| Chapter title |
Finding RNA–Protein Interaction Sites Using HMMs
|
|---|---|
| Chapter number | 13 |
| Book title |
Hidden Markov Models
|
| Published in |
Methods in molecular biology, February 2017
|
| DOI | 10.1007/978-1-4939-6753-7_13 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6751-3, 978-1-4939-6753-7
|
| Authors |
Tao Wang, Jonghyun Yun, Yang Xie, Guanghua Xiao |
| Editors |
David R. Westhead, M. S. Vijayabaskar |
| Abstract |
RNA-binding proteins play important roles in the various stages of RNA maturation through binding to its target RNAs. Cross-linking immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq) has made it possible to identify the targeting sites of RNA-binding proteins in various cell culture systems and tissue types on a genome-wide scale. Several Hidden Markov model-based (HMM) approaches have been suggested to identify protein-RNA binding sites from CLIP-Seq datasets. In this chapter, we describe how HMM can be applied to analyze CLIP-Seq datasets, including the bioinformatics preprocessing steps to extract count information from the sequencing data before HMM and the downstream analysis steps following peak-calling. |
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