Question

Use R programming to resolve this; can you please provide details on the code?

A) Create a dataframe – comparativeGenomeSize with the following vectors:

> organism<-c("Human","Mouse","Fruit Fly", "Roundworm","Yeast")

> genomeSizeBP<-c(3000000000,3000000000,135600000,97000000,12100000)

> estGeneCount<-c(30000,30000,13061,19099,6034)

B) Print the organism and estGeneCount for Human and fruitfly.(1)

C) Add a column to this data frame calculating base pairs per gene. To do this, write a function “genedensity” that takes as arguments the genomesizeBP and estimatedGeneCount information, and calculates from this the estimated bp per gene. (3)

Let X be normally distributed with mean 24 and variance 16 b) Calculate the following probabilities: (2)
– P(X ≤ 20)

– P(X > 29.5)

Write a while loop that prints out standard random normal numbers (use rnorm()) (1)
Using next adapt the loop from the last exercise so that it doesn’t print negative numbers. (2)

Answer 1

(A) & (B)

> organism<-c("Human","Mouse","Fruit Fly", "Roundworm","Yeast")

> genomeSizeBP<-c(3000000000,3000000000,135600000,97000000,12100000)

> estGeneCount<-c(30000,30000,13061,19099,6034)

>comparativeGenomeSize<-data.frame(organism=organism,genomeSizeBP=genomeSizeBP, estGeneCount=estGeneCount)

>comparativeGenomeSize

(C)

> #function geneDensity simply calculates bp per gene

> geneDensity<-function(bp,genes){ + bp/genes}

> #pass data frame columns to function geneDensity

> #storing results in variable bpPerGene

> bpPerGene<-geneDensity(comparativeGenomeSize$genomeSizeBP, + comparativeGenomeSize$estGeneCount)

> #result of function computation

> bpPerGene

(2)