A software to analyze data generated by short read sequencers. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. It offers four important utilities for predicting protein-DNA interaction sites from ChIP-Seq. First, it improves the spatial resolution of the predicted sites by empirically modeling the distance d and shifting tags by d/2. Second, MACS uses a dynamic λ local parameter to capture local biases in the genome and improves the robustness and specificity of the prediction. Third, MACS can be applied to ChIP-Seq experiments without controls, and to those with controls with improved performance. Last but not least, MACS is easy to use and provides detailed information for each peak.