Significance Testing for Aberrant Copy-Number (STAC)
- Aug 11th, 2006: New greatly improved version of the software (1.2) is now available. We recommend using this version instead of version 1.1.
- Jan 6th, 2006: New version of the software (1.1) now available.
We have developed STAC to fill this need.
- Genomic copy number aberrations (CNAs) occur in many solid tumors and may drive tumor initiation and/or progression.
- The problem is to determine CNAs which occur significantloy more often than chance across multiple samples in a class of tumors.
- Accurate identification of such significant CNAs across multiple experiments/samples is necessary for prioritizing regions for further study.
- Researchers have traditionally relied on non-statistical methods such as simple frequency cutoffs and manual review to prioritize regions.
- This approach may identify some regions of interest, however, it is subject to investigator bias and lacks statistical power necessary to control the error rates involved.
- Therefore there is a need for unbiased statistical methods which can identify non-random genomic copy number changes from multiple experiments.
For more information see the STAC publication in Genome Research, or the slides from our presentation given at the MGED8 conference September 2005.
If you have questions on the program or its usage or if you want to report any bugs, please contact: email@example.com or firstname.lastname@example.org.