In mahendra-mariadassou/L1fdvGenetics: Companion self-learning R package to the Genetics Project of FDV bachelor

## DO NOT EDIT THIS CHUNCK
knitr::opts_chunk$set(echo = TRUE, fig.width = 7, fig.height = 5, cache = FALSE)
library(L1fdvGenetics) ## Homework data and helper functions()
data("hw_data")        ## Homework data: geno/phenotypes of the F2 mice
data("genetic_map")    ## Homework data: genetic map

Goal

You're doing an internship in an immunology lab working with mice. The lab developed a QTL panel (a dense genetic map) for LEWIS and BN lines and the PI (Principal Investigator) asked the previous intern to do a QTL analysis for IgG1 production. Unfortunately, the intern was super sloppy and his digital lab book is very messy with bits of code and comments. The PI tasked you to revisit and document the analysis, to produce a nicer report.

Data

Genetic data

Instructions: Give a brief description of the genetic data, with relevant information.

dim(hw_data)
colnames(hw_data)[-1]
summary(range(hw_data[ , "IgG1"]))

Genetic map

Instructions: Give a brief description of the genetic data, with relevant information.

genetic_map
## Nb markers
with(genetic_map, tapply(Location, Chromosome, length))
## dist between markers
with(genetic_map, tapply(Location, Chromosome, function(x) { mean(diff(x)) })) 
## Min/Max distance
with(genetic_map, tapply(Location, Chromosome, function(x) { range(diff(x)) }))
## Min/Max positions
with(genetic_map, tapply(Location, Chromosome, range)) 

Analysis on chromosome 1

Instructions: Document the analyses performed. Select, format and comment the relevant results.

chr1_map <- subset(genetic_map, Chromosome == "Chr1")
chr1_markers <- chr1_map[ , "Marker"]
chr1_data <- hw_data[ , c("Organism", chr1_markers, "IgG1")]
for (marker in chr1_markers) {
  LOD(marker = marker, data = chr1_data) 
}

## LOD scores
positions  <- seq(from = 0, to = 100, by = 1)
lod_scores <- rep(0, length(positions)) 
for (i in 1:length(positions)) {
  lod_scores[i] <- LOD_position(position = positions[i], data = chr1_data, map = chr1_map)
}
lod_data <- data.frame(Position = positions, 
                       LOD      = lod_scores)
## Plot
plot(LOD ~ Position, data = lod_data, 
     type = "o",
     xlab = "Position along chromosome 1 (in cM)", 
     ylab = "LOD score"
     )
abline(v = chr1_map$Location, lty = 3, col = "grey80")

## Positions
subset(lod_data, LOD >= 2)

Analysis on chromosome 2 (DIY)

This part is completely optional and will not count toward the final grade.

Instructions: Repeat and adapt the previous analysis to detect and position putative QTL located in Chromosome 2.

## Write code here

Conclusion

Instructions: Write a small conclusion summarizing your findings. Add any information you find relevant.

Perspective

Instructions: How would you adapt the experimental and/or analytic strategy to account for an additive model?

mahendra-mariadassou/L1fdvGenetics documentation built on May 20, 2021, 10:42 p.m.