ArticleBioinformatics (Oxford, England)2018
Efficient analysis of large-scale genome-wide data with two R packages: bigstatsr and bigsnpr.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 237 papers, 6 of them syntheses that pooled it.
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Who cites it
237 citing papers in PubMed, 6 syntheses or guidelines pooled it.
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- Large-scale multi-omics analyses in Hispanic/Latino populations identify genes for cardiometabolic traits.Nature communications · 2025Pooled it
- Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure.Nature communications · 2022Pooled it
- Nidogen-1 could play a role in diabetic kidney disease development in type 2 diabetes: a genome-wide association meta-analysis.Human genomics · 2022Pooled it
- Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure.Briefings in bioinformatics · 2022Pooled it
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- Age at Autism Diagnosis in the Norwegian Mother, Father, and Child Cohort Study (MoBa): Exploring the Association With Family Well-Being.Autism : the international journal of research and practice · 2026Article
- SPLENDID incorporates continuous genetic ancestry in biobank-scale data to improve polygenic risk prediction across diverse populations.Nature methods · 2026Article
- Beyond years of schooling: Genetic associations across educational milestones in two Norwegian cohorts.PLoS genetics · 2026Article
- Novel immune-related susceptibility loci associated with pediatric steroid-sensitive nephrotic syndrome identified by a transethnic genome-wide association study.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2026Article
- Effects of the Temperature-Humidity Index on Milk Production Traits and Gene-Environment Interactions in Chinese Holstein Cows.Animals : an open access journal from MDPI · 2026Article
- Range-Wide Genetic Population Structure and Environmental Adaptation in the Eastern Oyster (Crassostrea virginica) Provides Insight for Aquaculture.Molecular ecology · 2026Article
- Performance of Polygenic Risk Scores for Atherosclerotic Cardiovascular Disease in theCirculation. Genomic and precision medicine · 2026Article
- Constructing Genetic Risk Scores: Robust Bayesian Approach through Projected Summary Statistics and Flexible Shrinkage.Journal of the American Statistical Association · 2026Article
- Blood DNA Methylation Predicts Long-Term Risk of Dementia in Prospective Cohorts.medRxiv : the preprint server for health sciences · 2026Article
177 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Genome-wide datasets produced for association studies have dramatically increased in size over the past few years, with modern datasets commonly including millions of variants measured in dozens of thousands of individuals. This increase in data size is a major challenge severely slowing down genomic analyses, leading to some software becoming obsolete and researchers having limited access to diverse analysis tools. Results: Here we present two R packages, bigstatsr and bigsnpr, allowing for the analysis of large scale genomic data to be performed within R. To address large data size, the packages use memory-mapping for accessing data matrices stored on disk instead of in RAM. To perform data pre-processing and data analysis, the packages integrate most of the tools that are commonly used, either through transparent system calls to existing software, or through updated or improved implementation of existing methods. In particular, the packages implement fast and accurate computations of principal component analysis and association studies, functions to remove single nucleotide polymorphisms in linkage disequilibrium and algorithms to learn polygenic risk scores on millions of single nucleotide polymorphisms. We illustrate applications of the two R packages by analyzing a case-control genomic dataset for celiac disease, performing an association study and computing polygenic risk scores. Finally, we demonstrate the scalability of the R packages by analyzing a simulated genome-wide dataset including 500 000 individuals and 1 million markers on a single desktop computer. Availability and implementation: https://privefl.github.io/bigstatsr/ and https://privefl.github.io/bigsnpr/. Supplementary information: Supplementary data are available at Bioinformatics online.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.