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Related Experiment Video

Updated: May 2, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

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Published on: June 23, 2012

On detecting incomplete soft or hard selective sweeps using haplotype structure.

Anna Ferrer-Admetlla¹, Mason Liang, Thorfinn Korneliussen

¹Department of Integrative Biology, University of California at Berkeley, Berkeley.

Molecular Biology and Evolution

|February 21, 2014

Summary

This summary is machine-generated.

We developed a new statistic, nSL, to detect selection in population genomic data. It is robust to recombination rate variation and effective for identifying sweeps from standing variation and incomplete sweeps.

Keywords:

SFS-based methods cholesterol demography haplotype-based methods hard sweeps recombination rate soft sweeps

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Last Updated: May 2, 2026

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Published on: August 3, 2018

Area of Science:

Population Genetics
Evolutionary Biology
Genomics

Background:

Detecting positive selection is crucial for understanding adaptation.
Existing methods for detecting selection, such as haplotype and site frequency spectrum (SFS)-based methods, have limitations.
Robust methods are needed to identify various types of selection sweeps.

Purpose of the Study:

To introduce a novel haplotype-based statistic, nSL, for detecting soft and hard sweeps in population genomic data.
To evaluate the performance of nSL compared to existing methods.
To investigate the evolutionary pressures on genes related to lipid metabolism in the Yoruban population.

Main Methods:

Development of the nSL statistic for analyzing population genomic data.
Comparison of nSL with classic haplotype and SFS-based methods.
Application of nSL to HapMap3 data, specifically the Yoruban population.

Main Results:

The nSL statistic demonstrates robustness to recombination rate variation and demographic model assumptions.
nSL exhibits high power for detecting sweeps from standing variation and incomplete sweeps.
Analysis of Yoruban population data revealed significant evidence of selection on lipid metabolism genes.

Conclusions:

nSL is a powerful and robust statistic for detecting selection, outperforming existing methods in several scenarios.
The identified selection on lipid metabolism genes in the Yorubans may be linked to pleiotropic effects of blood parasite resistance.
This finding offers insights into the evolutionary history and adaptation of human populations.