RNA sequencing (RNA-Seq) is the current method of choice for characterizing transcriptomes and
quantifying gene expression changes. This next generation sequencing-based method provides unprecedented
depth and resolution. The negative binomial (NB) probability distribution has been shown to be a
useful model for frequencies of mapped RNA-Seq reads and consequently provides a basis for statistical analysis
of gene expression. Negative binomial exact tests are available for two-group comparisons but do not
extend to negative binomial regression analysis, which is important for examining gene expression as a function
of explanatory variables and for adjusted group comparisons accounting for other factors. We address
the adequacy of available large-sample tests for the small sample sizes typically available from RNA-Seq
studies and consider a higher-order asymptotic (HOA) adjustment to likelihood ratio tests. We demonstrate
that 1) the HOA-adjusted likelihood ratio test is practically indistinguishable from the exact test in situations
where the exact test is available, 2) the type I error of the HOA test matches the nominal specification in
regression settings we examined via simulation, and 3) the power of the likelihood ratio test does not appear
to be affected by the HOA adjustment. This work helps clarify the accuracy of the unadjusted likelihood ratio
test and the degree of improvement available with the HOA adjustment. Furthermore, the HOA test may be
preferable even when the exact test is available because it does not require ad hoc library size adjustments.Keywords: Regression, RNA-Seq, Overdispersion, Extra- Poisson variation, Negative binomial, Higher-order asymptotic