kbroman

# k-by-k version of a mcnemar test

mcnemar <-
    function(tab, n_perm=1000)
{
    if(diff(dim(tab)) != 0 || any(tab < 0) || any(round(tab) != tab)) {
        stop("tab should be a square matrix with non-negative integers")
    }

    calc_stat <- function(tab) {

kbroman

# install_github("ryantimpe/brickr")
# install_github("tylermorganwall/rayshader")
library(brickr) # also need rayshader

url <- paste0("https://gist.githubusercontent.com/kbroman/",
              "bfba63a490fb40ea907a79e1ddd2354f/",
              "raw/8c3a3d82423956867bc31f0f0980f7c887badff1/",
              "karl_lego.csv")
file <- basename(url)
if(!file.exists(file)) download.file(url, file)

kbroman

# nrow 6097
# ncol 9
line,A,B,C,D,E,F,G,H
375,8,6,7,5,2,1,4,3
376,8,6,7,5,2,1,4,3
377,2,1,4,3,7,6,8,5
378,2,1,4,3,7,6,8,5
379,2,1,4,3,7,6,8,5
380,2,1,4,3,7,6,8,5
381,2,1,4,3,7,6,8,5

kbroman

# simulate DO data, to look at kinship coefficient for siblings vs others


library(simcross) # install with devtools::install_github("kbroman/simcross")
library(qtl2)


# example DO data with megaMUGA genotypes, used for map + founder genotypes
file <- paste0("https://raw.githubusercontent.com/rqtl/",
               "qtl2data/master/DO_Svenson291/svenson.zip")

kbroman

# problem with fit1() with model="binary", in giving negative or NAs for LOD scores

library(qtl2)

dat <- readRDS("fit1_binary_problem.rds")
fit1(dat$p, dat$y, model="binary")$lod # NA value

stopifnot( all(names(dat$y) == rownames(dat$p)) )

out_glm <- glm(dat$y ~ -1 + dat$p, family=binomial(link=logit),

kbroman

LIB = "packages/"
#LIB = NULL

# These were not on CRAN, so it did not install to "packages/"
# library ("curl")
# library ("devtools")
# devtools::install_github ('ropenscilabs/miner')
# devtools::install_github ('ropenscilabs/craft')
library (miner)
library (craft)

kbroman

#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::export]]
NumericVector sim_crossovers_orig(const double L)
{
    int n_xo;

    n_xo = R::rpois(L/100.0);

kbroman

# Study genotype frequencies / haplotype reconstructions in Diversity Outbred mice
# Example with the DOex data (https://github.com/rqtl/qtl2data/tree/master/DOex)
# See R/qtl2 discussion: https://groups.google.com/d/msg/rqtl2-disc/cBJ0zSbvid8/pplbQ_zyAwAJ

library(qtl2)
file <- paste0("https://raw.githubusercontent.com/rqtl/",
              "qtl2data/master/DOex/DOex.zip")
DOex <- read_cross2(file)

# genoprobs

kbroman

QTL papers

• Albert and Kruglyak (2015) The role of regulatory variation in complex traits and disease. Nature Reviews Genetics 16:197-212. doi:10.1038/nrg3891

• Jiang C, Zeng ZB (1995) Multiple trait analysis of genetic mapping for quantitative trait loci. Genetics 140:1111-1127 PMC:1206666

• Gatti DM et al (2014) Quantitative trait locus mapping methods for diversity outbred mice.

kbroman

# elsa-fy for minecraft
# using the miner R package, https://github.com/ROpenSciLabs/iner
#
# when she walks on water, it turns to ice
elsafy <- function(player_id=NULL, water=c(8, 9), ice=174, delay=0.02)
{
    on.exit( { # clean up a bit
        for(i in 1:20) miner:::mc_receive()
        } )