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From listmasteranimalgenome.org  Wed May 29 10:01:25 2019
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From: Hong Lee <Hong.Leeunisa.edu.au> 
Postmaster: submission approved by list moderator
To: Members of AnGenMap <angenmapanimalgenome.org>
Subject: MTG2: Multivariate reaction norm model 
Date: Wed, 29 May 2019 10:01:25 -0500

Dear all,

If you are interested in estimating genotype-environment (G-E) interaction,
you may also want to consider G-E correlation that may cause spurious G-E
interaction signals. We have recently developed multivariate reaction norm
model (MRNM) and implemented in MTG2 (section 1.4), which can tackle G-E
correlation and interaction problems. It is well known that unmodelled G-E
correlation can mislead G-E interaction analyses, however, there are few
statistical tools to correct this bias. MRNM can unbiasedly estimate G-E
interaction in the presence of G-E correlation and even it has a higher
power to detect the interaction, compared to existing methods. It is also
notable that MRNM is efficient to detect significant heterogeneity in the
estimated residual variances across different environmental or covariate
levels. For more detail, please see the following paper.

Ni et al. (2019) Genotype-covariate correlation and interaction
disentangled by a whole-genome multivariate reaction norm model. Nature
Communications 10: 2239 (https://www.nature.com/...19-10128-w).

The manual and software (v 2.15) can be downloaded from

https://sites.google.com/...ite/honglee0707/mtg2

In addition, MTG2 now has a function for linear mixed model GWAS (section 14),
which can be used with -wtr (weighted residual structure). Please see the
manual, e.g.

14.1. Standard LMM GWAS ............................................. 68
14.2. Standard LMM GWAS with -eig.................................... 69
14.3. Approximated LMM GWAS.......................................... 69

Any question or feedback would be appreciated (hong.leeunisa.edu.au)

Best wishes
Hong


 
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