IsoDOT Detects Differential RNA-isoform Expression/Usage with respect to a Categorical or Continuous Covariate with High Sensitivity and Specificity

TL;DR

IsoDOT is a novel statistical method that accurately detects differential isoform expression and usage in RNA-seq data, including for continuous covariates and single-case comparisons, with high sensitivity and specificity.

Contribution

IsoDOT introduces new capabilities for differential isoform analysis, specifically handling continuous covariates and single-case comparisons, which existing methods cannot do.

Findings

High sensitivity and specificity demonstrated in simulations

Identified genes with isoform usage changes in haloperidol-treated mice

Effective for both categorical and continuous covariate analysis

Abstract

We have developed a statistical method named IsoDOT to assess differential isoform expression (DIE) and differential isoform usage (DIU) using RNA-seq data. Here isoform usage refers to relative isoform expression given the total expression of the corresponding gene. IsoDOT performs two tasks that cannot be accomplished by existing methods: to test DIE/DIU with respect to a continuous covariate, and to test DIE/DIU for one case versus one control. The latter task is not an uncommon situation in practice, e.g., comparing paternal and maternal allele of one individual or comparing tumor and normal sample of one cancer patient. Simulation studies demonstrate the high sensitivity and specificity of IsoDOT. We apply IsoDOT to study the effects of haloperidol treatment on mouse transcriptome and identify a group of genes whose isoform usages respond to haloperidol treatment.