breeding_values

I am using random forest with breeding values for caterpillar and plant traits.

Some major questions:

• • Can I use Random forest to predict cat breeding value from plant genotype breeding value?

  • If I cbind the IR and plant traits together and run random forest does prediction strength of caterpillar traits increases with IR data?

  • Can we predict plant traits from IR traits?

Relevant output is ranking of top predictors and OOB values

Trait breeding values were calculated and are located at:

/uufs/chpc.utah.edu/common/home/u6000989/projects/mtrunc_mel/gemma/output/prediction

These were transferred into my mtrun file with

scp -r /uufs/chpc.utah.edu/common/home/u6000989/projects/mtrunc_mel/gemma/output/prediction/bv_pred_cat.txt /uufs/chpc.utah.edu/common/home/u6015714/mtrun/data

And onto my computer with

scp -r u6015714@kingspeak.chpc.utah.edu:/uufs/chpc.utah.edu/common/home/u6015714/mtrun/data/pntest_mtrunc_pruned.txt ~/Documents/mtrun

The relevant files are bv_pred_cat.txt, bv_pred_plant.txt and bv_pred_ir.txt.

Each of these files contains 94 rows, which are the individual plants which are in the same order as the genome. The traits are also in the same order as the other files.

Bv_cat has 4 columns (cat traits)

Bv_plant has 9 columns of plant traits

Bv IR has 19 columns of unknown IR spec freq, will refer to these as IR 1-19 for now.

Code for getting it all set up:

setwd("/home/tsaley/Documents/mtrun")

#load bv matrix

bv_plant<- read.table("bv_pred_plant_headers.txt", header=T)

bv_cat<- read.table("bv_pred_cat_with_headers.txt", header=T)

bv_ir<- read.table("bv_pred_ir_headers.txt", header=T)

#check dimensions

dim(geno)

#transpose genotype matrix

geno_t<-t(geno)

#check dimesnions

dim(geno_t)

#check dimensions of trait

dim(trait)

#create matrix with trait and genotype

cat8_plant<-cbind(bv_cat$p_cat_wgt_8, bv_plant)

#check dimensions

dim(cat8_plant)

#load Random forest

install.packages("randomForest")

library(randomForest)

#run random forest

cat8_plant<-randomForest(cat8_plant[,1] ~ ., data=cat8_plant, importance=TRUE, proximity=TRUE)