Tag: Meta-analysis

3TierMA – Three-Tiered Meta Analysis of Gene Expression Profiles of Co-morbid Diseases

3TierMA

:: DESCRIPTION

3TierMA is a three-tiered meta-analysis approach for studying the shared genetics of co-ocurring disease conditions in patients from their gene expression profiles.

::DEVELOPER

Bonnie Berger 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • R
  • Python

:: DOWNLOAD

3TierMA

:: MORE INFORMATION

Citation:

Sumaiya Nazeen, Nathan P. Palmer, Bonnie Berger* and Isaac S. Kohane.
Integrative analysis of genetic datasets reveals a shared innate immune component in autism spectrum disorder and its co-morbidities.
Genome Biology 17(1):228, 2016

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.

METRADISC / METRADISC-XL – METa-analysis of Microarrays Datasets / Heterogeneity Testing

METRADISC /METRADISC-XL

:: DESCRIPTION

METRADISC (METa-analysis of RAnked DISCovery datasets), a generalized meta-analysis method for combining information across discovery-oriented datasets and for testing between-study heterogeneity for each biological variable of interest. The method is based on non-parametric Monte Carlo permutation testing.

METRADISC-XL is a software for METa-analysis of microarrays datasets and heterogeneity testing.

::DEVELOPER

Department of Biomathematics. School of Medicine. University of Thessaly.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

  METRADISC / METRADISC-XL

:: MORE INFORMATION

Citation

Comput Biol Chem. 2008 Feb;32(1):38-46. Epub 2007 Sep 14.
Meta-analysis for ranked discovery datasets: theoretical framework and empirical demonstration for microarrays.
Zintzaras E, Ioannidis JP.

HEGESMA 2.0 – Genome Search Meta-analysis ang Heterogeneity testing

HEGESMA 2.0

:: DESCRIPTION

HEGESMA (HEterogeneity and GEnome Search Meta Analysis)is a comprehensive software for performing genome scan meta-analysis, a quantitative method to identify genetic regions (bins) with consistently increased linkage score across multiple genome scans, and for testing the heterogeneity of the results of each bin across scans. The program provides as an output the average of ranks and three heterogeneity statistics, as well as corresponding significance levels. Statistical inferences are based on Monte Carlo permutation tests. The program allows both unweighted and weighted analysis, with the weights for each study as specified by the user. Furthermore, the program performs heterogeneity analyses restricted to the bins with similar average ranks.

::DEVELOPER

Department of Biomathematics. School of Medicine. University of Thessaly.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 HEGESMA

:: MORE INFORMATION

Citation

Elias Zintzaras1, and John P. A. Ioannidis
HEGESMA: genome search meta-analysis and heterogeneity testing
Bioinformatics,21 (18): 3672-3673.

MetaPCA 0.1.4 – Meta-analysis in the Dimension Reduction of Genomic data

MetaPCA 0.1.4

:: DESCRIPTION

 MetaPCA is a software of dimension reductioin by PCA, sparse PCA and robust PCA in meta-analysis. The software implements simultaneous dimension reduction using PCA when multiple studies are combined.

::DEVELOPER

George C. Tseng 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  MetaPCA

:: MORE INFORMATION

 

MetaQTL 1.2.0 – Meta-analysis of QTL Mapping Experiments

MetaQTL 1.2.0

:: DESCRIPTION

MetaQTL is a Java package designed to perform the integration of data from the field of gene mapping experiments (e.g molecular markers, QTL, candidate genes, etc…). This package consists in a modular library and several programs written in pure Java. These programs can perform various tasks, including formatting, analyzing and visualizing data or results produced by MetaQTL.

::DEVELOPER

Jean-Baptiste Veyrieras

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • Java

:: DOWNLOAD

 MetaQTL

:: MORE INFORMATION

Citation:

MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments.
Veyrieras JB, Goffinet B, Charcosset A.
BMC Bioinformatics. 2007 Feb 8;8:49.

A-MADMAN 1.4 – Annotation-based Microarray Data Meta-ANalysis tool

A-MADMAN 1.4

:: DESCRIPTION

A-MADMAN (Annotation-based MicroArray DataMeta ANalysis tool) is an open source web application and gene chip analysis automation framework for annotation-based  meta-analysis of data from public repositories (NCBI GEO).

::DEVELOPER

COMPUTATIONAL GENOMICS LABORATORY, Department of Biology, University of Padova, Italy.

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 A-MADMAN

:: MORE INFORMATION

Citation:

Bisognin A, Coppe A, Ferrari F, Risso D, Romualdi C, Bicciato S, Bortoluzzi S.
A-MADMAN: Annotation-based microarray data meta-analysis tool.
BMC Bioinformatics. 2009 Jun 29;10:201

Haplotype meta-analysis – Meta-analysis of Haplotype Association Studies

Haplotype meta-analysis

:: DESCRIPTION

Haplotype meta-analysis is a STATA programs for meta-analysis of haplotype association studies.It use summary-based data as well as methods that use binary and count data in a generalized linear mixed model framework (logistic regression, multinomial regression and Poisson regression). The methods presented here avoid the inflation of the type I error rate that could be the result of the traditional approach of comparing a haplotype against the remaining ones, whereas, they can be fitted using standard software. Moreover, formal global tests are presented for assessing the statistical significance of the overall association. Although the methods presented here assume that the haplotypes are directly observed, they can be easily extended to allow for such an uncertainty by weighting the haplotypes by their probability.

:DEVELOPER

Computational Genetics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/MacOsX/Linux
  • Stata

:: DOWNLOAD

 Haplotype meta-analysis

:: MORE INFORMATION

Citation

Bagos PG.
Meta-analysis of haplotype-association studies: Comparison of methods and an empirical evaluation of the literature, 2011,
BMC Genetics, 12:8