Evaluating Methods for Differential Gene Expression And Alternative Splicing Using Internal Synthetic Controls
AbstractHigh-throughput transcriptome sequencing has become a powerful tool in the study of human diseases. Identification of causal mechanisms may entail analysis of differential gene expression (DGE), differential transcript/isoform expression (DTE) and identification, classification and quantification of alternative splicing (AS) and/or detection of novel AS events. For such a global transcriptome profiling execution of multi-level data analysis methodologies is required. Each level presents its own unique challenges and the questions about their performance remains. In this work we present results from systematic and consistent assessing and comparing a number of widely used methods for detecting DGE, DTE and AS using internal control “spike-in” sequences (Sequins) in RNA-seq data. We demonstrated that inclusion of internal controls in RNA-seq experiments allows accurate determination of lower bounds detection levels, and better assessment of DGE, DTE and AS accuracy and sensitivity. Tools for RNA-seq read alignment and detection of DGE performed reasonably. More efforts are needed to improve specificity and sensitivity of DTE and AS detection. Low expression of isoforms accompanied with sequencing depth does impact sensitivity and specificity of DTE and AS tools.
