<p>You're misinterpreting the moderated T-statistic, it's basically the fold-change divided by its variance. The p-value comes directly from that, so if you filter by moderated fold-change you're just setting an unknown (unless you go through the trouble of figuring it out) p-value threshold. Instead, do exactly as you've been doing and set appropriate (adjusted) p-value and fold-change thresholds.</p>

CC BY-SA 3.0
2017-10-19T19:17:34.760Z
2017-10-19T19:17:34.760Z
Devon Ryan
<p>I'm looking at some microarray data. For the first time I've calculated a <a href="https://support.bioconductor.org/p/6124/" rel="nofollow noreferrer">moderated T statistic</a> from <a href="http://bioconductor.org/packages/release/bioc/html/limma.html" rel="nofollow noreferrer">limma</a>.</p>

<p>Is there any standard practice for where to cut off that value? For log2 fold change I usually cut off at +/- 1.5 and adjust accordingly; for adjusted p value I cut off at p&lt;0.01 and adjust accordingly. </p>

<p>These moderated T statistics seem a little higher than log2 fold change and I'm not sure what is generally accepted as significant.</p>

<p>Thanks!</p>

CC BY-SA 3.0
2017-10-19T18:57:40.367Z
If you're filtering by the (adjusted) p-value, why do you want to also filter by moderated T-statistic? The p-value basically comes from the moderated T-statistic, after all.
Devon Ryan
CC BY-SA 3.0
2017-10-19T19:01:46.207Z
I would like to have values that are real but are also above a particular magnitude. The P value gives me an idea of whether the finding is real, but I also need a way to cut-off on magnitude. I'd usually do this by filtering l|og2Fold|>1.5, but I was hoping to have a similar moderated T-statistic cutoff. Or am I misinterpreting the moderated T statistic?
julianstanley
<bioconductor><r><differential-expression><microarray>
Standard Cutoff for Moderated T-statistics
# Standard Cutoff for Moderated T-statistics

(Asked by: username_0 on 2017-10-19)

I'm looking at some microarray data. For the first time I've calculated a [moderated T statistic](https://support.bioconductor.org/p/6124/) from [limma](http://bioconductor.org/packages/release/bioc/html/limma.html).

Is there any standard practice for where to cut off that value? For log2 fold change I usually cut off at +/- 1.5 and adjust accordingly; for adjusted p value I cut off at p<0.01 and adjust accordingly.

These moderated T statistics seem a little higher than log2 fold change and I'm not sure what is generally accepted as significant.

Thanks!

**Tags:** bioconductor, r, differential-expression, microarray
> **Comments:**
> **username_1**: If you're filtering by the (adjusted) p-value, why do you want to also filter by moderated T-statistic? The p-value basically comes from the moderated T-statistic, after all.  
> **username_0**: I would like to have values that are real but are also above a particular magnitude. The P value gives me an idea of whether the finding is real, but I also need a way to cut-off on magnitude. I'd usually do this by filtering l|og2Fold|>1.5, but I was hoping to have a similar moderated T-statistic cutoff. Or am I misinterpreting the moderated T statistic?  

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## 1 answers

### Answer by username_1 on 2017-10-19. Score: 3 | Accepted answer

You're misinterpreting the moderated T-statistic, it's basically the fold-change divided by its variance. The p-value comes directly from that, so if you filter by moderated fold-change you're just setting an unknown (unless you go through the trouble of figuring it out) p-value threshold. Instead, do exactly as you've been doing and set appropriate (adjusted) p-value and fold-change thresholds.


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