The antisense transcription pipeline is intended to be used on strand specific RNA-Seq libraries to find regions which show significant levels of antisense transcription.
It works by taking a set of known features (usually genes but could be exons microRNAs or anything else which makes sense), and intially finding the overall level of antisense reads over the whole genome. Any strand specific library will contain some mapped reads from the wrong strand, and we assume that overall the level of antisense transcription over all genes is low enough that we can consider it as noise.
Once the global antisense level has been measured we can go back and test each gene individually. A binomial distribution is used to determine how likely we see the observed number of antisense reads in a region, given the total number of reads seen there and the global rate of antisense transcription. After calculating this value for each feature the set of p-values is corrected using a Benjamini and Hochberg multiple testing correction. Each probe is quantitated by the obs/exp ratio for antisense reads, but alongside that a probe list is constructed for each data store which contains the list of features whose antisense level passed the significance threshold set in the pipeline options.