#Okay, let's try to do the bandwidth optimization on the Ulirsch data
library(dplyr)
library(magrittr)
library(parallel)
library(ggplot2)
load('~/MPRA/data/varInfo.RData')
#Oh God why haven't I saved this when I did it before
# load('~/MPRA/data/gatheredMPRA.RData')
#
# poolsig <-function(dat){
# sds = summarise(group_by(dat, type), sd = sd(qnact))
#
# smut = sds$sd[sds$type == 'Mut']
# sref = sds$sd[sds$type == 'Ref']
# nref = sum(dat$type == 'Ref')
# nmut = sum(dat$type == 'Mut')
#
# return(sqrt(((nref - 1)*sref**2 + (nmut - 1)*smut**2) / (nref + nmut - 2)))
# }
#
# varInfo$pooledSigma = mclapply(varInfo$construct, function(x){
# mpradat = filter(MPRA.qnactivity, construct == x)
# return(poolsig(mpradat))
# }, mc.cores = 21) %>% unlist
# Optimize bandwidths
# Run model
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