Factors and Data frames exercises

These exercises cover the factors and data frames sections of Introduction to R.

Exercise 1 - Factors

• Create a ordinal factor named “Height” containing – high, low, mid, low, mid, low, mid, high, mid, high.
• Using a logical index, create new factor of only those from “Height”" greater than low.
• Replace the last index in “Height” with veryHigh and create new factor with those greater than mid.

Exercise 2 - Data frames

• Create a data frame called Annotation with a column of gene names (“Gene_1”, “Gene_2”, “Gene_3”,“Gene_4”,“Gene_5”), ensembl gene names (“Ens001”, “Ens003”, “Ens006”, “Ens007”, “Ens010”), pathway information (“Glycolysis”, “TGFb”, “Glycolysis”, “TGFb”, “Glycolysis”) and gene lengths (100, 3000, 200, 1000,1200).

• Create data frame called Sample1 with ensembl gene names (“Ens001”, “Ens003”, “Ens006”, “Ens010”) and expression (1000, 3000, 10000,5000)

• Create data frame called Sample2 with ensembl gene names (“Ens001”, “Ens003”, “Ens006”, “Ens007”,“Ens010”) and expression (1500, 1500, 17000,500,10000)

• Create a data frame containing only those gene names common to all data frames with all information from Annotation and the expression from Sample 1 and Sample 2.

• Add an extra two columns containing the length normalised expressions for Sample 1 and Sample 2

• Identify the mean length normalised expression across Sample1 and Sample2 for Ens006 genes

• For all genes, identify the log2 fold change in length normalised expression from Sample 1 to Sample 2.

• Identify the total length of genes in Glycolysis pathway.