Repitools 1.39.0 – Analysis of Enrichment-based Epigenomic Data

Repitools 1.39.0

:: DESCRIPTION

Repitools are tools for the analysis of enrichment-based epigenomic data. Features include summarization and visualization of epigenomic data across promoters according to gene expression context, finding regions of differential methylation/binding, BayMeth for quantifying methylation etc.

::DEVELOPER

Mark Robinson

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows / MacOsX / Linux
R package

:: DOWNLOAD

Repitools

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Jul 1;26(13):1662-3. doi: 10.1093/bioinformatics/btq247. Epub 2010 May 10.
Repitools: an R package for the analysis of enrichment-based epigenomic data.
Statham AL, Strbenac D, Coolen MW, Stirzaker C, Clark SJ, Robinson MD.

GREGOR 1.4.0 – Evaluating Enrichment of Any set of Genetic Variants with any set of Regulatory Features

GREGOR 1.4.0

:: DESCRIPTION

GREGOR (Genomic Regulatory Elements and Gwas Overlap algoRithm) is a tool built to evaluate global enrichment of trait-associated variants in experimentally annotated epigenomic regulatory features.

::DEVELOPER

GREGOR team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Perl

:: DOWNLOAD

GREGOR

:: MORE INFORMATION

Citation

GREGOR: Evaluating global enrichment of trait-associated variants in epigenomic features using a systematic, data-driven approach.
Schmidt EM, Zhang J, Zhou W, Chen J, Mohlke KL, Chen YE, Willer CJ.
Bioinformatics. 2015 Apr 16. pii: btv201.

MPEA – Metabolite Pathway Enrichment Analysis

MPEA

:: DESCRIPTION

MPEA is a rapid tool for functional analysis and biological interpretation of metabolic profiling data. In particular, MPEA is designed to be used with data generated by gas chromatography mass spectrometry (GCMS); one of the most prominent analytical methods for metabolic studies and able to quantify hundreds of small molecules from biological extracts in a single run.

::DEVELOPER

Liisa Holm’s Bioinformatics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

MPEA

:: MORE INFORMATION

Citation:

Bioinformatics. 2011 Jul 1;27(13):1878-9. doi: 10.1093/bioinformatics/btr278. Epub 2011 May 5.
MPEA–metabolite pathway enrichment analysis.
Kankainen M1, Gopalacharyulu P, Holm L, Oresic M.

EmpiricalGO – Measure Enrichment using an Empirical Sampling Approach

EmpiricalGO

:: DESCRIPTION

EmpiricalGO is a Python script that generates the empirical distribution of the number of microRNA target genes in GO terms and returns p-values for term enrichment.

::DEVELOPER

SGJlab

:: SCREENSHOTS

n/a

:: REQUIREMENTS

Linux / MacOs / Windows
Python

:: DOWNLOAD

EmpiricalGO

:: MORE INFORMATION

Citation:

Bias in microRNA functional enrichment analysis.
Bleazard T, Lamb J, Griffiths-Jones S.
Bioinformatics. 2015 Jan 20. pii: btv023.

MicroPattern – Microbe Set Enrichment Analysis and Disease Similarity Calculation

MicroPattern

:: DESCRIPTION

MicroPattern is a tool used to mine regular rules and patterns behind a list of microbes. MicroPattern can also be used to calculate the similarity between the given disease-associated microbe list and the collected micro-disease association dataset

::DEVELOPER

the Cui Lab

:: SCREENSHOTS

n/a

:: REQUIREMENTS

Web browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Ma W, Huang C, Zhou Y, Li J, Cui Q.
MicroPattern: a web-based tool for microbe set enrichment analysis and disease similarity calculation based on a list of microbes.
Sci Rep. 2017 Jan 10;7:40200. doi: 10.1038/srep40200. PMID: 28071710; PMCID: PMC5223220.

hiddenDomains 3.1 – A modern HMM to Identify ChIP-seq Enrichment

hiddenDomains 3.1

:: DESCRIPTION

hiddenDomains uses a Hidden Markov Model to identify enriched domains in ChIP-seq data. It accepts BAM files for input and can perform an analysis with or without control data. The output is a BED file, ready for the UCSC genome browser, that contains the domains and is color coded according to their posterior probabilities.

::DEVELOPER

hiddenDomains team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/ Linux/ MacOsX
Perl
R

:: DOWNLOAD

hiddenDomains

:: MORE INFORMATION

Citation

Detecting broad domains and narrow peaks in ChIP-seq data with hiddenDomains.
Starmer J, Magnuson T.
BMC Bioinformatics. 2016 Mar 24;17(1):144. doi: 10.1186/s12859-016-0991-z.

MBRole 2.0 – Enrichment Analysis of Metabolomic data

MBRole 2.0

:: DESCRIPTION

MBRole (Metabolites Biological Role) is a server that performs functional enrichment analysis of a list of chemical compounds derived from a metabolomics experiment, which allows this list to be interpreted in biological terms.

::DEVELOPER

[Computational Systems Biology Group @CNB-CSIC]

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

MBROLE 2.0-functional enrichment of chemical compounds.
López-Ibáñez J, Pazos F, Chagoyen M.
Nucleic Acids Res. 2016 Apr 15. pii: gkw253.

Chagoyen, M. and Pazos, F. (2011)
‘MBRole: enrichment analysis of metabolomic data‘
Bioinformatics 27: 730-731

iPAGE 1.2a – Functional and Categorical Enrichment program based on Mutual information

iPAGE 1.2a

:: DESCRIPTION

iPAGE is a powerful package which in conjunction with FIRE provides a complete meta-analysis of whole-genome datasets.

::DEVELOPER

Tavazoie lab at Columbia University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/ MacOsX
Perl

:: DOWNLOAD

iPAGE

:: MORE INFORMATION

Citation:

Mol Cell. 2009 Dec 11;36(5):900-11. doi: 10.1016/j.molcel.2009.11.016.
Revealing global regulatory perturbations across human cancers.
Goodarzi H, Elemento O, Tavazoie S.

REA 1.1 – RIP-chip Enrichment Analysis

REA 1.1

:: DESCRIPTION

REA is a collection of methods for RIP-chip Enrichment Analysis. A table of normalized expression values from a RIP-chip experiment is read (e.g. as produced by the Affymetrix PowerTools) and two main steps are performed: Subtraction of the background of non target genes and secondary normalization for differing IP efficiencies.

::DEVELOPER

Institut für Informatik, Ludwig-Maximilians-Universität München

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/Linux/MacOsX
R package

:: DOWNLOAD

REA

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Jan 1;29(1):77-83. doi: 10.1093/bioinformatics/bts631.
RIP-chip enrichment analysis.
Erhard F, Dölken L, Zimmer R.

MEGA-V – Mutation Enrichment Gene set Analysis of Variants

MEGA-V

:: DESCRIPTION

MEGA-V is an open-source R application with a Shiny web interface. It identifies gene sets with a significantly higher number of variants in a cohort of interest (cohort A) as compared to (1) a control cohort (cohort B) or (2) a random distribution generated using Monte Carlo.

::DEVELOPER

the Ciccarelli Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/ Linux
R

:: DOWNLOAD

MEGA-V

:: MORE INFORMATION

Citation:

Gambardella G, Cereda M, Benedetti L, Ciccarelli FD.
MEGA-V: detection of variant gene sets in patient cohorts.
Bioinformatics. 2017 Apr 15;33(8):1248-1249. doi: 10.1093/bioinformatics/btw809. PMID: 28003259; PMCID: PMC5408849.