Introduction
infection, Tularemia, tularemia
DISEASE, INFECTION, TULAREMIA, TULAREMIA
Since 2008, high-throughput technologies, primarily transcriptomics, have been used to characterize the Some work has been done to benchmark RNA-Seq analyses and understand how technical parameters influence experimental findings (In this study, we sought to empirically establish the impact of these and other technical parameters on the ability to accurately assess differentially expressed genes (DEGs) using samples collected for a phase II clinical trial of a live attenuated tularemia vaccine. Tularemia is a disease caused by infection with the Gram-negative, aerobic and facultative intracellular bacterium, Specifically, our main goals were to (i) assess the reproducibility of gene expression measurements and the ability to detect the same DEGs in two different laboratories using technical replicate samples; (ii) assess the impact of various sequencing depths on gene representation for which we approximated an ultra-deeply sequenced PBMC transcriptome by pooling all hundred samples sequenced; (iii) estimate statistical power to determine DEGs as a function of effect size, sequencing depth, and sample size; (iv) define the impact of changes in technical parameters (sequencing depth and read length) on the identification of DEGs; (v) assess the accuracy of fold-change estimates using synthetic mRNA spike-ins for varying read-count filtering cutoffs; (vi) determine an empirical read-count cutoff for filtering out lowly-expressed genes, and (vii) establish recommendations for RNA-Seq analyses conducted in clinical vaccine studies. It is also important to note that the goals of this study were not to perform an exhaustive comparison of established analytical methods to quantify gene expression or detect DEGs, or to compare the performance of these tools, as these comparisons already exist in the literature (