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Related Experiment Video

Updated: May 22, 2026

Chromatin Immunoprecipitation of Murine Brown Adipose Tissue

Chromatin Immunoprecipitation of Murine Brown Adipose Tissue

Published on: November 21, 2018

Haplotype and minimum-chimerism consensus determination using short sequence data.

Shawn T O'Neil¹, Scott J Emrich

¹Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. semrich@nd.edu.

|April 28, 2012

Summary

This summary is machine-generated.

Hapler software accurately assembles haplotypes from low-coverage population sequence data. It reconstructs consensus sequences, reducing chimerism and improving reliability for ecological and population studies.

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Chromatin Isolation by RNA Purification (ChIRP)

Chromatin Isolation by RNA Purification (ChIRP)

Published on: March 25, 2012

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Last Updated: May 22, 2026

Chromatin Immunoprecipitation of Murine Brown Adipose Tissue

Chromatin Immunoprecipitation of Murine Brown Adipose Tissue

Published on: November 21, 2018

Chromatin Isolation by RNA Purification (ChIRP)

Chromatin Isolation by RNA Purification (ChIRP)

Published on: March 25, 2012

Area of Science:

Population genetics
Bioinformatics
Ecoinformatics

Background:

Haplotype assembly is crucial for population-sampled data, especially in ecoinformatics.
Existing methods struggle with low-diversity, low-coverage ecological samples.
Hapler software addresses these challenges with specialized methods.

Purpose of the Study:

To introduce Hapler, a software tool for haplotype assembly from population data.
To develop methods for increasing confidence in assemblies from error-prone, ambiguous data.
To reconstruct full consensus sequences while minimizing and identifying chimeric points.

Main Methods:

Hapler utilizes specialized algorithms for low-diversity, low-coverage sequence data.
Methods were developed to enhance confidence in haplotype assemblies.
The tool reconstructs consensus sequences, identifying potential chimeric regions.

Main Results:

Simulated data experiments show Hapler effectively assembles haplotypes from gene-sized alignments.
Hapler consensus sequences exhibit less chimerism compared to majority vote and viral quasispecies estimation.
Effectiveness is maintained across varying error rates, read lengths, and population biases.

Conclusions:

Haplotype diversity analysis is vital for studies using genetically diverse sequence data, particularly in ecoinformatics.
Hapler offers robust haplotype information and identifies phasing errors in consensus sequences.
The tool provides valuable data for population studies and downstream assembly applications.