What is p-value in gene expression?

The P-value is the probability for the experimental outcome as observed or more extreme, if there is no difference in expression between the experimental conditions. The P-value can serve as a probability measure to select differentially expressed genes from a pre-specified significance level (cutoff threshold).

What is the p-value usually?

The level of statistical significance is often expressed as a p-value between 0 and 1. The smaller the p-value, the stronger the evidence that you should reject the null hypothesis. A p-value less than 0.05 (typically ≤ 0.05) is statistically significant.

What does a P value of 0.05 indicate?

A p-value > 0.05 would be interpreted by many as “not statistically significant,” meaning that there was not sufficiently strong evidence to reject the null hypothesis and conclude that the groups are different.

What does p-value of 0.20 mean?

When power is close to 50%, getting a p-value greater than 0.20 is just as likely as getting a p-value between 0.05 and 0.20. And when power is less than 20%, getting a p-value greater than 0.20 is more than twice as likely as getting a p-value between 0.05 and 0.20.

What is the p-value of gene Y?

In our study of 1000 genes, let’s say gene Y had a p-value of 0.00005 and a q-value of 0.03. The probability that a test statistic of a non-differentially expressed gene would be as or more extreme as the test statistic for gene Y is 0.00005.

Is the level of significance the same as the p-value?

In conducting a test of significance or hypothesis test, there are two numbers that are easy to get confused. These numbers are easily confused because they are both numbers between zero and one, and are both probabilities. One number is called the p-value of the test statistic. The other number of interest is the level of significance or alpha.

What should the p-value of a null hypothesis be?

If the p-value is small we reject the null hypothesis and state that there is evidence against the null (i.e. the gene is differentially expressed). If we used the p-value directly from the Wald test with a significance cut-off of p < 0.05, that means there is a 5% chance it is a false positives.

What’s the difference between a p-value and an alpha value?

The p-value of the test statistic is a way of saying how extreme that statistic is for our sample data. The smaller the p-value, the more unlikely the observed sample. To determine if an observed outcome is statistically significant, we compare the values of alpha and the p-value.