ShinyGO v0.61: Gene Ontology Enrichment Analysis + more

We recently hired Jenny Qi for database updates and user support. Email Jenny for questions.

2/3/2020: Now published by Bioinformatics.

11/3/2019: V 0.61, Improve graphical visualization (thanks to reviewers). Interactive networks and much more.

5/20/2019: V.0.60, Annotation database updated to Ensembl 96. New bacterial and fungal genomes based on STRING-db!

Just paste your gene list to get enriched GO terms and othe pathways for over 315 plant and animal species, based on annotation from Ensembl (Release 96), Ensembl plants (R. 43) and Ensembl Metazoa (R. 43). An additional 2031 genomes (including bacteria and fungi) are annotated based on STRING-db (v.10). In addition, it also produces KEGG pathway diagrams with your genes highlighted, hierarchical clustering trees and networks summarizing overlapping terms/pathways, protein-protein interaction networks, gene characterristics plots, and enriched promoter motifs. See example outputs below:

Download table with gene IDs

Enrichment analysis based on hypergeometric distribution followed by FDR correction.

Select KEGG pathways in the left to display your genes in pathway diagrams.

A hierarchical clustering tree summarizing the correlation among significant pathways listed in the Enrichment tab. Pathways with many shared genes are clustered together. Bigger dots indicate more significant P-values.

Figure

Edge cutoff:

Wrap text

Download HTML Edges Nodes

Similar to the Tree tab, this interactive plot also shows the relationship between enriched pathways. Two pathways (nodes) are connected if they share 20% (default) or more genes. You can move the nodes by dragging them, zoom in and out by scrolling, and shift the entire network by click on an empty point and drag. Darker nodes are more significantly enriched gene sets. Bigger nodes represent larger gene sets. Thicker edges represent more overlapped genes.

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This table shows how your genes are converted to Ensembl gene IDs.

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If Gene Ontology is chosen, your genes are grouped by functional categories defined by high-level GO terms.

The characteristics of your genes are compared with the rest in the genome. Chi-squared and Student's t-tests are run to see if your genes are different from other genes.

Your genes are marked in each of the chromosomes. Note that the scale for each chromosomes are different.

Upstream 300bp as promoter

Upstream 600bp as promoter

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The promoter sequences of your genes are compared with those of the other genes in the genome in terms of transcription factor (TF) binding motifs. "*Query gene" indicates a transcription factor coded by a gene included in your list.

Your genes are sent to STRING-db website for enrichment analysis and retrieval of a protein-protein network. We tries to match your species with the 115 archaeal, 1678 bacterial, and 238 eukaryotic species in the STRING server and send the genes. If it is running, please wait until it finishes. This can take 5 minutes, especially for the first time when iDEP downloads large annotation files.

Functional Enrichment

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For feedbacks, please contact us, or visit our homepage. For details, please see our paper and a detailed demo. ShinyGO shares many functionalities and databases with iDEP. Source code at GitHub.

Citation:
Ge SX, Jung D & Yao R, Bioinformatics 2020

Previous versions (still functional):
ShinyGO V0.60, based on database derived from Ensembl BioMart version 96, archived on Nov 6, 2019
ShinyGO V0.51, based on database derived from Ensembl BioMart version 95, archived on May 20, 2019
ShinyGO V0.50, based on database derived from Ensembl BioMart version 92, archived on March 29, 2019
ShinyGO V0.41, based on database derived from Ensembl BioMart version 91, archived on July 11, 2018

Based on gene onotlogy (GO) annotation and gene ID mapping of 315 animal and plant genomes in Ensembl BioMart release 96 as of 5/20/2019. In addition, 115 archaeal, 1678 bacterial, and 238 eukaryotic genomes are annotated based on STRING-db v10. Additional pathway data are being collected for some model species from difference sources.

Genomes based on STRING-db is marked as STRING-db. If the same genome is included in both Ensembl and STRING-db, users should use Ensembl annotation, as it is more updated and is supported in more functional modules.

Sources for human pathway databases:

