Timeline for Inflated p-values in quantitative trait analysis
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| May 25, 2020 at 12:51 | vote | accept | sergiovm | ||
| May 20, 2020 at 16:27 | history | edited | Maximilian Press | CC BY-SA 4.0 |
removed inappropriate reference, added more context for population structure correction.
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| May 20, 2020 at 16:24 | comment | added | Maximilian Press | @SergioVillicana You honestly can never know whether you have corrected for all confounding variables. Family structure is ok but underlying genetic relatedness, e.g. cryptic relatedness, is much more difficult to detect. Additionally, I realized that the Arabidopsis paper (mentioning the epigenetic similarity matrix) might not be appropriate, I got confused thinking about methylation as response vs. explanatory. I'm editing the answer to remove that paper. | |
| May 20, 2020 at 12:43 | comment | added | sergiovm | Thanks @MaximilianPress. Actually I'm don't think we have other confounding variables, we are correcting for all the possible ones, including family structure, and all data come from the same population. After the adjustment for residuals of methylation, data is normally distributed. It is not binary, but the probability of being methylated. I'll check the papers you mention. | |
| May 20, 2020 at 5:44 | history | answered | Maximilian Press | CC BY-SA 4.0 |