ArticlePloS one2014
FFBSKAT: fast family-based sequence kernel association test.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Methods for association analysis and meta-analysis of rare variants in families.Genetic epidemiology · 2015Pooled it
- Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits.Scientific reports · 2021Article
- Gene-Based Association Testing of Dichotomous Traits With Generalized Functional Linear Mixed Models Using Extended Pedigrees: Applications to Age-Related Macular Degeneration.Journal of the American Statistical Association · 2021Article
- Hadoop and PySpark for reproducibility and scalability of genomic sequencing studies.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2020Article
- A generalized model for combining dependent SNP-level summary statistics and its extensions to statistics of other levels.Scientific reports · 2019Article
- Exome sequencing identifies gene variants and networks associated with extreme respiratory outcomes following preterm birth.BMC genetics · 2018Article
- Analysis of genetic and nongenetic factors influencing triglycerides-lowering drug effects based on paired observations.BMC proceedings · 2018Article
- Risk Prediction Modeling on Family-Based Sequencing Data Using a Random Field Method.Genetics · 2017Article
- The Weighting is the Hardest Part: On the Behavior of the Likelihood Ratio Test and the Score Test Under a Data-Driven Weighting Scheme in Sequenced Samples.Twin research and human genetics : the official journal of the International Society for Twin Studies · 2017Article
- Multiple rare variants in high-risk pancreatic cancer-related genes may increase risk for pancreatic cancer in a subset of patients with and without germline CDKN2A mutations.Human genetics · 2016Article
- Regional heritability mapping method helps explain missing heritability of blood lipid traits in isolated populations.Heredity · 2016Article
- A novel statistical method for rare-variant association studies in general pedigrees.BMC proceedings · 2016Article
- Article
- Adaptive combination of P-values for family-based association testing with sequence data.PloS one · 2014Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The kernel machine-based regression is an efficient approach to region-based association analysis aimed at identification of rare genetic variants. However, this method is computationally complex. The running time of kernel-based association analysis becomes especially long for samples with genetic (sub) structures, thus increasing the need to develop new and effective methods, algorithms, and software packages. We have developed a new R-package called fast family-based sequence kernel association test (FFBSKAT) for analysis of quantitative traits in samples of related individuals. This software implements a score-based variance component test to assess the association of a given set of single nucleotide polymorphisms with a continuous phenotype. We compared the performance of our software with that of two existing software for family-based sequence kernel association testing, namely, ASKAT and famSKAT, using the Genetic Analysis Workshop 17 family sample. Results demonstrate that FFBSKAT is several times faster than other available programs. In addition, the calculations of the three-compared software were similarly accurate. With respect to the available analysis modes, we combined the advantages of both ASKAT and famSKAT and added new options to empower FFBSKAT users. The FFBSKAT package is fast, user-friendly, and provides an easy-to-use method to perform whole-exome kernel machine-based regression association analysis of quantitative traits in samples of related individuals. The FFBSKAT package, along with its manual, is available for free download at http://mga.bionet.nsc.ru/soft/FFBSKAT/.
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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.