added vignette for comparing GEMMA v 0.96 C++ code results with those of gemma2 0.0.1

Author: fboehm

.gitignore

@@ -3,3 +3,4 @@
 .RData
 .Renviron
 
+inst/doc

DESCRIPTION

@@ -10,5 +10,8 @@ LazyData: true
 URL: https://github.com/fboehm/gemma2
 BugReports: https://github.com/fboehm/gemma2/issues
 Suggests: covr,
-    testthat
+    testthat,
+    knitr,
+    rmarkdown
 RoxygenNote: 6.0.1
+VignetteBuilder: knitr

LICENSE

@@ -1,2 +1,2 @@
 YEAR: 2017
-COPYRIGHT HOLDER: Your name goes here
+COPYRIGHT HOLDER: Frederick Boehm

NEWS.md

@@ -1,3 +1,7 @@
+# gemma2 0.0.1
+
+* added vignette for comparing mvlmm gemma2 results with those of Zhou's C++ GEMMA code (v 0.96)
+
 # gemma2 0.0.0.9000
 
 * Added a `NEWS.md` file to track changes to the package.

vignettes/compare-with-GEMMAv096.Rmd

@@ -0,0 +1,77 @@
+---
+title: "Comparing gemma2 output with that of Zhou's GEMMA (v0.96)"
+author: "Frederick Boehm"
+date: "`r lubridate::now()`"
+output: rmarkdown::html_vignette
+vignette: >
+  %\VignetteIndexEntry{Vignette Title}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}
+bibliography: gemma.bib
+---
+
+```{r setup, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>"
+)
+```
+
+# Overview
+
+`gemma2` is an R implementation of an EM algorithm [@zhou2014efficient] to fit a multivariate linear mixed effects model. Specifically, it fits, via restricted maximum likelihood (REML), the model:
+
+$$vec(Y) = X vec(B) + vec(G) + vec(E)$$
+
+where $Y$ is a n by 2 phenotypes matrix, with each row being a single subject and each column a distinct phenotype. $X$ is a 2n by 2f matrix of genotypes, where $n$ is the sample size and $f$ is the number of founder lines. $X$ has a block-diagonal structure, so that it contains, on the diagonal, two $n$ by $f$ blocks of genotype data. The two off-diagonal blocks are all zeros. $B$ is a $f$ by $2$ matrix of founder allele effect sizes. 
+
+
+
+
+Vignettes are long form documentation commonly included in packages. Because they are part of the distribution of the package, they need to be as compact as possible. The `html_vignette` output type provides a custom style sheet (and tweaks some options) to ensure that the resulting html is as small as possible. The `html_vignette` format:
+
+- Never uses retina figures
+- Has a smaller default figure size
+- Uses a custom CSS stylesheet instead of the default Twitter Bootstrap style
+
+## Vignette Info
+
+Note the various macros within the `vignette` section of the metadata block above. These are required in order to instruct R how to build the vignette. Note that you should change the `title` field and the `\VignetteIndexEntry` to match the title of your vignette.
+
+## Styles
+
+The `html_vignette` template includes a basic CSS theme. To override this theme you can specify your own CSS in the document metadata as follows:
+
+    output: 
+      rmarkdown::html_vignette:
+        css: mystyles.css
+
+## Figures
+
+The figure sizes have been customised so that you can easily put two images side-by-side. 
+
+```{r, fig.show='hold'}
+plot(1:10)
+plot(10:1)
+```
+
+You can enable figure captions by `fig_caption: yes` in YAML:
+
+    output:
+      rmarkdown::html_vignette:
+        fig_caption: yes
+
+Then you can use the chunk option `fig.cap = "Your figure caption."` in **knitr**.
+
+## More Examples
+
+You can write math expressions, e.g. $Y = X\beta + \epsilon$, footnotes^[A footnote here.], and tables, e.g. using `knitr::kable()`.
+
+```{r, echo=FALSE, results='asis'}
+knitr::kable(head(mtcars, 10))
+```
+
+Also a quote using `>`:
+
+> "He who gives up [code] safety for [code] speed deserves neither."
+([via](https://twitter.com/hadleywickham/status/504368538874703872))

vignettes/gemma.bib

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+@article{zhou2014efficient,
+  title={Efficient multivariate linear mixed model algorithms for genome-wide association studies},
+  author={Zhou, Xiang and Stephens, Matthew},
+  journal={Nature methods},
+  volume={11},
+  number={4},
+  pages={407--409},
+  year={2014},
+  publisher={Nature Research}
+}