title: Assessing Computational Steps for CLIP-Seq Data Analysis.
abstract: RNA-binding protein (RBP) is a key player in regulating gene expression at the posttranscriptional level. CLIP-Seq, with the ability to provide a genome-wide map of protein-RNA interactions, has been increasingly used to decipher RBP-mediated posttranscriptional regulation. Generating highly reliable binding sites from CLIP-Seq requires not only stringent library preparation but also considerable computational efforts. Here we presented a first systematic evaluation of major computational steps for identifying RBP binding sites from CLIP-Seq data, including preprocessing, the choice of control samples, peak normalization, and motif discovery. We found that avoiding PCR amplification artifacts, normalizing to input RNA or mRNAseq, and defining the background model from control samples can reduce the bias introduced by RNA abundance and improve the quality of detected binding sites. Our findings can serve as a general guideline for CLIP experiments design and the comprehensive analysis of CLIP-Seq data.
authors.affiliation: Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, TN 37232, USA ; Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
authors.forename: Qi
authors.initials: Q
authors.lastname: Liu
authors.affiliation: Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
authors.forename: Xue
authors.initials: X
authors.lastname: Zhong
authors.affiliation: Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA.
authors.forename: Blair B
authors.initials: BB
authors.lastname: Madison
authors.affiliation: Division of Gastroenterology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA ; Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA ; Abramson Cancer Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
authors.forename: Anil K
authors.initials: AK
authors.lastname: Rustgi
authors.affiliation: Center for Quantitative Sciences, Vanderbilt University School of Medicine, Nashville, TN 37232, USA ; Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA ; Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
authors.forename: Yu
authors.initials: Y
authors.lastname: Shyr
mesh_terms: D001665:Binding Sites / Q000235:genetics; D018938:Caco-2 Cells; D005786:Gene Expression Regulation; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D035683:MicroRNAs / Q000235:genetics; D012333:RNA, Messenger / Q000235:genetics* / Q000378:metabolism; D016601:RNA-Binding Proteins / Q000235:genetics* / Q000378:metabolism; D017423:Sequence Analysis, RNA
chemical_list: D035683:MicroRNAs; D012333:RNA, Messenger; D016601:RNA-Binding Proteins