Open Access Highly Accessed Methodology article

The RIN: an RNA integrity number for assigning integrity values to RNA measurements

Andreas Schroeder13, Odilo Mueller2*, Susanne Stocker14, Ruediger Salowsky1, Michael Leiber1, Marcus Gassmann1, Samar Lightfoot2, Wolfram Menzel5, Martin Granzow6 and Thomas Ragg6*

Author Affiliations

1 Agilent Technologies, Hewlett-Packard-Strasse 8, 76337 Waldbronn, Germany.

2 Agilent Technologies, 5301 Stevens Creek Blvd., Santa Clara, CA 95051, USA

3 ABP, Schiphol Boulevard 239, 1118 BH Schiphol. The Netherlands.

4 Roche Diagnostics GmbH, Nonnenwald 2, 82372 Penzberg, Germany.

5 Universit├Ąt Karlsruhe, ILKD, Am Fasanengarten 5, 76131 Karlsruhe, Germany.

6 quantiom bioinformatics GmbH & Co. KG, Ringstrasse 61, 76356 Weingarten, Germany.

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BMC Molecular Biology 2006, 7:3  doi:10.1186/1471-2199-7-3

Published: 31 January 2006



The integrity of RNA molecules is of paramount importance for experiments that try to reflect the snapshot of gene expression at the moment of RNA extraction. Until recently, there has been no reliable standard for estimating the integrity of RNA samples and the ratio of 28S:18S ribosomal RNA, the common measure for this purpose, has been shown to be inconsistent. The advent of microcapillary electrophoretic RNA separation provides the basis for an automated high-throughput approach, in order to estimate the integrity of RNA samples in an unambiguous way.


A method is introduced that automatically selects features from signal measurements and constructs regression models based on a Bayesian learning technique. Feature spaces of different dimensionality are compared in the Bayesian framework, which allows selecting a final feature combination corresponding to models with high posterior probability.


This approach is applied to a large collection of electrophoretic RNA measurements recorded with an Agilent 2100 bioanalyzer to extract an algorithm that describes RNA integrity. The resulting algorithm is a user-independent, automated and reliable procedure for standardization of RNA quality control that allows the calculation of an RNA integrity number (RIN).


Our results show the importance of taking characteristics of several regions of the recorded electropherogram into account in order to get a robust and reliable prediction of RNA integrity, especially if compared to traditional methods.