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qLD: high-performance computation of linkage disequilibrium on CPU and GPU

Theodoris Charalabos, Alachiotis Nikolaos, Low Tze Meng, Pavlidis Pavlos

Πλήρης Εγγραφή

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Περίληψη

Linkage disequilibrium (LD) is the non-random association between alleles at different loci. Assessing LD in thousands of genomes and/or millions of single-nucleotide poly-morphisms (SNPs) exhibits excessive time and memory requirements that can potentially hinder future large-scale genomic analyses. To this end, we introduce qLD (quickLD) (https//lgithub.com/StrayLamb2lqLD), a highly optimized open-source software that assesses LD based on Pearson's correlation coefficient. qLD exploits the fact that the computational kernel for calculating LD can be cast in terms of dense linear algebra operations. In addition, the software employs memory-aware techniques to lower memory requirements, and parallel GPU architectures to further shorten analysis times. qLD delivers up to 5x faster processing than the current state-of-the-art software implementation when run on the same CPU, and up to 29x when computation is offloaded to a GPU. Furthermore, the software is designed to quantity allele associations between arbitrarily distant loci in a time-and memory-efficient way, thereby facilitating the evaluation of long-range LD and the detection of co-evolved genes. We showcase qLD on the analysis of 22,554 complete SARS-CoV-2 genomes.

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