3 files changed, 65 insertions, 3 deletions
diff --git a/doc/GEMMAmanual.bib b/doc/GEMMAmanual.bib
new file mode 100644
index 0000000..a6826dc
--- /dev/null
+++ b/doc/GEMMAmanual.bib
@@ -0,0 +1,62 @@
+@Article{Zhou:2012,
+	author = "Xiang Zhou and Matthew Stephens",
+	title = "Genome-wide efficient mixed-model analysis for association studies",
+	journal = "Nature Genetics",
+	year = 2012,
+	volume = 44,
+	pages = "821-824"
+}
+
+@Article{Zhou:2013,
+	author = "Xiang Zhou and Peter Carbonetto and Matthew Stephens",
+	title = "Polygenic modelling with {B}ayesian sparse linear mixed models",
+	journal = "PLoS Genetics",
+	year = 2013,
+	volume = 9,
+	pages = "e1003264"
+}
+
+@Article{Zhou:2014,
+	author = "Xiang Zhou and Matthew Stephens",
+	title = "Efficient multivariate linear mixed model algorithms for genome-wide association studies",
+	journal = "Nature Methods",
+	year = 2014,
+	volume = 11,
+	pages = "407-409"
+}
+
+@Article{Guan:2008,
+	author = "Yongtao Guan and Matthew Stephens",
+	title = "Practical issues in imputation-based association mapping",
+	journal = "PLoS Genetics",
+	year = 2008,
+	volume = 4,
+	pages = "e1000279"
+}
+
+@Article{Purcell:2007,
+	author = "Shaun Purcell and Benjamin Neale and Kathe Todd-Brown and Lori Thomas and Manuel A. R. Ferreira and David Bender and Julian Maller and Pamela Sklar and de Bakker, Paul I. W.  and Mark J. Daly and Pak C. Sham",
+	title = "{PLINK}: a toolset for whole-genome association and population-based linkage analysis",
+	journal = "The American Journal of Human Genetics",
+	year = 2007,
+	volume = 81,
+	pages = "559-575"
+}
+
+@Article{Howie:2009,
+	author = "Bryan N. Howie and Peter Donnelly and Jonathan Marchini",
+	title = "A flexible and accurate genotype imputation method for the next generation of genome-wide association studies",
+	journal = "PLoS Genetics",
+	year = 2009,
+	volume = 5,
+	pages = "e1000529"
+}
+
+@Article{Valdar:2006,
+	author = "William Valdar and Leah C. Solberg and Dominique Gauguier and Stephanie Burnett and Paul Klenerman and William O. Cookson and Martin S. Taylor and J Nicholas P. Rawlins and Richard Mott and Jonathan Flint",
+	title = "Genome-wide genetic association of complex traits in heterogeneous stock mice",
+	journal = "Nature Genetics",
+	year = 2006,
+	volume = 38,
+	pages = "879-887"
+}
+\ No newline at end of file
diff --git a/doc/GEMMAmanual.pdf b/doc/GEMMAmanual.pdf
index 8998f0d..8773c45 100644
--- a/doc/GEMMAmanual.pdf
+++ b/doc/GEMMAmanual.pdf
diff --git a/doc/GEMMAmanual.tex b/doc/GEMMAmanual.tex
index 49c96dc..e5730e0 100644
--- a/doc/GEMMAmanual.tex
+++ b/doc/GEMMAmanual.tex
@@ -79,7 +79,7 @@
 \section{Introduction}
 
 \subsection{What is GEMMA}
-GEMMA is the software implementing the Genome-wide Efficient Mixed Model Association algorithm \cite{Zhou:2012} for a standard linear mixed model and some of its close relatives for genome-wide association studies (GWAS). It fits a univariate linear mixed model (LMM) for marker association tests with a single phenotype to account for population stratification and sample structure, and for estimating the proportion of variance in phenotypes explained (PVE) by typed genotypes (i.e. "chip heritability") \cite{Zhou:2012}.  It fits a multivariate linear mixed model (mvLMM) for testing marker associations with multiple phenotypes simultaneously while controlling for population stratification, and for estimating genetic correlations among complex phenotypes \cite{Zhou:2013b}. It fits a Bayesian sparse linear mixed model (BSLMM) using Markov chain Monte Carlo (MCMC) for estimating PVE by typed genotypes, predicting phenotypes, and identifying associated markers by jointly modeling all markers while controlling for population structure \cite{Zhou:2013}. It is computationally efficient for large scale GWAS and uses freely available open-source numerical libraries.
+GEMMA is the software implementing the Genome-wide Efficient Mixed Model Association algorithm \cite{Zhou:2012} for a standard linear mixed model and some of its close relatives for genome-wide association studies (GWAS). It fits a univariate linear mixed model (LMM) for marker association tests with a single phenotype to account for population stratification and sample structure, and for estimating the proportion of variance in phenotypes explained (PVE) by typed genotypes (i.e. "chip heritability") \cite{Zhou:2012}.  It fits a multivariate linear mixed model (mvLMM) for testing marker associations with multiple phenotypes simultaneously while controlling for population stratification, and for estimating genetic correlations among complex phenotypes \cite{Zhou:2014}. It fits a Bayesian sparse linear mixed model (BSLMM) using Markov chain Monte Carlo (MCMC) for estimating PVE by typed genotypes, predicting phenotypes, and identifying associated markers by jointly modeling all markers while controlling for population structure \cite{Zhou:2013}. It is computationally efficient for large scale GWAS and uses freely available open-source numerical libraries.
 
 
 \subsection{How to Cite GEMMA}
@@ -87,7 +87,7 @@ GEMMA is the software implementing the Genome-wide Efficient Mixed Model Associa
 \item Software tool and univariate linear mixed models \\
 Xiang Zhou and Matthew Stephens (2012). Genome-wide efficient mixed-model analysis for association studies. Nature Genetics. 44: 821-824.
 \item Multivariate linear mixed models \\
-Xiang Zhou and Matthew Stephens (2014). Efficient algorithms for multivariate linear mixed models in genome-wide association studies. Nature Methods. in press.
+Xiang Zhou and Matthew Stephens (2014). Efficient multivariate linear mixed model algorithms for genome-wide association studies. Nature Methods. 11: 407-409.
 \item Bayesian sparse linear mixed models \\
 Xiang Zhou, Peter Carbonetto and Matthew Stephens (2013). Polygenic modeling with Bayesian sparse linear mixed models. PLoS Genetics. 9(2): e1003264.
 \end{itemize}
@@ -622,6 +622,6 @@ A: One should always use the same phenotype and genotype files for both fitting
 	
 \clearpage
 \bibliographystyle{plain}
-\bibliography{/net/wallace/ga/xz7/Documents/Papers/BIB/lmm,/net/wallace/ga/xz7/Documents/Papers/BIB/bslmm,/net/wallace/ga/xz7/Documents/Papers/BIB/mvlmm}
+\bibliography{GEMMAmanual}
 
 \end{document}