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load("aries_funnorm.randomeffect.pc10.160915.Robj")
load("samplesheet_aries.160915.Robj")

# Make sure that all the sample_names in samplesheet match the colnames in norm.beta.random

all(samplesheet$Sample_Name == colnames(norm.beta.random))

# This is not the case so we need to match things up
# Get the intersect
ids <- intersect(samplesheet$Sample_Name, colnames(norm.beta.random))

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rowCors = function(x, y)
{ 
	sqr = function(x) x*x
	if(!is.matrix(x)||!is.matrix(y)||any(dim(x)!=dim(y)))
	  stop("Please supply two matrices of equal size.")
	x   = sweep(x, 1, rowMeans(x))
	y   = sweep(y, 1, rowMeans(y))
	cor = rowSums(x*y) /  sqrt(rowSums(sqr(x))*rowSums(sqr(y)))
	return(cor)
}

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#!/bin/bash

while [[ $# > 1 ]]
do
key="$1"

case $key in
	-g|--rootname)
	genort="${2}"
	shift

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impute <- function(X)
{
	apply(X, 2, function(x) {
		x[is.na(x)] <- mean(x, na.rn=T)
		return(x)
	})
}


# Original matrix

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# In R:

load("/panfs/panasas01/shared/alspac/deprecated/gib/aries_renormalised/condanal_results.RData")
mprobes <- c("cg06500161", "cg11024682", "cg07094298", "cg04011474", "cg10192877", "cg17782974", "cg20496314", "cg07202479", "cg09494176", "cg17501210", "cg21139312", "cg26403843") 

b <- subset(condres, CPG %in% mprobes)

write.table(unique(b$SNP), file="~/snplist.txt", row=F, col=F, qu=F)

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---
title: Notes on survival analysis
author: Gibran Hemani
date: "`r Sys.Date()`"
output: pdf_document
bibliography: survival.bib
---

These notes are based on [http://data.princeton.edu/wws509/notes](http://data.princeton.edu/wws509/notes).

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simulate_two_correlated_snps <- function(n, p1, p2, r)
{
	D <- r * sqrt((1-p1) * (1-p2) * p1 * p2)
	p11 <- p1 * p2 + D
	p12 <- p1 * (1 - p2) - D
	p21 <- (1 - p1) * p2 - D
	p22 <- (1-p1) * (1-p2) + D

	if(any(c(p11, p12, p21, p22) < 0))
	{

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palette(c("#E41A1C", "#377EB8", "#4DAF4A", "#984EA3",
  "#FF7F00", "#FFFF33", "#A65628", "#F781BF", "#999999"))

shinyServer(function(input, output, session) {

  # Combine the selected variables into a new data frame
  selectedData <- reactive({
    iris[, c(input$xcol, input$ycol)]
  })

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get_beta_se_from_p_z_n_vary <- function(z, n, vy, maf)
{
	qval <- qchisq(pnorm(abs(z), low=FALSE)*2, 1, low=F) / (qchisq(pnorm(abs(z), low=FALSE)*2, n-2, low=F)/(n-2))
	r <- sqrt(sum(qval / (n - qval)))
	b <- sign(z) * sqrt(r^2 * vy / (2*maf*(1-maf)))
	se <- b / z
	return(list(b=b, se=se))
}

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library(shiny)
library(shinydashboard)
library(googleAuthR)

options("googleAuthR.scopes.selected" = c("https://www.googleapis.com/auth/userinfo.profile", "https://www.googleapis.com/auth/userinfo.email"))
options("googleAuthR.webapp.client_id" = "906514199468-1jpkqgngur8emoqfg9j460s47fdo2euo.apps.googleusercontent.com")
options("googleAuthR.webapp.client_secret" = "I7Gqp83Ku4KJxL9zHWYxG_gD")

user_info <- function(){
	f <- gar_api_generator("https://www.googleapis.com/oauth2/v1/userinfo",