===================== INSTRUCTIONS ==============================

This document contains instructions for installing and using MCPDT
package for R.


1. Install

For Linux and Mac users, download the source code R package file:
MCPDT_(version number).src.tar.gz
For Windows users, download the compiled R package file for Windows:
MCPDT.zip
Then use the following function in R to install the package
>install.packages(pkgs=filename,repos=NULL)
where "filename" should be replaced with the actual file name.


2. Use

Use
>library(MCPDT)
to load the package into R.

Use
>?MCPDT
to read the instruction.


3. Example (newest version that also outputs FDR as of July 27, 2012)

Download the sample pedigree file:
testped.R
Then use
>source("testped.R")
>MCPDT(testped,100)
$pvalue
                PDT    PDT.FDR      MCPDT   MCPDT.FDR
Marker 1 0.03038282 0.06076564 0.00321145 0.006422899
Marker 2 0.20590321 0.20590321 0.50851382 0.508513819

$Tstat
              PDT    MCPDT     
Marker 1 2.165064 2.9770586 
Marker 2 1.264911 0.5342586 

$mcsize
[1] 100

$af
   Marker 1 Marker 2
1     0.28   0.2825
2     0.72   0.7175

>MCPPAT(testped,100)
$Ipvalue
              PPAT   PPAT.FDR      MCPPAT  MCPPAT.FDR
Marker 1 0.0268567 0.05371339 0.001660145 0.003320289
Marker 2 0.5485062 0.54850624 0.868756281 0.868756281

$Apvalue
                PDT    PDT.FDR       MCPDT   MCPDT.FDR
Marker 1 0.03038282 0.06076564 0.003334572 0.006669145
Marker 2 0.20590321 0.20590321 0.549066374 0.549066374

$Tstat
              PDT     MCPDT     PPAT    MCPPAT
Marker 1 2.165064 2.9770586 2.213594 3.2098017
Marker 2 1.264911 0.5342586 0.600000 0.1153962

$mcsize
[1] 100

$af
   Marker 1 Marker 2
1     0.28   0.2825
2     0.72   0.7175

Note 1. Output for MCPPAT: Ipvalue in the output gives the p-values that are 
associated with testing for imprinting, whereas Apvalue gives the output 
associated with testing for association, which should give the same results 
as with running MCPDT except random variation (due to random seed, see the following)
 
Note 2. The actual numbers that you get for MCPDT and MCPPAT may be a 
little different from the results shown above due to the random nature of the 
Monte Carlo method. You may set the random seed using set.seed before running 
the functions so that you can recover the same results.
 

4. Reference

MCPDT:
Ding, J., Lin, S. and Liu, Y. (2006) Monte Carlo pedigree
disequilibrium test for markers on the X chromosome. Am J Hum
Genet 79:567-573  

MCPPAT:
Zhou, J.Y., Ding, J., Fung, W.K. And Lin, S. (2010) Detection of 
parent-of-origin effects using general pedigree data. 
Genetic Epidemiology 34:151-158.

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If you have any questions, please email Jie Ding at:
ding(at)stat.osu.edu, Ji-Yuan Zhou at zhoujy(at)hkusua.hku.hk
or Shili Lin at shili@stat.osu.edu