IsoDOT Detects Differential RNA-Isoform Expression/Usage With Respect to a Categorical or Continuous Covariate With High Sensitivity and Specificity

Wei Sun, Yufeng Liu, James J. Crowley, Ting Huei Chen, Hua Zhou, Haitao Chu, Shunping Huang, Pei Fen Kuan, Yuan Li, Darla Miller, Ginger Shaw, Yichao Wu, Vasyl Zhabotynsky, Leonard McMillan, Fei Zou, Patrick F. Sullivan, Fernando Pardo Manuel De Villena

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

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, for example, comparing the paternal and maternal alleles of one individual or comparing tumor and normal samples 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 the mouse transcriptome and identify a group of genes whose isoform usages respond to haloperidol treatment. Supplementary materials for this article are available online.

Original languageEnglish (US)
Pages (from-to)975-986
Number of pages12
JournalJournal of the American Statistical Association
Volume110
Issue number511
DOIs
StatePublished - Jul 3 2015

Bibliographical note

Publisher Copyright:
© 2015, © American Statistical Association.

Keywords

  • Differential isoform expression
  • Differential isoform usage
  • Isoform
  • Penalized regression
  • RNA-seq

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