CHRONOS 1.22.0 – microRNA-mediated sub-pathway Enrichment Analysis

CHRONOS 1.22.0

:: DESCRIPTION

CHRONOS (time-vaRying enriCHment integrOmics Subpathway aNalysis tOol) is an R package by integrating time-series mRNA/microRNA expression data with KEGG pathway maps and microRNA-target interactions.

::DEVELOPER

the Biosignal Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows/ MacOsX
R

:: DOWNLOAD

CHRONOS

:: MORE INFORMATION

Citation

CHRONOS: A time-varying method for microRNA-mediated sub-pathway enrichment analysis.
Vrahatis AG, Dimitrakopoulou K, Balomenos P, Tsakalidis AK, Bezerianos A.
Bioinformatics. 2015 Nov 14. pii: btv673

MamPhEA – Mammalian Phenotype Enrichment Analysis

MamPhEA

:: DESCRIPTION

MamPhEA is a web application dedicated to understanding functional properties of mammalian gene sets based on mouse-mutant phenotypes.

::DEVELOPER

MamPhEA team

:: SCREENSHOTS

N/a

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Sep 1;26(17):2212-3. doi: 10.1093/bioinformatics/btq359. Epub 2010 Jul 6.
MamPhEA: a web tool for mammalian phenotype enrichment analysis.
Weng MP1, Liao BY.

deTS v1.0 – Tissue-Specific Enrichment Analysis

deTS v1.0

:: DESCRIPTION

deTS is an R package to identify the most relevant tissues for candidate genes or for gene expression profiles.

::DEVELOPER

Bioinformatics and Systems Medicine Laboratory

:: SCREENSHOTS

n/a

:: REQUIREMENTS

Linux
R

:: DOWNLOAD

deTS

:: MORE INFORMATION

Citation:

Pei G, Dai Y, Zhao Z, Jia P.
deTS: tissue-specific enrichment analysis to decode tissue specificity.
Bioinformatics. 2019 Oct 1;35(19):3842-3845. doi: 10.1093/bioinformatics/btz138. PMID: 30824912; PMCID: PMC6761978.

POEAS – Plant Ontology Enrichment Analysis Server

POEAS

:: DESCRIPTION

POEAS is a plant ontology enrichment analysis server. The server uses a simple list of genes as an input and perform enrichment analysis and provide results in two levels: a table with enrichment results and a visulaization utilitity to generate ontological graphs that can be used in publications.

::DEVELOPER

POEAS Team

:: SCREENSHOTS

n/a

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Bioinform Biol Insights. 2014 Dec 21;8:209-14. doi: 10.4137/BBI.S19057. eCollection 2014.
POEAS: Automated Plant Phenomic Analysis Using Plant Ontology.
Shameer K, Naika MB, Mathew OK, Sowdhamini R

npGSEA 1.28.0 – Permutation Approximation methods for Gene Set Enrichment Analysis

npGSEA 1.28.0

:: DESCRIPTION

npGSEA (non-permutation GSEA) calculates gene set enrichment statistics and p-values without the computational cost of permutations. It is applicable in settings where one or many gene sets are of interest. There are also built-in plotting functions to help users visualize results.

::DEVELOPER

Jessica Larson <larson.jess at gmail.com> and Art Owen

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/Linux/ MacOsX
R
BioConductor

:: DOWNLOAD

npGSEA

:: MORE INFORMATION

Citation

Moment based gene set tests.
Larson JL, Owen AB.
BMC Bioinformatics. 2015 Apr 28;16(1):132.

GSEA 4.1.0 – Gene Set Enrichment Analysis

GSEA 4.1.0

:: DESCRIPTION

GSEA (Gene Set Enrichment Analysis) is a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states (e.g. phenotypes).

::DEVELOPER

GSEA team

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows / MacOsX
Java

:: DOWNLOAD

GSEA

:: MORE INFORMATION

Citation:

Subramanian, Tamayo, et al. (2005,)
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
PNAS 102, 15545-15550

SeqGSEA 1.33.0 – Gene Set Enrichment Analysis (GSEA) of RNA-Seq Data: integrating differential expression and splicing

SeqGSEA 1.33.0

:: DESCRIPTION

SeqGSEA generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing.

::DEVELOPER

Xi Wang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Mac OsX / Windows
R package
BioConductor

:: DOWNLOAD

SeqGSEA

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Mar 6. [Epub ahead of print]
SeqGSEA: a Bioconductor package for gene set enrichment analysis of RNA-Seq data integrating differential expression and splicing.
Wang X1, Cairns MJ.

BMC Bioinformatics. 2013;14 Suppl 5:S16. doi: 10.1186/1471-2105-14-S5-S16. Epub 2013 Apr 10.
Gene set enrichment analysis of RNA-Seq data: integrating differential expression and splicing.
Wang X, Cairns MJ.

sTAM – Single Sample microRNA Set Enrichment Analysis

sTAM

:: DESCRIPTION

sTAM is a computational tool for single sample miRNA set enrichment analysis (MSEA).

::DEVELOPER

the Cui Lab

:: SCREENSHOTS

n/a

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Shi J, Cui Q.
sTAM: An Online Tool for the Discovery of miRNA-Set Level Disease Biomarkers.
Mol Ther Nucleic Acids. 2020 Sep 4;21:670-675. doi: 10.1016/j.omtn.2020.07.004. Epub 2020 Jul 10. PMID: 32750560; PMCID: PMC7398894.

miR2Gene 201107 – Gene Pattern discovery by Enrichment Analysis of their microRNA Regulators

miR2Gene 201107

:: DESCRIPTION

miR2Gene for gene pattern discovery by enrichment analysis of their microRNA regulators is a web-accessible program, which is used to mine potential patterns for one single gene, multiple genes, and KEGG pathway genes based on miRNA set enrichment analysis of the miRNAs regulating given genes.

::DEVELOPER

the Cui Lab

:: SCREENSHOTS

n/a

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

BMC Syst Biol. 2011 Dec 14;5 Suppl 2:S9. doi: 10.1186/1752-0509-5-S2-S9. Epub 2011 Dec 14.
miR2Gene: pattern discovery of single gene, multiple genes, and pathways by enrichment analysis of their microRNA regulators.
Qiu C1, Wang J, Cui Q.

SSEA 1.0 – SNP Set Enrichment Analysis for Genome-wide Association Studies

SSEA 1.0

:: DESCRIPTION

SSEA (SNP Set Enrichment Analysis) is a new SNP-based pathway analysis software for GWAS studies. SSEA consists of two main steps: selecting representative SNPs for each gene, and performing pathway enrichment analysis using all selected SNPs.

::DEVELOPER

CBCL Lab (Computational Biology and Computational Learning) @ UCI

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows / MacOsX
Java

:: DOWNLOAD

SSEA

:: MORE INFORMATION

Citation

Lingjie Weng, Fabio Macciardi, Aravind Subramanian, Guia Guffanti, Steven G. Potkin, Zhaoxia Yu, Xiaohui Xie
“SNP-based Pathway Enrichment Analysis for Genome-wide Association Study“;
BMC Bioinformatics 2011, 12:99