ArticleBioinformatics (Oxford, England)2020
Seqminer2: an efficient tool to query and retrieve genotypes for statistical genetics analyses from biobank scale sequence dataset.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- KidneyGenAfrica multi-cohort Genome-wide association study and polygenic prediction of kidney function in 110,000 Africans.Nature communications · 2026Pooled it
- Scalable and accurate rare variant meta-analysis with Meta-SAIGE.Nature genetics · 2025Pooled it
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Authors and funding
5 authors.
Funding
Abstract
summaryHere, we present a highly efficient R-package seqminer2 for querying and retrieving sequence variants from biobank scale datasets of millions of individuals and hundreds of millions of genetic variants. Seqminer2 implements a novel variant-based index for querying VCF/BCF files. It improves the speed of query and retrieval by several magnitudes compared to the state-of-the-art tools based upon tabix. It also reimplements support for BGEN and PLINK format, which improves speed over alternative implementations. The improved efficiency and comprehensive support for popular file formats will facilitate method development, software prototyping and data analysis of biobank scale sequence datasets in R. AVAILABILITY AND IMPLEMENTATION: The seqminer2 R package is available from https://github.com/zhanxw/seqminer. Scripts used for the benchmarks are available in https://github.com/yang-lina/seqminer/blob/master/seqminer2%20benchmark%20script.txt. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
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