Garcia-Linares C, Mercade´ J, Gel B, Biayna J, Terribas E, et al. (2012) Applying Microsatellite Multiplex PCR Analysis (MMPA) for Determining Allele Copy-Number Status and Percentage of Normal Cells within Tumors. PLoS ONE 7(8): e42682. doi:10.1371/journal.pone.0042682
We reported the development of a simple set of calculations for analyzing microsatellite multiplex PCR data from control-tumor pairs that allows us to obtain accurate information not only regarding the allelic imbalance (AI) status of tumors, but also the percentage of tumor-infiltrating normal cells, the locus copy-number status and the mechanism involved in AI. Microsatellite multiplex PCR analysis (MMPA) should be particularly useful for analyzing specific regions of the genome containing tumor suppressor genes and also for determining the percentage of infiltrating normal cells within tumors allowing them to be sorted before they are analyzed by more expensive techniques.
Semi-automated analysis of MMPA results
To analyze the data extracted by Peak Scanner software we have developed a tool that automates all the necessary MMPA calculations. This automated analysis has been implemented using the Ruby programming language in a script named mmpa.rb. The script calculates and outputs the Km, comparing the reactions of control-tumor pairs, the average percentage of normal tissue contamination in the tumor, and the overall mechanism of AI for the test sample. For each informative microsatellite, calculated Ks, AI determination, observed peak height ratios, expected peak height ratios, % of non-AI cells and mechanisms generating the AIs are also calculated. mmpa.rb is released under the GNU GPL license. Source code and detailed instructions for its installation and use are available here:
This is a zip file. If you have problems accessing the documents please contact the Eduard Serra on eserra(ELIMINAR)@imppc.org