limma report | Omics-Datatype: PTX | Date-Time: 26_09_2024-14_33_40


Note!

This HTML report contains plots visualizing the results from the limma topTables.
Right-click on any plot in this report to save it as a .svg (vector graphic) file!

To understand the three limma result categories shown in this report, please download and review this PDF document

The grey shaded areas of the plots in this report cover the non-significant features!



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Report Info ℹ

omics data type :PTX
data description :Proteomics data of CHO cells
data collection date :February 2024
meta condition :NA
meta batch :NA
limma design :NA
analyst name :Thomas Rauter
contact info :thomas.rauter@plus.ac.at
project name :DGTX
method description :NA
results summary :NA
conclusions :NA

Downloads 📥

limma topTables :

Table of Contents

Time Effect

Features that have a significant time effect have a spline that shows a temporal pattern (the degree of temporal pattern that is sufficient for this depends on the adj.p-value threshold) within one level (then they are significant for that level). If the spline fit to the time course of a feature within a level is more or less flat over time, it will not be a significant feature (hit) in this limma result category.

Plot Explanation:

A p-value histogram shows the distribution of p-values from multiple statistical tests. On the x-axis, we have the unadjusted p-values, ranging from 0 to 1, while the y-axis represents the frequency, or how often p-values fall within a certain range. If there is no true signal, we expect the p-values to be uniformly distributed, resulting in a flat histogram across all bins. This means that the tests are not detecting any statistically significant differences. However, if there is a strong signal in the data, we will see a concentration of p-values near 0, indicating that many tests have resulted in statistically significant findings. On the other hand, if most p-values are clustered near 1, it could suggest that the tests are not finding significant effects.

Plot
Plot

Average Difference Conditions

Features that have a significant average difference between two conditions (when there are more than two, all of them are compared pairwise) have different overall y-axis values for the spline in the compared levels. For example, if the time course of a given feature is on average around 17 in one level, but around 11 in the other level, this could be a significant feature (hit) in this limma result category (irrespective of the temporal pattern of this feature in any of the compared levels).

Plot Explanation:

A volcano plot is a scatter plot used to visualize the results of multiple hypothesis tests. The x-axis represents the log fold change, showing how much something changes between two groups, while the y-axis represents -log10(adj. p-value), which shows the statistical significance. Points further from the center on the x-axis show larger effects, and points higher on the y-axis indicate more significant results.

Plot
Plot

Interaction of Condition and Time

Features that have a significant interaction of condition and time have a different temporal pattern of their spline in both compared levels. For example, if the spline curve goes up in level 1 of the comparison, but goes down in level 2, this could be a significant feature (hit) in this limma result category.

Plot