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.