Here we developed a novel analysis framework named MACE (model-based analysis of ChIP-exo) dedicated to ChIP-exo data analysis. MACExo has the following four steps: 1) sequencing data normalization and bias correction; 2) signal consolidation and noise reduction; 3) single nucleotide resolution border detection using Chebyshev Inequality; and 4) border matching using Gale-Shapley’s stable matching algorithm. When applied to yeast Reb1 and human CTCF ChIP-exo data, MACE is able to define TFBSs with higher sensitivity, specificity and spatial resolution, as evidenced by multiple criteria, such as motif enrichment, sequence conservation, nucleosome positioning, and open chromatin states.
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