User:Diego Forero/Notebook/Silico-Meta

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<!-- sibboleth --><div id="lncal1" style="border:0px;"><div style="display:none;" id="id">lncal1</div><div style="display:none;" id="dtext">09/18/2009,09/19/2009</div><div style="display:none;" id="page">User:Diego Forero/Notebook/Silico-Meta</div><div style="display:none;" id="fmt">yyyy/MM/dd</div><div style="display:none;" id="css">OWWNB</div><div style="display:none;" id="month"></div><div style="display:none;" id="year"></div><div style="display:none;" id="readonly">Y</div></div>

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Project Description/Abstract

  • A SURVEY OF AVAILABLE COMPUTATIONAL TOOLS FOR META-ANALYSIS OF MICROARRAY EXPRESSION STUDIES
  • Meta-analysis of genome-wide expression data generated by microarray experiments has been used as a novel approach to discover the transcriptional alterations underlying complex biological phenotypes. This methodological approach represents a potential strategy to find consistent gene expression signatures in larger datasets and to find possible causes of heterogeneity. A comparison of the existing programs designed for implementation of this type of meta-analyses of high-throughput data is lacking. In this work, we review the features of eight freely available computational tools for meta-analysis of microarray data: GeneMeta, MAID, metaArray, metaGEM, metahdep, metaMA, RankAggreg and RankProd. All of these tools are packages for the R/Bioconductor environment and are based on different, and potentially complementary, algorithms. This survey will be useful for researchers interested in the implementation of meta-analyses of microarray data and for the development of future additional computational tools.
  • AUTHORS:
  • Diego Forero, MD, PhD(c)

Notes

  • This work is in progress

To be submitted to Briefings in Bioinformatics

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