Week 4 Practical

To load packages from Bioconductor and access the vignettes
How to load data from preprocessed data objects within bioconductor
Analysis of gene expression data with different methods and normalisation techniques
Basic use of limma for Differential Expression Anaysis

In [18]:

options(jupyter.plot_mimetypes ='image/png')

Exercise 1

In [24]:

library(affy)

Exercise 2

In [20]:

getwd()

This is marked based on the work in the time travel, as the workbook was mostly empty when opened.

Exercise 1

Overall clarity (0.25 score)
Correctness of the code ( 0.25 score)
Exhaustive cover of required analysis (0 score)
Interpretation of the results (0.25 score)
Total score = 0.75 Exercise not fully completed, does not explain what are the objects that they require and what is the output.

Exercise 2

Overall clarity (0.25 score)
Correctness of the code ( 0.25 score)
Exhaustive cover of required analysis (0.25 score)
Interpretation of the results (0.25 score)
Total score = 1

Exercise 3

Exercise 4

Overall clarity (0.25 score)
Correctness of the code ( 0.25 score)
Exhaustive cover of required analysis (0.25 score)
Interpretation of the results (0.25 score)
Total score = 1

Exercise 5

Exercise 6

Overall clarity (0.25 score)
Correctness of the code ( 0.25 score)
Exhaustive cover of required analysis (0.25 score)
Interpretation of the results (0.25 score)
Total score = 1

Exercise 7

Overall clarity (0.25 score)
Correctness of the code ( 0.25 score)
Exhaustive cover of required analysis (0.25 score)
Interpretation of the results (0.25 score)
Total score = 1

Exercise 8

Final score 6.75/11

In [ ]: