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Genes were considered to be differential expressed when test statistics reply p-Values were less than 0.05 and calculated fold changes between the control and the treatment exceeded 1.5.
EdgeR uses Fisher's exact test to compute p-values for the calculated fold changes.
In Figure 2, we show a correlation plot comparing the calculated fold changes in genes expression between the two labs.
For the EST data, we used transcripts per million (TPM) instead of absolute expression abundance, and for Q_PCR results, we calculated fold changes directly, according to the manufacture's instruction.
As expected, the overall correlation of the calculated fold changes for 205,465 exon probe sets (14,236 genes) between both platforms was slightly lower than the gene level correlation (R = 0.91) as shown in Figure 1B.
To identify such genes, we calculated fold changes of 20639 genes that were measured in both studies (i.e. RNA-Seq in our project and the Affymetrix U133 Plus 2.0 microarrays used for the autopsy RNA study).
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Then using a series of pairwise comparisons between different sample sets we calculated fold change and p values (Student's t-test).
This allows such transcripts to be included in the normal analysis scheme, but their calculated fold change will be entirely artificial.
All sequences regulated by LPS/INFγ/APC with a calculated fold change of more than 2.0 (p<0.01) were subjected to one-way ANOVA factorial analysis, compared with the significantly regulated sequences (fold change >2, p value<0.01) by LPS/INFγ.
We calculated fold change and p-value for this difference of proportions.
Using these observed and expected values we calculated Fold Change and p-value for the enrichment.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com