Hello,
We just finished the QC for the total reads obtain from a Time Course RNA-Seq experiment (Illumina HiSeq2000), and are satisfied with the quality.
Now we have started the Differential Expression Gene analysis, and the strategy proposed by our bioinformatican was the following:
Calculating DEG for every condition compared with the initial one, so we will have at the end 5 comparisons. DEG for each gene will show a certain p-value in each case, so we would count as statistically significant those genes with p-value<0.05 in all 5 comparisons.
Do you think this is a right approach?
Thanks in advance for your comments and advices.
We just finished the QC for the total reads obtain from a Time Course RNA-Seq experiment (Illumina HiSeq2000), and are satisfied with the quality.
Now we have started the Differential Expression Gene analysis, and the strategy proposed by our bioinformatican was the following:
Calculating DEG for every condition compared with the initial one, so we will have at the end 5 comparisons. DEG for each gene will show a certain p-value in each case, so we would count as statistically significant those genes with p-value<0.05 in all 5 comparisons.
Do you think this is a right approach?
Thanks in advance for your comments and advices.
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