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Prober: A general toolkit for analyzing sequencing-based ‘toeprinting’ assays
Open accessPreprint — published as 10.1016/j.cels.2017.04.007 · Paper page
Abstract
SUMMARY: A number of high-throughput transcriptase drop-off assays have recently been developed to probe post-transcriptional dynamics of RNA-protein interaction, RNA structure, and post-transcriptional modifications. Although these assays survey a diverse set of ‘epitranscriptomic’ marks, they share methodological similarities and as such their interpretation is predicated on addressing similar computational challenges. Among these, a key question is how to learn isoform-specific chemical modification profiles in the face of complex read multi-mapping. In this paper, we propose PROBer, the first rigorous statistical model to handle these challenges for a general set of sequencing-based ‘toeprinting’ assays.
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Metadata
- Authors
- Li, B., Tambe, A., Aviran, S., & Pachter, L.
- Affiliations
- University of California, Berkeley (US)
- University of California, Davis (US)
- California Institute of Technology (US)
- Corresponding author
- Pachter, Lior
- Venue
- Cell Systems
- Publisher
- openRxiv
- Published
- 2016-07-10
- Volume
- 4
- Issue
- 5
- Pages
- 568-574.e7
- ISSN
- 2405-4712 (ISSN-L)
- PMC
- PMC5758053
- OpenAlex
- W2612260255
- Cited by
- 15
- References
- 1
- Citations by year
- 2024: 1 · 2023: 1 · 2021: 1 · 2020: 2 · 2019: 2 · 2018: 6 · 2017: 1 · 2016: 1
- FWCI
- 1.23
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cell Systems (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (HG006860)
- National Human Genome Research Institute (R00HG006860, R01HG006129)
- National Institute of General Medical Sciences (T32GM008295, P50GM102706)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA modifications and cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- RNA-protein interactions, RNA structure, RNA modification, epitranscriptomics, transcript abundance estimation, statistical models, RNA sequencing data analysis
- MeSH terms
- Algorithms, Animals, Humans, RNA, RNA Processing, Post-Transcriptional, Software, Models, Statistical, Sequence Analysis, RNA, Computational Biology, Protein Isoforms, High-Throughput Nucleotide Sequencing, Transcriptome
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