Abstract

With the recent Precision Medicine Initiative, more institutions are focusing on technical innovation and method improvement in high-throughput sequencing experiments. We first review recent technique progresses in profiling DNA methylation, then as data quality and alignment efficiency of sequencing profiles are directly related to the reliability and reproducibility of high-throughput experiments, we repurpose the prevalent ChIP-sequencing technique and emphasize on sequencing data quality and alignment efficiency. Till now, there is no tool yet specifically designed for optimal peak alignment estimation or quality-related genomic feature extraction for ChIP-sequencing profiles. Finally, we introduce our recent proposed pipeline, embedded with optimization-based peak aligner (COPAR), to interrogate the optimal peak alignment and inherent genomic features from NGS experiments. It provides a versatile perspective for biologists to perform quality-check for NGS experiments and optimize their experiment design. COPAR can process mapped read file in BED format and output statistically sound results for biological experiments.

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