Predicting gene expression in massively parallel reporter assays: A comparative study

Anat Kreimer, Haoyang Zeng, Matthew D. Edwards, Yuchun Guo, Kevin Tian, Sunyoung Shin, Rene Welch, Michael Wainberg, Rahul Mohan, Nicholas A. Sinnott-Armstrong, Yue Li, Gökcen Eraslan, Talal Bin Amin, Ryan Tewhey, Pardis C. Sabeti, Jonathan Goke, Nikola S. Mueller, Manolis Kellis, Anshul Kundaje, Michael A. BeerSunduz Keles, David K. Gifford, Nir Yosef

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


In many human diseases, associated genetic changes tend to occur within noncoding regions, whose effect might be related to transcriptional control. A central goal in human genetics is to understand the function of such noncoding regions: given a region that is statistically associated with changes in gene expression (expression quantitative trait locus [eQTL]), does it in fact play a regulatory role? And if so, how is this role “coded” in its sequence? These questions were the subject of the Critical Assessment of Genome Interpretation eQTL challenge. Participants were given a set of sequences that flank eQTLs in humans and were asked to predict whether these are capable of regulating transcription (as evaluated by massively parallel reporter assays), and whether this capability changes between alternative alleles. Here, we report lessons learned from this community effort. By inspecting predictive properties in isolation, and conducting meta-analysis over the competing methods, we find that using chromatin accessibility and transcription factor binding as features in an ensemble of classifiers or regression models leads to the most accurate results. We then characterize the loci that are harder to predict, putting the spotlight on areas of weakness, which we expect to be the subject of future studies.

Original languageEnglish (US)
Pages (from-to)1240-1250
Number of pages11
JournalHuman mutation
Issue number9
StatePublished - Sep 2017


  • eQTLs
  • functional genomics
  • gene regulation
  • massively parallel reporter assays

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)


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