RNA and DNA Sample QC
Sample QC refers to the evaluation of RNA samples before the amplification process. Assessment of sample concentration and integrity are essential for ensuring the quality of expression data. A fixed volume of each RNA sample is used to determine both sample concentration and integrity. Samples with concentrations exceeding the limits of the intended target protocol are automatically diluted and re-assayed to confirm accurate dilution. Samples passing RNA Sample QC are committed to Production Ready Plates (PRPs) for amplification. Sample QC for DNA follows a similar process as RNA, but samples passing DNA Sample QC are committed to gDNA Ready Plates (GRPs) for amplification.
RNA and DNA Sample Concentration, which varies depending on the target amplification protocol (refer to the RNA submission page), are both assessed using an automated RiboGreen fluorescent assay.
Sample Integrity is evaluated with the 28S/18S ratio and RNA Integrity Number (RIN) score from the Agilent Bioanalyzer capillary electrophoresis system. DNA Sample Integrity is evaluated using agarose gel electrophoresis (Invitrogen E-gel system).
Samples whose concentrations fall above the concentration range for a target protocol will be automatically diluted and re-assayed to confirm accurate dilution. If samples fail to meet the QC criteria, the Project Manager is notified and the Project Team determines how to proceed. In many cases, sample is either excluded from pools or excluded from the experiment altogether.
The Covance Genomics Laboratory (CGL) quality control of microarray data from the Affymetrix platform follows a collection of QC metrics and parameters that aid in the identification of problematic arrays. CGL uses both in-house and Affymetrix QC metrics in conjunction with QC functions provided by Bioconductor to assess array quality. Many QC metrics are based on values calculated by the MAS 5.0 algorithm.
After amplification, CGL evaluates the following metrics:
- Amplification yield
- A260/A280 ratio
QC metrics are designed to identify issues that occur at different stages of the process. They are therefore classified into 4 groups which represent different failure modes:
- Border QC
- Hybridization Data QC
- Amplification QC
- RNA QC