What is Quantile Normalization?
Quantile normalization, in the field of statistics, is a technique that makes two distributions identical in statistical properties. The two distributions in this instance, which we’ll discuss later, are the test and reference distributions. To make them identical in terms of statistical properties, the highest entry in the test and reference distributions should be aligned, followed by the next highest, and so on.
While it sounds complex, you can think of it as two lines of five students arranged by height (i.e., shortest to tallest). The first line could have Ross, Chandler, Joey, Gunther, and Frank, and the second could have Phoebe, Monica, Rachel, Ursula, and Janice. To quantile-normalize the lines, Ross and Phoebe (the shortest male and female, making them identical in the statistical property height) will be the first test and reference subjects, respectively, followed by Chandler and Monica, and so on.