Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Autoencoder/RandomForest-TabPFN for cross-cancer metabolomics: prostate and breast cancer diagnosis using paper spray and ion mobility-mass spectrometry techniques.

GigaScience·2026

Same author

A leader-repeat hairpin blocks extraneous CRISPR RNA production in diverse CRISPR-Cas13 systems.

The EMBO journal·2026

Same author

Functional outcome after vertical parasagittal hemispherotomy in pediatric hemimegalencephaly: Insights from a single case.

Surgical neurology international·2026

Same author

Comprehensive analysis of CRISPR array repeat mutations reveals subtype-specific patterns and links to spacer dynamics.

microLife·2026

Same author

The complexity of multiple CRISPR arrays in strains with (co-occurring) CRISPR systems.

microLife·2026

Same author

CoMPaseD: advanced planning of proteomic experiments aiming to identify small proteins.

microLife·2026

Same journal

Chromosomal scale genome assembly of medicinal plant Sophora tonkinensis.

BMC genomics·2026

Same journal

Variant-specific RNA testing resolves variants of uncertain significance in exome testing.

BMC genomics·2026

Same journal

Kaiso overexpression promotes an interferon immune response in murine intestines.

BMC genomics·2026

Same journal

Genomic evidence of ecological flexibility and cross-niche CRISPR spacerome targeting phage-plasmid hybrids in Latilactobacillus curvatus.

BMC genomics·2026

Same journal

Fgf evolution in vertebrates: insights from cyclostomes.

BMC genomics·2026

Same journal

Metabolic reprogramming, oxidative stress, and mitophagy in JSRV Env-transformed BEAS-2B cells: insights from integrated transcriptomics and metabolomics.

BMC genomics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Nov 25, 2025

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Improving CLIP-seq data analysis by incorporating transcript information.

Michael Uhl¹, Van Dinh Tran¹, Rolf Backofen^2,3

¹Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, Freiburg, 79110, Germany.

|December 18, 2020

Summary

This summary is machine-generated.

RNA-binding protein (RBP) analysis using CLIP-seq data can be improved by incorporating transcript information. This study highlights how considering splicing events enhances RBP binding site prediction accuracy.

Keywords:

CLIP-seq Peak calling RBP binding site prediction eCLIP

More Related Videos

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

RNA-Seq Analysis of Differential Gene Expression in Electroporated Chick Embryonic Spinal Cord

RNA-Seq Analysis of Differential Gene Expression in Electroporated Chick Embryonic Spinal Cord

Published on: November 1, 2014

Related Experiment Videos

Last Updated: Nov 25, 2025

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

RNA-Seq Analysis of Differential Gene Expression in Electroporated Chick Embryonic Spinal Cord

RNA-Seq Analysis of Differential Gene Expression in Electroporated Chick Embryonic Spinal Cord

Published on: November 1, 2014

Area of Science:

Molecular Biology
Bioinformatics
Genomics

Background:

Current RNA-binding protein (RBP) CLIP-seq analysis methods focus on genomic read profiles.
These methods overlook crucial transcript information, specifically splicing events, potentially leading to inaccuracies.

Purpose of the Study:

To investigate the impact of transcript information on RNA-binding protein (RBP) binding site identification in CLIP-seq data.
To evaluate the susceptibility of current peak calling tools to errors near exon borders.

Main Methods:

Quantified false peak calling near exon borders in public CLIP-seq datasets.
Developed and utilized CLIPcontext tool for extracting transcript and genomic context sequences.
Assessed the effect of context choice on RBP binding site prediction tool performance.
Analyzed enrichment of known RBP motifs in transcript context sites.

Main Results:

Current peak callers exhibit significant false positive rates near exon borders in CLIP-seq data.
The choice of sequence context demonstrably impacts the performance of RBP binding site prediction tools.
Known motifs for exon-binding RBPs are frequently found in transcript context, suggesting improved site recovery.

Conclusions:

Incorporating transcript information is crucial for accurate CLIP-seq data analysis.
Future peak calling and downstream analysis tools should integrate transcript information for enhanced RBP binding site identification.