As RNA integrity has long been known to be a problem in molecular biology studies, there are a few methods that have been used historically to determine the integrity of RNA. The most popular has long been agarose gel electrophoresis with ethidium bromide staining, allowing one to visualize the bands from the rRNA peaks. The height of the 28S and 18S bands can be compared to each other, with a 2:1 ratio indicating non-degraded RNA. While this method is very cheap and easy, there are several issues with this method, primarily its subjectivity, leading to inconsistent, non-standardized RNA quality assessments, and the large amounts of RNA that are needed to visualize it on an agarose gel, which can be problematic if there is not much RNA to work with. There are also a number of different problems that can arise from agarose gel electrophoresis, such as poor loading, uneven running, and uneven staining that lead to increased variability in the accuracy of using agarose gel electrophoresis to determine RNA integrity.
The RNA Integrity Number was developed by Agilent Technologies in 2005. The algorithm was generated by taking hundreds of samples and having specialists manually assign them all a value of 1 to 10 based on their integrity, with 10 being the highest. Adaptive learning tools using a Bayesian learning technique were used to generate an algorithm that could predict the RIN, predominantly by using the features listed below under "Computation". This allows for all Agilent software to produce the same RIN for a given RNA sample, standardizing the measurement and making it much less subjective than earlier methods.