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| Item Type: | Article | ||||
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| Title: | omniCLIP: probabilistic identification of protein-RNA interactions from CLIP-seq data | ||||
| Creators Name: | Drewe-Boss, P. and Wessels, H.H. and Ohler, U. | ||||
| Abstract: | CLIP-seq methods allow the generation of genome-wide maps of RNA binding protein - RNA interaction sites. However, due to differences between different CLIP-seq assays, existing computational approaches to analyze the data can only be applied to a subset of assays. Here, we present a probabilistic model called omniCLIP that can detect regulatory elements in RNAs from data of all CLIP-seq assays. omniCLIP jointly models data across replicates and can integrate background information. Therefore, omniCLIP greatly simplifies the data analysis, increases the reliability of results and paves the way for integrative studies based on data from different assays. | ||||
| Keywords: | Machine Learning, Bioinformatics, Protein-RNA Interactions, CLIP-seq, eCLIP, iCLIP, PAR-CLIP, HITS-CLIP, Generalized Linear Models, Mixture Models | ||||
| Source: | Genome Biology | ||||
| ISSN: | 1474-760X | ||||
| Publisher: | BioMed Central | ||||
| Volume: | 19 | ||||
| Page Range: | 183 | ||||
| Date: | 1 November 2018 | ||||
| Official Publication: | https://doi.org/10.1186/s13059-018-1521-2 | ||||
| PubMed: | View item in PubMed | ||||
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