GAPIT pipeline

GAPIT specifications

Information


Unique identifier OMICS_08869
Name GAPIT
Alternative names Genome Association and Prediction Integrated Tool, SUPER (Settlement of MLM Under Progressively Exclusive Relationship)
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Zhiwu Zhang <>

Publications for Genome Association and Prediction Integrated Tool

GAPIT IN pipelines

 (3)
2017
PMCID: 5470659
PMID: 28614352
DOI: 10.1371/journal.pone.0176932

[…] testing., the principle component analysis and ld testing in fig 1 were calculated using plink [28] (fig 2 and s2 fig) were generated by the genome association and prediction integrated tool (gapit) [29]. a resampling test was used to identify false positive signals through selection of 80% of the individuals without replacement to conduct the gwas and the process was repeated 1,000 times […]

2017
PMCID: 5470659
PMID: 28614352
DOI: 10.1371/journal.pone.0176932

[…] within a fixed range around each qtn were treated as loci in the same ld interval (true positives), and the window size of this range was set as 100,000 bp. simulated phenotypes were generated using gapit [29]. the mixed linear model was performed in gemma [23] and compared to analysis of the same simulated phenotype data using farmcpu., the norberg angle (101.8±sd = 9.8°) was averaged […]

2016
PMCID: 4982113
PMID: 27515508
DOI: 10.1186/s12864-016-2918-5

[…] r software [111] with a compressed mixed linear model and population parameters previously determined [112]. the optimal number of principle components for inclusion in the model was determined with gapit by bayesian information criterion. the significance threshold for marker-trait associations was determined by a modified bonferroni adjustment in which meff was calculated using simplem [113] […]

GAPIT institution(s)
College of Electrical and Information, Northeast Agricultural University, Harbin, China; Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China; Institute for Genomic Diversity, Cornell University, Ithaca, NY, USA; Department of Animal Science and Technology, North East Agricultural University, Harbin, China; Institute of Animal Husbandry, Heilongjiang Academy of Agricultural Science, Harbin, China; College of Horticulture, Nanjing Agricultural University, Nanjing, China; School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai, China; National Maize Improvement Center of China, China Agricultural University, Beijing, China; Department of Crop Sciences, University of Illinois, Urbana, IL, USA; USDA- ARS, Ithaca, NY, USA; Department of Crop and Soil Sciences, Washington State University, Pullman, WA, USA
GAPIT funding source(s)
Supported by NSF (0922493 and 1238014), USDA-ARS, an Emerging Research Issues Internal Competitive Grant from the Agricultural Research Center at Washington State University, College of Agricultural, Human, and Natural Resource Sciences, the Endowment and Research Project (No. 126593) from the Washington Grain Commission, the National Natural Science Foundation of China (Grant no. 31301748), and the China Postdoctoral Science Foundation (Grant no. 2014M551607).

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