In order to use STAC you first have to do some work to pre-process your data into binary "calls".
Aberrations come in many forms, they can be gains, losses, LOH, high level gain, etc. For any given type of aberration that you are interested in you have to run a separate STAC analysis. In other words, if you are interested in both gain and loss, you have to run them as two separate cases. More generally, to input data into STAC you must have binary aberration calls of "0" or "1" where "0" means no aberration and "1" means aberration, where the type of aberration is fixed throughout the analysis.
It is not advisable to analyze an entire chromosome as one stretch, the analysis should be done one arm at a time with the centromere omitted. One can also focus on just a piece of a chromosome arm, it is not necessary to analyze the entire arm, it is just not advisable to analyze more than an arm at once.
You can enter data in either of two possible formats, depending on what is more convenient for you.
where "exp1" is followed a tab which is followed by the spans separated by semi-colons. (It is not necessary to put commas in the numbers, it is optional.)
NOTE: You will have to decide carefully on a criteria to make aberration calls at each location or span. How best to do this depends on the particular nature of your data. If using two-channel BAC arrays, we have found that performing this pre-processing step using any of the various single-slide methods which are available can result in a significant decrease in resolution because they tend not to call a region as aberrant unless it is supported by several array elements in the region. Since STAC derives support for aberration from concordance across multiple arrays, it is better to preserve the native resolution of the individual arrays as much as possible. We have found that often it is preferrable to be liberal and let every clone result in a call as long as its intensity ratio that exceeds some reasonable threshold (this threshold may be element dependent). STAC won't call this a real signal unless it is seen concordantly across sufficiently many samples. Therefore if it is just noise in the array, it does not result in false positives.