The article presents a detailed analysis of ChIP-seq experiments for DNA-binding proteins. It introduces a data processing pipeline designed to accurately detect protein binding positions from unpaired sequence reads. The pipeline includes steps for tag alignment, background correction, and binding position detection. The authors compare the performance of several binding detection algorithms, including novel and previously described methods, and evaluate their sensitivity and spatial precision. They also analyze the relationship between sequencing depth and the characteristics of detected binding positions, and provide a method for estimating the necessary sequencing depth for desired coverage of protein binding sites. The study highlights the challenges of ChIP-seq data, including varying sequencing error rates and background tag distributions. The authors propose using strand cross-correlation profiles to assess the significance of observed binding positions and to determine the required sequencing depth. They also discuss the importance of background tag distribution in determining the statistical significance of binding positions and the need for input sequencing to account for background effects. The authors evaluate the performance of different binding detection methods, including WTD, MSP, and MTC, and find that some methods provide higher specificity and position accuracy. They also assess the statistical significance of detected binding positions using false discovery rate (FDR) and compare the results with empirical and analytical models. The study concludes that the sequencing depth required for detecting binding positions depends on the target enrichment ratio and that additional sequencing can reveal more binding sites with lower enrichment ratios. The authors also discuss the importance of considering the properties of the binding site coverage and the need for accurate sequencing depth estimation in ChIP-seq studies. They propose a method for determining the minimal fold enrichment ratio above which binding positions have been saturated at a given sequencing depth. The study emphasizes the importance of analyzing additional factors, such as sequencing biases and stability of ChIP and input tag distributions, in future studies. Finally, the authors suggest that the described techniques may be adapted for analysis of histone modifications and other widely-distributed chromatin marks.The article presents a detailed analysis of ChIP-seq experiments for DNA-binding proteins. It introduces a data processing pipeline designed to accurately detect protein binding positions from unpaired sequence reads. The pipeline includes steps for tag alignment, background correction, and binding position detection. The authors compare the performance of several binding detection algorithms, including novel and previously described methods, and evaluate their sensitivity and spatial precision. They also analyze the relationship between sequencing depth and the characteristics of detected binding positions, and provide a method for estimating the necessary sequencing depth for desired coverage of protein binding sites. The study highlights the challenges of ChIP-seq data, including varying sequencing error rates and background tag distributions. The authors propose using strand cross-correlation profiles to assess the significance of observed binding positions and to determine the required sequencing depth. They also discuss the importance of background tag distribution in determining the statistical significance of binding positions and the need for input sequencing to account for background effects. The authors evaluate the performance of different binding detection methods, including WTD, MSP, and MTC, and find that some methods provide higher specificity and position accuracy. They also assess the statistical significance of detected binding positions using false discovery rate (FDR) and compare the results with empirical and analytical models. The study concludes that the sequencing depth required for detecting binding positions depends on the target enrichment ratio and that additional sequencing can reveal more binding sites with lower enrichment ratios. The authors also discuss the importance of considering the properties of the binding site coverage and the need for accurate sequencing depth estimation in ChIP-seq studies. They propose a method for determining the minimal fold enrichment ratio above which binding positions have been saturated at a given sequencing depth. The study emphasizes the importance of analyzing additional factors, such as sequencing biases and stability of ChIP and input tag distributions, in future studies. Finally, the authors suggest that the described techniques may be adapted for analysis of histone modifications and other widely-distributed chromatin marks.