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FaST-LMM

FaST-LMM

FaST-LMM (Factored Spectrally Transformed Linear Mixed Models) is a tool for large genome-wide association studies (GWAS).

Topic

GWAS study; Genotype and phenotype; Machine learning

Details

  • Operation: Prediction and recognition
  • Software interface: Command-line user interface; Library
  • Language: Python
  • Operating system: Linux; Mac OS X; Microsoft Windows
  • License: Apache License 2.0
  • Cost: Free
  • Version name: -
  • Maturity: Mature
  • Credit: The Wellcome Trust Case Control Consortium, Wellcome Trust, US National Science Foundation, US National Institutes of Health.
  • Contact: fastlmm-dev _at_ python.org | jennl _at_ microsoft.com | christoph.lippert _at_ tuebingen.mpg.de | heckerma _at_ microsoft.com
  • Collection: EBI Training Tools

Publications

Listgarten J, Lippert C, Kadie CM, Davidson RI, Eskin E, Heckerman D "Improved linear mixed models for genome-wide association studies." Nat. Methods 2012; 9(6):525-6 https://doi.org/10.1038/nmeth.2037
PMID: 22669648
PMCID: PMC3597090


Lippert C, Listgarten J, Liu Y, Kadie CM, Davidson RI, Heckerman D "FaST linear mixed models for genome-wide association studies" Nat Methods. 2011 Sep 4;8(10):833-5. https://doi.org/10.1038/nmeth.1681
PMID: 21892150


Zou J, Lippert C, Heckerman D, Aryee M, Listgarten J "Epigenome-wide association studies without the need for cell-type composition" Nat Methods. 2014 Mar;11(3):309-11 https://doi.org/10.1038/nmeth.2815
PMID: 24464286


Widmer C, Lippert C, Weissbrod O, Fusi N, Kadie C, Davidson R, Listgarten J, Heckerman D "Further Improvements to Linear Mixed Models for Genome-Wide Association Studies " Sci Rep. 2014 Nov 12;4:6874. https://doi.org/10.1038/srep06874
PMID: 25387525
PMCID: PMC4230738


Heckerman D, Gurdasani D, Kadie C, Pomilla C, Carstensen T, Martin H, Ekoru K, Nsubuga RN, Ssenyomo G, Kamali A, Kaleebu P, Widmer C, Sandhu MS "Linear Mixed Model for Heritability Estimation That Explicitly Addresses Environmental Variation" Proc Natl Acad Sci U S A. 2016 Jul 5;113(27):7377-82 https://doi.org/10.1073/pnas.1510497113
PMID: 27382152
PMCID: PMC4941438


Lippert C, Xiang J, Horta D, Widmer C, Kadie C, Heckerman D, Listgarten J "Greater Power and Computational Efficiency for Kernel-Based Association Testing of Sets of Genetic Variants" Bioinformatics. 2014 Nov 15;30(22):3206-14 https://doi.org/10.1093/bioinformatics/btu504
PMID: 25075117
PMCID: PMC4221116


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