Second-generation PLINK: rising to the challenge of larger and richer datasets
By Christopher C. Chang, Carson C. Chow, Laurent Tellier, Shashaank Vattikuti, Shaun Purcell, James J. Lee. GigaScience, 2014
11,330 citations recorded by the source corpus.
BackgroundPLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for faster and scalable implementations of key functions, such as logistic regression, linkage disequilibrium estimation, and genomic distance evaluation. In addition, GWAS and population-genetic data now frequently contain genotype likelihoods, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1’s primary data format.FindingsTo address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, On $O\left (\sqrt {n}\right)$ -time/constant-space Hardy-Weinberg equilibrium and Fisher’s exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. We have also developed an extension to the data format which adds low-overhead support for genotype likelihoods, phase, multiallelic variants, and reference vs. alternate alleles, which is the basis of our planned second release (PLINK 2.0).ConclusionsThe second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.
Subfields: Genetics
View Paper: https://www.semanticscholar.org/paper/91e0bb69106b4e8620a1f4ee1d98e0046baafed4
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Citations in the corpus
- A resource-efficient tool for mixed model association analysis of large-scale data (2019, methodology): “We then compared the discovery power between the two sets by the clumping analysis in PLINK2 20 ( P -value threshold = 5 ´ 10 -9 , window size = 5 Mb, and LD r 2 threshold = 0.01).”
- PRSice-2: Polygenic Risk Score software for biobank-scale data (2019, neutral): “9 [17] has been incorporated to optimize computation.”
- Signals of polygenic adaptation on height have been overestimated due to uncorrected population structure in genome-wide association studies (2018, positive): “674 [31] Chang CC, Chow CC, Tellier LCAM, Vattikuti S, Purcell SM, Lee JJ.”