Hi all,
I am looking at the following bioconductor document: http://www.bioconductor.org/help/workflows/rnaseqGene/#time-course-experiments
Towards the end of the documents, there is a heatmap with the following title: "Heatmap of log2 fold changes for genes with smallest adjusted p value"
It references the log2FC values of the comparisons performed in the following list:
- "Intercept"
- "strain_mut_vs_wt"
- "minute_15_vs_0"
- "minute_30_vs_0"
- "minute_60_vs_0"
- "minute_120_vs_0"
- "minute_180_vs_0"
- "strainmut.minute15"
- "strainmut.minute30"
- "strainmut.minute60"
- "strainmut.minute120"
- "strainmut.minute180"
I assume that (2) are the log2FC from the comparison of mutant to wildtype strain (at time = 0?) and (3) is the comparison of two timepoints, 15 minutes vs baseline at time zero, taking into account the effect of the strain.
However, what are the comparisons performed for (8)-(12)?
Is (8) wildtype strain vs mutant at 15 minutes? Or is it the mutant strain at 15 minutes vs 0 minutes?
Thanks for any insight!
Great, thank you for the reference!
The interaction terms
genotypeII.conditionB
andgenotypeIII.conditionB
give the difference between the condition effect for a given genotype and the condition effect for the reference genotype.So the "strainmut.minute15" column shows the log2FC for the mutant at 15 minutes compared to the wildtype at 15 minutes?
In that case, there does not seem to be a column for mutant at 0 minutes vs wildtype at 0 minutes in the heatmap. However, the betas variable does contain a column labeled "strain_mut_vs_wt" which was removed before plotting the heatmap -- is that the data at time point zero?
Yes, the main effect strain_mut_vs_wt is the mutant vs WT effect at time 0, and the Intercept is then the WT base-level expression at time 0.
Great! And if a gene has a positive log2FC in the "strain_mut_vs_wt" column, then it is upregulated in the mutant strain (because the mutant strain is listed first in the description")?
Yes, you can read more about how to interpret log2 fold changes in this section of the workflow:
http://www.bioconductor.org/help/workflows/rnaseqGene/#differential-expression-analysis
"The column
log2FoldChange
is the effect size estimate. It tells us how much the gene’s expression seems to have changed due to treatment with dexamethasone in comparison to untreated samples. This value is reported on a logarithmic scale to base 2: for example, a log2 fold change of 1.5 means that the gene’s expression is increased by a multiplicative factor of 21.5 ≈ 2.82."Thank you, I appreciate your help with interpreting these more complex models!