Woodland; Fabio M R Amaral; Gregory L Szeto; Oliver Fuchs; Sophia M Schüssler-Fiorenza Rose; Shvetank Sharma; Uwe Schwartz; Xabier Bengoetxea Bausela; Maciej Szymkiewicz; Vasileios Maroulis; Anton Salykin; Carolina M Barra; Candice D Kruth; Nicholas J Bongio; Vaibhav Mathur; Radmila D Todoric; Udi E Rubin; Apostolos Malatras; Carl T Fulp; John A Galindo; Ruta Motiejunaite; Christoph Jüschke; Philip C Dishuck; Katharina Lahl; Mohieddin Jafari; Sara Aibar; Apostolos Zaravinos; Linda H Steenhuizen; Lindsey R Allison; Pablo Gamallo; Fernando de Andres Segura; Tyler Dae Devlin; Vicente Pérez-García; Avi Ma'ayan
Journal:  Nat Commun       Date:  2016-09-26       Impact factor: 14.919

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