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MTG specifications

Information


Unique identifier OMICS_22756
Name MTG
Alternative names Multi-Trait Genomic residual maximum likelihood and Genomic best linear unbiased prediction, MTG2, MTGBLUP
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Computer skills Advanced
Version 2.08
Stability Stable
Maintained Yes

Versioning


No version available

Maintainer


  • person_outline Sang Lee

Publications for Multi-Trait Genomic residual maximum likelihood and Genomic best linear unbiased prediction

MTG citations

 (7)
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Improving genetic prediction by leveraging genetic correlations among human diseases and traits

2018
Nat Commun
PMCID: 5841449
PMID: 29515099
DOI: 10.1038/s41467-017-02769-6
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[…] Code reported in this manuscript is available from https://github.com/uqrmaie1/smtpred.For GCTA, see http://cnsgenomics.com/software/gcta/For LDSC, see https://github.com/bulik/ldscFor MTG2, see https://sites.google.com/site/honglee0707/mtg2For LDpred, see https://github.com/bvilhjal/ldpred/For UK Biobank, see http://www.ukbiobank.ac.uk/For PLINK2, see http://www.cog-genomics.org/pl […]

library_books

Estimation of genomic prediction accuracy from reference populations with varying degrees of relationship

2017
PLoS One
PMCID: 5739427
PMID: 29267328
DOI: 10.1371/journal.pone.0189775

[…] , local or extensive population sample) is important for predicting outcomes of genomic prediction for specific designs. This study has addressed this question, and the theory has been implemented in MTG2 software (https://sites.google.com/site/honglee0707/mtg2). Therefore, a user can know the expected prediction accuracy and the power[] before designing an experiment of genomic prediction. Our ap […]

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Performance of risk prediction for inflammatory bowel disease based on genotyping platform and genomic risk score method

2017
BMC Med Genet
PMCID: 5576242
PMID: 28851283
DOI: 10.1186/s12881-017-0451-2
call_split See protocol

[…] nalyses using PLINK []. An alternative to GPRS is a best linear genomic prediction (GBLUP []) which is based on mixed linear model that regresses phenotypes on all SNPs jointly. For GBLUP we used the MTG2 software [, ]. The third method applied elastic net regularization (EN) using the glmnet package [] in R []. The EN method was recently applied by Wei et al. [] for risk prediction of CD and UC u […]

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Genotype environment interaction on human cognitive function conditioned on the status of breastfeeding and maternal smoking around birth

2017
Sci Rep
PMCID: 5519601
PMID: 28729621
DOI: 10.1038/s41598-017-06214-y
call_split See protocol

[…] The models and methods used in this study have been fully implemented in publicly available software, MTG2. The source code, executive binary file, manual and examples are readily available to use, and can be downloaded from https://sites.google.com/site/honglee0707/mtg2. […]

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Multiple Trait Covariance Association Test Identifies Gene Ontology Categories Associated with Chill Coma Recovery Time in Drosophila melanogaster

2017
Sci Rep
PMCID: 5445101
PMID: 28546557
DOI: 10.1038/s41598-017-02281-3
call_split See protocol

[…] aded from http://dmu.agrsci.dk/DMU/. The CVAT approach can also be derived from the REML procedures implemented in existing software packages commonly used in genomics such as GCTA, LDAK, DISSECT and MTG2. […]

library_books

Using information of relatives in genomic prediction to apply effective stratified medicine

2017
Sci Rep
PMCID: 5299615
PMID: 28181587
DOI: 10.1038/srep42091

[…] Theory, simulation models and GBLUP used in this study have been fully implemented in publicly available software, MTG2. The source code, executive binary file, manual and examples are readily available to use, and can be downloaded from https://sites.google.com/site/honglee0707/mtg2. […]

Citations

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MTG institution(s)
School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
MTG funding source(s)
Supported by the Australian National Health and Medical Research Council (APP1080157), the Australian Research Council (DE130100614 and DP160102126) and the Australian Sheep Industry Cooperative Research Centre.

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