Type	Subtype/Database name	#GeneSets	Source
Gene Ontology	Biological Process (BP)	15796	Ensembl 92
	Cellular Component (CC)	1916	Ensembl 92
	Molecular Function (MF)	4605	Ensembl 92
KEGG	KEGG	327	Release 86.1
Curated	Biocarta	249	Whichgenes 1.5
	GeneSetDB.EHMN	55	GeneSetDB
	Panther	168	1.0.4
	HumanCyc	240	pathway Commons V9
	INOH	576	pathway Commons V9
	NetPath	27	pathway Commons V9
	PID	223	pathway Commons V9
	PSP	327	pathway Commons V9
	Recon X	2339	pathway Commons V9
	Reactome	2010	V64
	Wiki	457	20180610
TF.Target	CircuitsDB.TF	829	V2012
	ENCODE	181	V70.0
	Marbach2016	628	regulatorycircuits Release 1.0
	RegNetwork.TF	1400	7/1/2017
	TFacts	428	Feb. 2012
	tftargets.ITFP	1926	tftargets May,2017
	tftargets.Neph2012	16476	tftargets May,2017
	tftargets.TRED	131	tftargets May,2017
	TRRUST	793	V2
miRNA.Targets	CircuitsDB.miRNA	140	V. 2012
	GeneSetDB.MicroCosm	44	GeneSetDB
	miRDB	2588	V 5.0
	miRTarBase	2599	V 7.0
	RegNetwork.miRNA	618	V. 2015
	TargetScan	219	V7.2
MSigDB.Computational	Computational gene sets	858	MSigDB 6.1
MSigDB.Curated	Literature	3465	MSigDB 6.1
MSigDB.Hallmark	hallmark	50	MSigDB 6.1
MSigDB.Immune	Immune system	4872	MSigDB 6.1
MSigDB.Location	Cytogenetic band	326	MSigDB 6.1
MSigDB.Motif	TF and miRNA Motifs	836	MSigDB 6.1
MSigDB.Oncogenic	Oncogenic signatures	189	MSigDB 6.1
PPI	BioGRID	15542	3.4.160
	CORUM	2178	02.07.2017
	BIND	3807	pathway Commons V9
	DIP	2630	pathway Commons V9
	HPRD	7141	pathway Commons V9
	IntAct	11991	pathway Commons V9
Drug	GeneSetDB.MATADOR	266	GeneSetDB
	GeneSetDB.SIDER	473	GeneSetDB
	GeneSetDB.STITCH	4616	GeneSetDB
	GeneSetDB.T3DB	846	GeneSetDB
	SMPDB	699	pathway Commons V9
	CTD	8758	pathway Commons V9
	Drugbank	2563	pathway Commons V9
Other	GeneSetDB.CancerGenes	23	GeneSetDB
	GeneSetDB.MethCancerDB	21	GeneSetDB
	GeneSetDB.MethyCancer	54	GeneSetDB
	GeneSetDB.MPO	3134	GeneSetDB
	HPO	6785	May,2018
Total:		140,438

Sources for mouse pathway databases:


Type	Source	#Sets	Note
Co-expression	Literature	8,742	Differentially expressed genes from 2526 studies
	MSigDB	3,964	Molecular Signature Database, v.6.0
	L2L	248	List of lists, v.2006.2
	CancerGenes*	23	Cancer gene lists
	GeneSigDB	494	Gene Signature Database, R.4
Gene	GO_BP	11,943	V2017.5
Ontology	GO_MF	2,932
	GO_CC	1,475
Curated	Biocarta*	176	Metabolic and signaling pathways
pathways	PANTHER	151	Ontology-based pathway database, v3.4.1
	WikiPathways*	146	Open platform for pathway curation
	INOH*	73	Integrating network objects with hierarchies
	NetPath*	25	Signal transduction pathways
Metabolic	KEGG	314	Metabolic pathways, R.82.0
pathways	EHMN*	53	Edinburgh human metabolic network
	MouseCyc	321	Mouse Biochemical Pathways , v2013.7
Drug	CTD*	910	The Comparative Toxicogenomics Database
related	SIDER*	460	Side Effect Resource
	MATADOR*	248	Manually Annotated Targets and Drugs Online Resource
	DrugBank*	136	Open data drug and target database
	SMPDB*	74	Small Molecule Pathway Database
miRNA	miRDB	1,912	miRNA target prediction and annotations, v 5.0
Target	microRNA.org	314	Predicted miRNA targets, v.R2010
Genes	Grimson et al.	179	Predicted miRNA targets. v.6.2
	TarBase	84	Experimentally validated miRNA targets, v.6.0
	miRTarBase	775	Experimentally validated miRNA targets, V6.1
	MicroCosm	464	Predicted targets
	PicTar	35	Predicted miRNA sites, v. 2007.3
TF Target	TFactS*	101	Predicted TF targets
Genes	TRED	99	Confirmed TF target genes, v.2013.7
	CircuitsDB	94	Mixed miRNA/TF regulation, v. 2012
	TRANSFAC	78	Confirmed TF binding sites, v7.0
Others	Location	341	Genomic location on chromosomes, v.2017
	HPO*	1,518	The human phenotype ontology
	STITCH*	3,929	Interaction networks of chemicals and proteins
	MPO*	2,943	Mammalian Phenotype Ontology
	T3DB*	722	Database of common toxins and their targets
	PID*	193	Pathway Interaction Database
	MethyCancer*	50	Human DNA methylation and cancer
	MethCancerDB*	19	Aberrant DNA methylation in human cancer
	Total	46,758	*Secondary data from GeneSetDB

Input:

A list of gene ids, separated by tab, space, comma or the newline characters. Ensembl gene IDs are used internally to identify genes. Other types of IDs will be mapped to Ensembl gene IDs using ID mapping information available in Ensembl BioMart.

Output:

Enriched GO terms and pathways:

In addition to the enrichment table, a set of plots are produced. If KEGG database is choosen, then enriched pathway diagrams are shown, with user's genes highlighted, like this one below:

Many GO terms are related. Some are even redundant, like "cell cycle" and "cell cycle process". To visualize such relatedness in enrichment results, we use a hierarchical clustering tree and network. In this hierarchical clustering tree, related GO terms are grouped together based on how many genes they share. The size of the solid circle corresponds to the enrichment FDR.

In this network below, each node represents an enriched GO term. Related GO terms are connected by a line, whose thickness reflects percent of overlapping genes. The size of the node corresponds to number of genes.

Through API access to STRING-db, we also retrieve a protein-protein interaction (PPI) network. In addition to a static network image, users can also get access to interactive graphics at the www.string-db.org web server.

ShinyGO also detects transcription factor (TF) binding motifs enriched in the promoters of user's genes.