intermediate 8 min read
Life sciences · Topic
Linkage Disequilibrium
probability theory · information theory · hypothesis testing
Linkage disequilibrium (LD) is the non-random association of alleles at two or more loci in a population. It is fundamental to GWAS fine-mapping, haplotype analysis, and polygenic score construction. LD decays with recombination over generations, creating a characteristic block structure across the genome.

The $D$ Statistic

For two biallelic loci with alleles $A/a$ (frequencies $p_A, p_a$) and $B/b$ (frequencies $p_B, p_b$), the disequilibrium coefficient is:

\[D = p_{AB} - p_A p_B\]

where $p_{AB}$ is the observed haplotype frequency. Under linkage equilibrium $D = 0$. $D$ ranges between $D_{\min}$ and $D_{\max}$, which depend on allele frequencies.

Normalised Measures

Two standardised measures dominate the literature:

\[D' = \frac{D}{D_{\max}} \quad \text{if } D > 0, \qquad D' = \frac{D}{D_{\min}} \quad \text{if } D < 0\] \[r^2 = \frac{D^2}{p_A\, p_a\, p_B\, p_b}\]

$|D’| = 1$ indicates no recombination has been observed between the haplotypes; $r^2 = 1$ indicates complete allelic correlation (perfect proxies). $r^2$ is the more useful metric for GWAS power because it directly determines the loss of power when using a proxy SNP: effective sample size scales as $N \cdot r^2$.

Decay with Recombination

LD decays geometrically each generation under random mating:

\[D_t = D_0\,(1 - c)^t\]

where $c$ is the recombination fraction between loci and $t$ is the number of generations. At $c = 0.5$ (unlinked loci), LD halves each generation. In humans, substantial LD typically extends 10–100 kb.

Haplotype Blocks and LD Pruning

Operation Definition    
Haplotype block Genomic region with limited historical recombination and high internal $ D’ $
LD pruning Remove SNPs within a window until no pair exceeds an $r^2$ threshold (e.g., $r^2 > 0.1$)    
LD clumping Keep the most-significant SNP per locus; assign nearby SNPs at $r^2 > $ threshold to it    

LD-independent SNP sets from pruning are used for PCA, heritability estimation, and relatedness calculation.