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Home›Genetics›LD Block Analysis
Process / pipelineGenomic variation analysis

LD Block Analysis

Linkage Disequilibrium Block Analysis and Haplotype Mapping · Also known as: Haplotype block analysis, LD mapping, Block structure analysis

Linkage disequilibrium (LD) block analysis is a genomic method that partitions the human genome into distinct haplotype blocks—regions of limited recombination where variants are in strong statistical association. First systematically described by Gabriel and colleagues in 2002, this approach reveals the underlying structure of genetic variation and enables efficient genomic studies by reducing the number of variants needed to capture common diversity. LD block analysis forms the foundation of genome-wide association study (GWAS) design and modern population genetics.

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LD Block Analysis
Admixture AnalysisF-statistics (FST)IBD MappingPolygenic Risk ScoreQTL MappingGCTA

When to use it

LD block analysis is essential for designing efficient genome-wide association studies, as it identifies tag SNPs that capture most common variation. It is particularly informative in recently admixed or founder populations where LD extends over longer genomic distances. Apply this method whenever you need to understand fine-scale linkage patterns, design SNP arrays, or interpret regional association signals. Avoid it for very small, non-representative samples where LD estimates are unreliable.

Strengths & limitations

Strengths
  • Reveals hidden structure in genetic variation across the genome
  • Enables efficient study design by identifying tag SNPs that capture diversity
  • Provides insights into recombination patterns and population history
  • Works well with standard SNP array data
  • Allows quick filtering of redundant variants for computationally intensive analyses
Limitations
  • Block boundaries are population-specific and change between populations with different demographic histories
  • LD extends differently across populations, making cross-population transferability limited
  • Defining block boundaries is somewhat arbitrary and depends on threshold choices
  • Rare variants are not well-captured by LD block analysis
  • Complex recombination patterns in some regions make block definition ambiguous

Frequently asked

What is the difference between r-squared and D-prime for measuring linkage disequilibrium?

r-squared (r²) measures the proportion of variance in allele frequencies explained by linkage. D-prime (D') measures the normalized deviation from linkage equilibrium and ranges from 0 to 1. D' is more sensitive to rare alleles and is often used to define LD blocks, while r² is more useful for predicting one allele from another.

Why does LD structure differ between populations?

Population history shapes LD. Populations with recent bottlenecks (founder effects) or admixture have longer-range LD. Populations with large, stable histories have shorter LD because more recombination has occurred. Migration and admixture also create population-specific block structures.

What are tag SNPs, and why are they important?

Tag SNPs are a small subset of markers within an LD block that capture most haplotypic diversity. Genotyping only tag SNPs is far more cost-effective than genotyping all variants, while retaining power to detect associations. This principle enabled the original HapMap Project and efficient GWAS design.

Can LD block analysis help with fine-mapping causal variants?

LD block analysis provides context for fine-mapping but does not directly identify causal variants. However, understanding LD structure helps prioritize variants for functional follow-up and determines how many variants must be examined to capture likely causal alleles.

Sources

  1. Gabriel, S. B., Schaffner, S. F., Nguyen, H., Moore, J. M., Roy, J., Blumenstiel, B., & Lander, E. S. (2002). The structure of haplotype blocks in the human genome. Science, 296(5576), 2225–2229. DOI: 10.1126/science.1069424 ↗
  2. Daly, M. J., Rioux, J. D., Schaffner, S. F., Hudson, T. J., & Lander, E. S. (2001). High-resolution haplotype structure in the human genome. Nature Genetics, 29(2), 229–232. DOI: 10.1038/ng1001-229 ↗
  3. Wang, N., Akey, J. M., Zhang, K., Chakraborty, R., & Jin, L. (2005). Distribution of recombination crossovers and the origin of block-like patterns of linkage disequilibrium. Genetics, 155(4), 1599–1606. link ↗

How to cite this page

ScholarGate. (2026, June 3). Linkage Disequilibrium Block Analysis and Haplotype Mapping. ScholarGate. https://scholargate.app/en/genetics/ld-block-analysis

Related methods

Admixture AnalysisF-statistics (FST)IBD MappingPolygenic Risk ScoreQTL Mapping

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

  • Admixture AnalysisGenetics↔ compare
  • F-statistics (FST)Genetics↔ compare
  • IBD MappingGenetics↔ compare
  • Polygenic Risk ScoreGenetics↔ compare
  • QTL MappingGenetics↔ compare
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Referenced by

Admixture AnalysisF-statistics (FST)GCTAIBD MappingPolygenic Risk ScoreQTL Mapping

Similar methods

Genome-wide association studyQTL MappingMachine learning-assisted genome-wide association studyIBD MappingAdmixture AnalysisBayesian GWASeQTL AnalysisF-statistics (FST)

Related reference concepts

Linkage Disequilibrium and SNP TaggingLinkage DisequilibriumHaplotype Blocks and Population-Level Structural OrganizationGenome-Wide Association Studies and Variant DiscoveryQTL and Complex Trait MappingPopulation Stratification and Ancestry in GWAS

Spotted an issue on this page? Report or suggest a fix →

ScholarGate — LD Block Analysis (Linkage Disequilibrium Block Analysis and Haplotype Mapping). Retrieved 2026-07-21 from https://scholargate.app/en/genetics/ld-block-analysis · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Shaun Gabriel & Eric Lander
Subfamily
Genomic variation analysis
Year
2002
Type
Haplotype analysis method
Related methods
Admixture AnalysisF-statistics (FST)IBD MappingPolygenic Risk ScoreQTL Mapping
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