Exercise 3: Data Inspection The distributions of methylation values show that the vast majority of the genome is highly (>=80%) methylated, with only a small subset staying unmethylated. The Methylation profiles of all of the samples are extremely similar to each other, showing there are no global differences to explain or normalise and showing that the analysis can proceed using the current quantitations. The scatterplots show some noise when comparing replicates within the same sample (left), but the differences seen on an individual comparison are mostly not widespread across other replicates. When comparing the two replicate sets we can see a clearer picture, but with some large changes in a small number of points. When looking at the underlying quantitations we generally see very similar changes in all of the replicates suggesting that these differences should reflect real biology. Both PCA and tSNE show a clear and consistent difference between the replicates from the two alleles suggesting that the differences in methylation overall divide nicely into the experimental groups we expect. Exercises 4,5 and 6: Differential Expression The number of hits found using the different statistical tests should be: Chi-Square: 19496 Logistic Regression: 17485 EdgeR: 6339 All of the sets of hits look sensible when highlighted on a scatterplot of the entire data set. When collating the hits 5483 were present in the hits from all techniques. After applying the 25% absolute difference cutoff then only 60 probes should remain. Exercise 8: Reporting When the report is made, most of the top hits should match to known imprinted genes. In this version of the report I collapsed the replicate sets in the Data Track Display options so that we only see the mean values for allele1 and allele2 rather than the values for all of the individual replicates.
Exercise 3: Data Inspection The distributions of methylation values show that the vast majority of the genome is highly (>=80%) methylated, with only a small subset staying unmethylated. The Methylation profiles of all of the samples are extremely similar to each other, showing there are no global differences to explain or normalise and showing that the analysis can proceed using the current quantitations. The scatterplots show some noise when comparing replicates within the same sample (left), but the differences seen on an individual comparison are mostly not widespread across other replicates. When comparing the two replicate sets we can see a clearer picture, but with some large changes in a small number of points. When looking at the underlying quantitations we generally see very similar changes in all of the replicates suggesting that these differences should reflect real biology. Both PCA and tSNE show a clear and consistent difference between the replicates from the two alleles suggesting that the differences in methylation overall divide nicely into the experimental groups we expect. Exercises 4,5 and 6: Differential Expression The number of hits found using the different statistical tests should be: Chi-Square: 19496 Logistic Regression: 17485 EdgeR: 6339 All of the sets of hits look sensible when highlighted on a scatterplot of the entire data set. When collating the hits 5483 were present in the hits from all techniques. After applying the 25% absolute difference cutoff then only 60 probes should remain. Exercise 8: Reporting When the report is made, most of the top hits should match to known imprinted genes. In this version of the report I collapsed the replicate sets in the Data Track Display options so that we only see the mean values for allele1 and allele2 rather than the values for all of the individual replicates.
Differential%20methylation%20Exercises.docx