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Updated: May 25, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

Breakpointer: using local mapping artifacts to support sequence breakpoint discovery from single-end reads.

Ruping Sun¹, Michael I Love, Tomasz Zemojtel

¹Department of Computational Molecular Biology, Max-Planck-Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. ruping@molgen.mpg.de

Bioinformatics (Oxford, England)

|February 4, 2012

Summary

This summary is machine-generated.

Breakpointer is a new algorithm that efficiently finds structural variant breakpoints using single-end reads from next-generation sequencing. It identifies variants missed by other methods, improving structural variant detection.

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Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Published on: August 24, 2017

Area of Science:

Genomics
Bioinformatics

Background:

Structural variants (SVs) are crucial in genomic research.
Accurate detection of SVs from sequencing data is challenging.

Purpose of the Study:

To develop a fast algorithm for locating structural variant breakpoints.
To improve the detection of SVs, especially those missed by existing methods.

Main Methods:

Developed Breakpointer, a novel algorithm for breakpoint detection.
Utilizes local non-uniform read distribution and misalignments.
Scans single-end read alignments to identify potential breakpoint regions.

Main Results:

Breakpointer efficiently locates breakpoints of structural variants.
Identifies insertions longer than read length.
Detects SVs in repetitive regions potentially missed by other tools.

Conclusions:

Breakpointer is a valuable addition to existing methods for SV detection.
Enhances the analysis of single-end reads for comprehensive SV identification.