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Related Concept Videos

RNA-seq03:21

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 microarray-based...

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Related Experiment Video

Updated: May 9, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

ASPeak: an abundance sensitive peak detection algorithm for RIP-Seq.

Alper Kucukural1, Hakan Özadam, Guramrit Singh

  • 1Department of Biochemistry and Molecular Pharmacology, Howard Hughes Medical Institute, University of Massachusetts Medical School, Worcester, MA 01605 and Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.

Bioinformatics (Oxford, England)
|August 10, 2013
PubMed
Summary
This summary is machine-generated.

Identifying RNA-protein binding sites is challenging due to variable RNA levels. ASPeak (abundance sensitive peak detection algorithm) offers a robust solution for sensitive motif finding and functional analysis in RNA immunoprecipitation data.

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Introductory Analysis and Validation of CUT&RUN Sequencing Data
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Introductory Analysis and Validation of CUT&RUN Sequencing Data

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Last Updated: May 9, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Introductory Analysis and Validation of CUT&RUN Sequencing Data
04:58

Introductory Analysis and Validation of CUT&RUN Sequencing Data

Published on: December 13, 2024

Area of Science:

  • Bioinformatics
  • Molecular Biology
  • Genomics

Background:

  • RNA abundances exhibit significant variability, posing challenges for identifying RNA-protein binding sites from sequencing data.
  • Existing peak identification tools are primarily designed for ChIP-Seq and are not optimized for RNA-binding protein datasets.
  • Accurate identification of RNA-protein interactions is crucial for understanding gene regulation.

Purpose of the Study:

  • To introduce ASPeak, a novel bioinformatics tool for detecting RNA-protein binding sites.
  • To address the specific challenges associated with analyzing RNA-binding protein data.
  • To enable sensitive motif finding and downstream functional analyses.

Main Methods:

  • ASPeak is an abundance-sensitive peak detection algorithm.
  • The algorithm was previously applied to detect peaks in exon junction complex RNA immunoprecipitation experiments.
  • ASPeak is implemented as a Perl pipeline accepting bedGraph files.

Main Results:

  • ASPeak provides stringent and robust target sets for RNA-protein binding sites.
  • The algorithm facilitates sensitive motif discovery.
  • Enables effective downstream functional analyses of identified binding sites.

Conclusions:

  • ASPeak is a valuable bioinformatics tool for identifying RNA-protein binding sites.
  • It overcomes limitations of existing methods for analyzing RNA-binding protein data.
  • The tool supports sensitive motif finding and functional analysis, advancing RNA biology research.