omniCLIP: probabilistic identification of protein-RNA interactions from CLIP-seq data
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 probab...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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BMC
2018-11-01
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| Series: | Genome Biology |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13059-018-1521-2 |
| _version_ | 1819161436686909440 |
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| author | Philipp Drewe-Boss Hans-Hermann Wessels Uwe Ohler |
| author_facet | Philipp Drewe-Boss Hans-Hermann Wessels Uwe Ohler |
| author_sort | Philipp Drewe-Boss |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-22T17:12:19Z |
| format | Article |
| id | doaj.art-fed1e40fc1db4685a5d9f0ac304a5a1a |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-12-22T17:12:19Z |
| publishDate | 2018-11-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-fed1e40fc1db4685a5d9f0ac304a5a1a2022-12-21T18:19:03ZengBMCGenome Biology1474-760X2018-11-0119111410.1186/s13059-018-1521-2omniCLIP: probabilistic identification of protein-RNA interactions from CLIP-seq dataPhilipp Drewe-Boss0Hans-Hermann Wessels1Uwe Ohler2Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz AssociationBerlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz AssociationBerlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz AssociationAbstract 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.http://link.springer.com/article/10.1186/s13059-018-1521-2Machine learningBioinformaticsProtein-RNA interactionsCLIP-seqeCLIPiCLIP |
| spellingShingle | Philipp Drewe-Boss Hans-Hermann Wessels Uwe Ohler omniCLIP: probabilistic identification of protein-RNA interactions from CLIP-seq data Genome Biology Machine learning Bioinformatics Protein-RNA interactions CLIP-seq eCLIP iCLIP |
| title | omniCLIP: probabilistic identification of protein-RNA interactions from CLIP-seq data |
| title_full | omniCLIP: probabilistic identification of protein-RNA interactions from CLIP-seq data |
| title_fullStr | omniCLIP: probabilistic identification of protein-RNA interactions from CLIP-seq data |
| title_full_unstemmed | omniCLIP: probabilistic identification of protein-RNA interactions from CLIP-seq data |
| title_short | omniCLIP: probabilistic identification of protein-RNA interactions from CLIP-seq data |
| title_sort | omniclip probabilistic identification of protein rna interactions from clip seq data |
| topic | Machine learning Bioinformatics Protein-RNA interactions CLIP-seq eCLIP iCLIP |
| url | http://link.springer.com/article/10.1186/s13059-018-1521-2 |
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