  A topological multiple testing approach to peak detection is proposed for the
problem of detecting transcription factor binding sites in ChIP-Seq data. After
kernel smoothing of the tag counts over the genome, the presence of a peak is
tested at each observed local maximum, followed by multiple testing correction
at the desired false discovery rate level. Valid p-values for candidate peaks
are computed via Monte Carlo simulations of smoothed Poisson sequences, whose
background Poisson rates are obtained via linear regression from a Control
sample at two different scales. The proposed method identifies nearby binding
sites that other methods do not.
