cisMetalysis 1.3 – Meta Analysis of Gene Expression data sets

cisMetalysis 1.3

:: DESCRIPTION

Metalysis is meant for revealing higher level insights from multiple gene expression data sets. In particular, if you have up- and down-regulated gene sets from several different conditions and want to know what might be common to those different gene sets, you can use the Metalysis program.

cis-Metalysis” is an extension to Metalysis specifically designed to use motif target sets as annotation sets. It takes gene target predictions of the transcription factor motifs and then uses the Metalysis framework to identify meta associations between a motif and set of conditions. Because of the general consensus that condition-specific expression of a gene may be determine by combinations of transcription factors, cis-Metalysis also searches for motif combinations associated with expression.

::DEVELOPER

The Sinha Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • C++ Compiler

:: DOWNLOAD

 cisMetalysis

:: MORE INFORMATION

Citation

Proc Natl Acad Sci U S A. 2012 Jun 26;109(26):E1801-10. doi: 10.1073/pnas.1205283109.
New meta-analysis tools reveal common transcriptional regulatory basis for multiple determinants of behavior.
Ament SA, Blatti CA, Alaux C, Wheeler MM, Toth AL, Le Conte Y, Hunt GJ, Guzmán-Novoa E, Degrandi-Hoffman G, Uribe-Rubio JL, Amdam GV, Page RE Jr, Rodriguez-Zas SL, Robinson GE, Sinha S

Qiita v0.2.0 – Microbiome Meta-analysis

Qiita v0.2.0

:: DESCRIPTION

Qiita (canonically pronounced cheetah) is the QIIME database effort to enable rapid analysis of microbial ecology datasets. The Qiita repository is responsible for defining the data model and the Python API for interacting with a Qiita database.

::DEVELOPER

Knight Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

Qiita

:: MORE INFORMATION

Citation

Qiita: rapid, web-enabled microbiome meta-analysis.
Gonzalez A, et al.
Nat Methods. 2018 Oct;15(10):796-798. doi: 10.1038/s41592-018-0141-9

B-LORE – Bayesian multiple logistic Regression for GWAS Meta-analysis

B-LORE

:: DESCRIPTION

B-LORE (Bayesian LOgistic REgression) is a command line tool that creates summary statistics from multiple logistic regression on GWAS data, and combines the summary statistics from multiple studies in a meta-analysis. It can also incorporate functional information about the SNPs from other external sources. Several genetic regions, or loci are preselected for analysis with B-LORE.

::DEVELOPER

Söding Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOs
  • C Compiler
  • Python
:: DOWNLOAD

B-LORE

:: MORE INFORMATION

Citation:

PLoS Genet. 2018 Dec 31;14(12):e1007856. doi: 10.1371/journal.pgen.1007856. eCollection 2018 Dec.
Bayesian multiple logistic regression for case-control GWAS.
Banerjee S, Zeng L, Schunkert H, Söding J.

MetaSKAT 0.71 – Meta-analysis for multiple markers

MetaSKAT 0.71

:: DESCRIPTION

MetaSKAT is a R package for multiple marker meta-analysis across studies. It can carry out meta-analysis of SKAT, SKAT-O and burden tests with individual level genotype data or gene level summary statistics.

::DEVELOPER

Xihong Lin’s Group, Harvard School of Public Health

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  MetaSKAT

:: MORE INFORMATION

Citation

Lee, S., Teslovich, T.M., Boehnke, M. and Lin, X. (2013)
General framework for meta-analysis of rare variants in sequencing association studies
Am J Hum Genet. 2013 Jul 11;93(1):42-53. doi: 10.1016/j.ajhg.2013.05.010

GWAtoolbox 2.2.4-7 – Quality Control and Handling of Genome-wide Association Studies Meta-analysis data

GWAtoolbox 2.2.4-7

:: DESCRIPTION

GWAtoolbox is an R-package for fast quality control and data handling of multiple data files obtained from genome-wide association studies (GWAS).

::DEVELOPER

the Center of Biomedicine (CBM) at EURAC research.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/windows/MacOsX
  • R package

:: DOWNLOAD

 GWAtoolbox

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Feb 1;28(3):444-5. doi: 10.1093/bioinformatics/btr679.
GWAtoolbox: an R package for fast quality control and handling of genome-wide association studies meta-analysis data.
Fuchsberger C, Taliun D, Pramstaller PP, Pattaro C; CKDGen consortium.

cnvPipe 0.82 – Enable CNV Meta Analysis

cnvPipe 0.82

:: DESCRIPTION

The aim of the cnvPipe package is to take CNV segmentation results produced from multiple cohorts, and to produce, for both deletions and duplications separately:

  • a single coherent set of CNV regions (CNVRs) across all cohorts
  • CNV genotypes corresponding to each of these regions for each sample in the cohort, in a standardised format

::DEVELOPER

Dr Lachlan J Coin

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 cnvPipe

:: MORE INFORMATION

ancMETA – Leveraging Cross-population Gene/Sub-network Meta-analysis to recover Disease Association Signal (DAS) Risk

ancMETA

:: DESCRIPTION

ancMETA is an application for leveraging cross-population Gene/Sub-network Meta-analysis to recover Disease Association Signal (DAS) risk in a homogenous or recently admixed population.

::DEVELOPER

Emile CHIMUSA

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 ancMETA

:: MORE INFORMATION

MetaPath 1.0 – Meta-analysis for Pathway Analysis

MetaPath 1.0

:: DESCRIPTION

MetaPath (Meta-analysis for Pathway Analysis) performs the meta-analysis for pathway enrichment analysis

::DEVELOPER

George C. Tseng 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 MetaPath

:: MORE INFORMATION

Citation

Kui Shen and George C. Tseng. (2010)
Meta-analysis for pathway enrichment analysis when combining multiple microarray studies.
Bioinformatics. 26:1316-1323.

ExAtlas – Meta-analysis of Gene Expression data

ExAtlas

:: DESCRIPTION

ExAtlas is an on-line software tool for meta-analysis and visualization of gene expression data.

::DEVELOPER

Laboratory of Genetics, National Institute on Aging,  NIH

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

ExAtlas: An interactive online tool for meta-analysis of gene expression data.
Sharov AA, Schlessinger D, Ko MS.
J Bioinform Comput Biol. 2015 Jun 9:1550019.

metaRNASeq 1.0.2 – Meta-analysis of RNA-seq data

metaRNASeq 1.0.2

:: DESCRIPTION

metaRNASeq implements two p-value combination techniques (inverse normal and Fisher methods). It also provides a vignette explaining how to combine data from multiple RNA-seq experiments.

::DEVELOPER

Guillemette Marot <guillemette.marot at inria.fr>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • R

:: DOWNLOAD

 metaRNASeq

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2014 Mar 29;15:91. doi: 10.1186/1471-2105-15-91.
Differential meta-analysis of RNA-seq data from multiple studies.
Rau A1, Marot G, Jaffrézic F.