PIPE-CLIP: a comprehensive online tool for CLIP-seq data analysis

CLIP-seq is widely used to study genome-wide interactions between RNA-binding proteins and RNAs. However, there are few tools available to analyze CLIP-seq data, thus creating a bottleneck to the implementation of this methodology. Here, we present PIPE-CLIP, a Galaxy framework-based comprehensive online pipeline for reliable analysis of data generated by three types of CLIP-seq protocol: HITS-CLIP, PAR-CLIP and iCLIP. PIPE-CLIP provides both data processing and statistical analysis to determine candidate cross-linking regions, which are comparable to those regions identified from the original studies or using existing computational tools. PIPE-CLIP is available at http://pipeclip.qbrc.org/.

[1]  J. Greenblatt,et al.  RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments , 2013, Nucleic acids research.

[2]  Eduardo Eyras,et al.  DGCR8 HITS-CLIP reveals novel functions for the Microprocessor , 2012, Nature Structural &Molecular Biology.

[3]  Raja Jothi,et al.  Genome-wide identification of in vivo protein–DNA binding sites from ChIP-Seq data , 2008, Nucleic acids research.

[4]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[5]  S. Chi,et al.  An alternative mode of microRNA target recognition , 2012, Nature Structural &Molecular Biology.

[6]  Robert B Darnell,et al.  HITS‐CLIP: panoramic views of protein–RNA regulation in living cells , 2010, Wiley interdisciplinary reviews. RNA.

[7]  Robert B Darnell,et al.  Nova autoregulation reveals dual functions in neuronal splicing , 2005, The EMBO journal.

[8]  Gonçalo R. Abecasis,et al.  The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..

[9]  R. Darnell,et al.  Mapping in vivo protein-RNA interactions at single-nucleotide resolution from HITS-CLIP data , 2011, Nature Biotechnology.

[10]  C. Glass,et al.  Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. , 2010, Molecular cell.

[11]  Renato Paro,et al.  Mixture models and wavelet transforms reveal high confidence RNA-protein interaction sites in MOV10 PAR-CLIP data , 2012, Nucleic acids research.

[12]  Chris Sander,et al.  RNA targets of wild-type and mutant FET family proteins , 2011, Nature Structural &Molecular Biology.

[13]  Mohsen Khorshid,et al.  CLIPZ: a database and analysis environment for experimentally determined binding sites of RNA-binding proteins , 2010, Nucleic Acids Res..

[14]  Julian König,et al.  Analysis of CLIP and iCLIP methods for nucleotide-resolution studies of protein-RNA interactions , 2012, Genome Biology.

[15]  A. Agresti.  Categorical data analysis , 1993 .

[16]  R. Fisher.  Statistical methods for research workers , 1927, Protoplasma.

[17]  Tyson A. Clark,et al.  HITS-CLIP yields genome-wide insights into brain alternative RNA processing , 2008, Nature.

[18]  Uwe Ohler,et al.  PARalyzer: definition of RNA binding sites from PAR-CLIP short-read sequence data , 2011, Genome Biology.

[19]  N. Rajewsky,et al.  Transcriptome-wide analysis of regulatory interactions of the RNA-binding protein HuR. , 2011, Molecular cell.

[20]  M. Kiebler,et al.  Faculty Opinions recommendation of Argonaute HITS-CLIP decodes microRNA-mRNA interaction maps. , 2009 .

[21]  Andrew D. Smith,et al.  Site identification in high-throughput RNA-protein interaction data , 2012, Bioinform..

[22]  R. Darnell,et al.  The neuronal RNA-binding protein Nova-2 is implicated as the autoantigen targeted in POMA patients with dementia. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[23]  Donny D. Licatalosi,et al.  RNA processing and its regulation: global insights into biological networks , 2010, Nature Reviews Genetics.

[24]  Eric R. Ziegel,et al.  An Introduction to Generalized Linear Models , 2002, Technometrics.

[25]  Jimin Pei,et al.  Cell-free Formation of RNA Granules: Bound RNAs Identify Features and Components of Cellular Assemblies , 2012, Cell.

[26]  R. Darnell,et al.  The neuronal RNA binding protein Nova-1 recognizes specific RNA targets in vitro and in vivo , 1997, Molecular and cellular biology.

[27]  Jernej Ule,et al.  CLIP Identifies Nova-Regulated RNA Networks in the Brain , 2003, Science.

[28]  J. Ule,et al.  iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution , 2010, Nature Structural &Molecular Biology.

[29]  R. Darnell,et al.  Nova Regulates GABAA Receptor γ2 Alternative Splicing via a Distal Downstream UCAU-Rich Intronic Splicing Enhancer , 2003, Molecular and Cellular Biology.

[30]  Scott B. Dewell,et al.  Transcriptome-wide Identification of RNA-Binding Protein and MicroRNA Target Sites by PAR-CLIP , 2010, Cell.

[31]  Clifford A. Meyer,et al.  Model-based Analysis of ChIP-Seq (MACS) , 2008, Genome Biology.

[32]  Masato Yano,et al.  Ptbp2 represses adult-specific splicing to regulate the generation of neuronal precursors in the embryonic brain. , 2012, Genes & development.

[33]  Hsien-Da Huang,et al.  A computational approach for identifying microRNA-target interactions using high-throughput CLIP and PAR-CLIP sequencing , 2013, BMC Genomics.