Created rawData vignette

I am trying R markdown to markdown with knitr and then markdown to html5 with pandoc.  Also note that this vignette requires package CleftCNVAssoc which is not available anywhere but enigma.
Translated inherited deletions vignette from Sweave format to R markdown format

Also updated rawData with asciidoc or pandoc... not sure.
Updated rawData vignette.
Updated rawData vignette.
Updated vignettes and included a build script for the web-site
Simple update of raw data vignettes
Updated and created more raw data vignettes
Transposed inherited deletions vignette to asciidoc with embedded figures

courtesy of karl broman
Updated inherited-deletions vignette.

Now we count as transmitted all deletions that have a transmitted component anywhere in the region.  It takes an hour to count for all approximately two thousand regions.  Tomorrow I will use binom.test to compute the CIs for the transmission rate.

Note that a trio with trio-state 111 is ambiguousm as it is both a transmission and a non-transmission.  Currently it is counted towards transmitted and not towards untransmitted.
Clean up

Here I cleaned out extraneous files and added to the .gitignore file --- all in an effort to keep things minimal.

Bumped the version --- mostly just to update the date in the DESCRIPTION file ;)
More clean up.

Here I removed files associated with the inherited deletions vignette that were needed for my earlier report generation method, i.e., R markdown and pandoc.

Also updated .gitignore to contain make.out, the hilariously named log file generated with make and Makefile.
Included asciidoc.R in repo.

asciidoc.R is a script that executes the Asciidoc() command.  The filename must be updated --- currently it is used for inherited-deletions.
Updated Inherited Deletions Vignette.

On the web page there is now a link to the New Counting method within the CLP Association vignette.  Here we implement the change in counting and plot a histogram of overall tranmission rates per region, as well as the CIs per region , stratified by cleft, control, and all.

We still see regions of undertransmission.  If our hypothesis is that these are regions with excessive false positve rates, and that they should be eliminated from the study than we need a systematic way to categorize bad regions.

It still may be worthwhile to investigate correlation between marker density and under-transmission.  Some physical property, whether it is biology, or the chip design, is likely to be causing the under-transmission/false positives.