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Updated the README.
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eriqande committed Sep 18, 2019
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38 changes: 38 additions & 0 deletions README.Rmd
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---
title: "CKMRsim"
output: github_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

This package implements Monte Carlo methods
(including efficient importance sampling approaches) for assessing the false positive and false
negative rates expected when using a particular set of genetic markers for pairwise relationship inference. It also
provides functions implemented in C++ for computing likelihood ratios for different
relationships between all pairs of individuals in a data set.

CKMRsim can be installed with devtools. It requires that development tools be installed on your
system to allow compilation of C++ via RCpp.
```{r, eval=FALSE}
devtools::install_github("eriqande/CKMRsim", build_vignettes = TRUE)
```

After this, the various vignettes can be accessed and read like this:
```{r, eval=FALSE}
vignette("CKMRsim-example-1")
vignette("CKMRsim-example-2-microsatellites")
vignette("CKMRsim-simulating-linked-markers")
vignette("CKMRsim-writing-geno-error-funcs")
```

In order to pursue simulations in the face of physical linkage, you must download
and install the external dependency, Mendel version 16. For Windows and Mac OS X,
CKMRsim will look for the Mendel binary in its default install location. So download
it from [http://software.genetics.ucla.edu/mendel](http://software.genetics.ucla.edu/mendel) and do a default install.
Note that you need to register with your email in order to download Mendel.

45 changes: 30 additions & 15 deletions README.md
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# CKMRsim
CKMRsim
================

[![DOI](https://zenodo.org/badge/55812404.svg)](https://zenodo.org/badge/latestdoi/55812404)
This package implements Monte Carlo methods (including efficient
importance sampling approaches) for assessing the false positive and
false negative rates expected when using a particular set of genetic
markers for pairwise relationship inference. It also provides functions
implemented in C++ for computing likelihood ratios for different
relationships between all pairs of individuals in a data set.

CKMRsim can be installed with devtools. It requires that development
tools be installed on your system to allow compilation of C++ via RCpp.

This is an R package in development. Not much else here now.
``` r
devtools::install_github("eriqande/CKMRsim", build_vignettes = TRUE)
```

NOTES:
After this, the various vignettes can be accessed and read like this:

When you define a pedigree for gene dropping, individuals 1 and 2 are the focal
individauls of the pair and they must have observed parents (because MENDEL output
is hard to parse otherwise...). Hence PO must look like:
```
Kid Pa Ma Sex Observed
1 1 2 3 1 1
2 2 4 5 1 1
3 3 0 0 2 0
4 4 0 0 1 0
5 5 0 0 2 0
``` r
vignette("CKMRsim-example-1")

vignette("CKMRsim-example-2-microsatellites")

vignette("CKMRsim-simulating-linked-markers")

vignette("CKMRsim-writing-geno-error-funcs")
```
instead of having just three lines.

In order to pursue simulations in the face of physical linkage, you must
download and install the external dependency, Mendel version 16. For
Windows and Mac OS X, CKMRsim will look for the Mendel binary in its
default install location. So download it from
<http://software.genetics.ucla.edu/mendel> and do a default install.
Note that you need to register with your email in order to download
Mendel.
7 changes: 5 additions & 2 deletions vignettes/CKMRsim-simulating-linked-markers.Rmd
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## Prerequisites

INCLUDE STUFF HERE ABOUT HOW TO DOWNLOAD MENDEL AND WHERE IT SHOULD BE INSTALLED TO.
NOTE THAT I NEED TO FIGURE THAT OUT ON WINDOZE.
In order to pursue simulations in the face of physical linkage, you must download
and install the external dependency, Mendel version 16. For Windows and Mac OS X,
CKMRsim will look for the Mendel binary in its default install location. So download
it from [http://software.genetics.ucla.edu/mendel](http://software.genetics.ucla.edu/mendel) and do a default install.
Note that you need to register with your email in order to download Mendel.

## An Example

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