ArticleNucleic acids research2017
CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed.
- Guidelines to Study Transcriptome Remodeling by Proteins Using Deep Sequencing (RNA-Seq).Methods in molecular biology (Clifton, N.J.) · 2027Article
- Signal or noise? RNA-binding proteins and the challenges of binding site assignments.Nucleic acids research · 2026Review
- Molecular interactome of HNRNPU reveals regulatory networks in neuronal differentiation and DNA methylation.Nucleic acids research · 2026Article
- The striatal heterogeneous nuclear ribonucleoprotein H1 mRNA targetome associated with methamphetamine administration and behavior.Progress in neuro-psychopharmacology & biological psychiatry · 2026Article
- Transcriptome-wide mapping reveals an RNA-dependent mechanism of platinum cancer drugs.bioRxiv : the preprint server for biology · 2025Article
- Cell type- and factor-specific nonsense-mediated RNA decay.Nucleic acids research · 2025Article
- Peak analysis of cell-free RNA finds recurrently protected narrow regions with clinical potential.Genome biology · 2025Article
- Melon: metagenomic long-read-based taxonomic identification and quantification using marker genes.Genome biology · 2024Article
- Protocol to process crosslinking and immunoprecipitation data into annotated binding sites.STAR protocols · 2024Article
- Nuclear RNA catabolism controls endogenous retroviruses, gene expression asymmetry, and dedifferentiation.Molecular cell · 2023Article
- The RNA helicase DDX39A binds a conserved structure in chikungunya virus RNA to control infection.Molecular cell · 2023Article
- Skipper analysis of eCLIP datasets enables sensitive detection of constrained translation factor binding sites.Cell genomics · 2023Article
- Mapping PTBP2 binding in human brain identifies SYNGAP1 as a target for therapeutic splice switching.Nature communications · 2023Article
- Improved analysis of (e)CLIP data with RCRUNCH yields a compendium of RNA-binding protein binding sites and motifs.Genome biology · 2023Article
- The role of N6-methyladenosine-modified non-coding RNAs in the pathological process of human cancer.Cell death discovery · 2022Review
- Translocated Legionella pneumophila small RNAs mimic eukaryotic microRNAs targeting the host immune response.Nature communications · 2022Article
- Large-Scale Analysis of RNA-Protein Interactions for Functional RNA Motif Discovery Using FOREST.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Bioinformatics Approaches for Determining the Functional Impact of Repetitive Elements on Non-coding RNAs.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Spatial correlation statistics enable transcriptome-wide characterization of RNA structure binding.Cell reports methods · 2021Article
- mThe EMBO journal · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Crosslinking or RNA immunoprecipitation followed by sequencing (CLIP-seq or RIP-seq) allows transcriptome-wide discovery of RNA regulatory sites. As CLIP-seq/RIP-seq reads are short, existing computational tools focus on uniquely mapped reads, while reads mapped to multiple loci are discarded. We present CLAM (CLIP-seq Analysis of Multi-mapped reads). CLAM uses an expectation-maximization algorithm to assign multi-mapped reads and calls peaks combining uniquely and multi-mapped reads. To demonstrate the utility of CLAM, we applied it to a wide range of public CLIP-seq/RIP-seq datasets involving numerous splicing factors, microRNAs and m6A RNA methylation. CLAM recovered a large number of novel RNA regulatory sites inaccessible by uniquely mapped reads. The functional significance of these sites was demonstrated by consensus motif patterns and association with alternative splicing (splicing factors), transcript abundance (AGO2) and mRNA half-life (m6A). CLAM provides a useful tool to discover novel protein-RNA interactions and RNA modification sites from CLIP-seq and RIP-seq data, and reveals the significant contribution of repetitive elements to the RNA regulatory landscape of the human transcriptome.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.