I hope this really doesn't come across as a dumb question (newbie alert) but I have a question that has really been bugging me.
To make a long story short, we determined differentially expressed genes using Cuffdiff. The conclusion for one of the comparisons doesn't exactly jive with what's accepted so we keep revisiting the issue. The terms "grouped" and "pairwise" keep coming up. Our in-house statistician prefers the grouped results but other colleagues say to use pairwise. Basically we have 8 eyes. And we're doing some comparisons between tissues. So for the grouped comparison, we take all the read counts for condition 1 in all eyes and compare it to condition 2 in all the eyes. Now, the suggestion is to compare condition 1 to condition 2 in each eye separately. And THEN somehow find a combined p-value. Another team member is using Cuffdiff and apparently there is an easy way to do this. I, however, have been using NOISeq, edgeR, and DESeq. I had grown particularly fond of NOISeq. However, to me, it just doesn't make sense to do these individual pairwise comparisons. At least for NOISeq, which performs better with biological replicates. Am I understanding something incorrectly??? Someone please clarify this for me. What is the benefit of doing the comparisons individually? To me, it's just a lot of noise because now you're getting differences between individuals.
To make a long story short, we determined differentially expressed genes using Cuffdiff. The conclusion for one of the comparisons doesn't exactly jive with what's accepted so we keep revisiting the issue. The terms "grouped" and "pairwise" keep coming up. Our in-house statistician prefers the grouped results but other colleagues say to use pairwise. Basically we have 8 eyes. And we're doing some comparisons between tissues. So for the grouped comparison, we take all the read counts for condition 1 in all eyes and compare it to condition 2 in all the eyes. Now, the suggestion is to compare condition 1 to condition 2 in each eye separately. And THEN somehow find a combined p-value. Another team member is using Cuffdiff and apparently there is an easy way to do this. I, however, have been using NOISeq, edgeR, and DESeq. I had grown particularly fond of NOISeq. However, to me, it just doesn't make sense to do these individual pairwise comparisons. At least for NOISeq, which performs better with biological replicates. Am I understanding something incorrectly??? Someone please clarify this for me. What is the benefit of doing the comparisons individually? To me, it's just a lot of noise because now you're getting differences between individuals.
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