The erccdashboard: an R Package for Analysis of External Spike-in RNA Controls in Gene Expression Experiments

External RNA spike-in control ratio abundance mixtures enable assessment of technical performance of a gene expression experiment and comparison of performance between gene expression experiments. We've developed an R package, the “erccdashboard”, to analyze ratio abundance mixtures of the External RNA Control Consortium (ERCC) controls for the purpose of gene expression experiment method validation. For RNA-Seq, analysis of sequence reads with existing QC metrics provides an assessment of sequencing and mapped read quality, the analysis of ERCC control ratio mixtures is intended to provide QC metrics that are relevant for gene expression analysis methods including transcript quantification and differential expression testing. The erccdashboard package addresses this critical analysis need with QC metrics for gene expression experiments including dynamic range, biases and variability in ratio measurements, diagnostic performance (discrimination of true positive and true negative controls), and empirical determination of the limit of detection of ratios. Using the erccdashboard package quantitative differences between these ratio measurement performance metrics were shown for experiments within the same laboratory, between different laboratories, and for different gene expression measurement technologies (sequencing platforms and microarrays). The ERCC control ratio measurements also provide a quantification of biases that may be addressed with normalization approaches, such as differences in mRNA fraction of total RNA for a pair of gene expression experiment samples and batch effects. The erccdashboard R software package is freely available and may be adopted as part of the QC process for any gene expression measurement analysis pipeline.