CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data.
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In: Database: The Journal of Biological Databases and Curation, Vol. 2012, bas055, 15.12.2012.
Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - CancerMA: a web-based tool for automatic meta-analysis of public cancer microarray data.
AU - Feichtinger, Julia
AU - Mcfarlane, Ramsay
AU - Larcombe, Lee
PY - 2012/12/15
Y1 - 2012/12/15
N2 - 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.
AB - 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.
U2 - 10.1093/database/bas055
DO - 10.1093/database/bas055
M3 - Article
VL - 2012
JO - Database: The Journal of Biological Databases and Curation
JF - Database: The Journal of Biological Databases and Curation
SN - 1758-0463
M1 - bas055
ER -