High-throughput sequencing technologies have been widely used in modern genomics studies. Due to experimental/technical issues, diverse sources of biases can be introduced into the sequencing data and subsequently disturb the downstream analysis. In the talk, I will use ChIP-seq as an example to demonstrate how we improved the downstream analysis by accounting for biases. I will discuss the effects of GC-content bias in large ChIP-seq datasets and our proposed statistical method to account for this bias in protein binding quantification.