CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data

Database (Oxford). 2012 Dec 15;2012:bas055. doi: 10.1093/database/bas055. Print 2012.

Abstract

The identification of novel candidate markers is a key challenge in the development of cancer therapies. This can be facilitated by putting accessible and automated approaches analysing the current wealth of 'omic'-scale data in the hands of researchers who are directly addressing biological questions. Data integration techniques and standardized, automated, high-throughput analyses are needed to manage the data available as well as to help narrow down the excessive number of target gene possibilities presented by modern databases and system-level resources. Here we present CancerMA, an online, integrated bioinformatic pipeline for automated identification of novel candidate cancer markers/targets; it operates by means of meta-analysing expression profiles of user-defined sets of biologically significant and related genes across a manually curated database of 80 publicly available cancer microarray datasets covering 13 cancer types. A simple-to-use web interface allows bioinformaticians and non-bioinformaticians alike to initiate new analyses as well as to view and retrieve the meta-analysis results. The functionality of CancerMA is shown by means of two validation datasets.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Access to Information*
  • Automation
  • Computational Biology / methods*
  • Databases, Genetic*
  • Gene Expression Regulation, Neoplastic
  • Humans
  • Internet*
  • Meta-Analysis as Topic*
  • Neoplasms / genetics*
  • Oligonucleotide Array Sequence Analysis*
  • Reproducibility of Results
  • User-Computer Interface
  • Workflow