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Kreimer, A.* ; Zeng, H.* ; Edwards, M.D.* ; Guo, Y.* ; Tian, K.* ; Shin, S.* ; Welch, R.* ; Wainberg, M.* ; Mohan, R.* ; Sinnott-Armstrong, N.A.* ; Li, Y.* ; Eraslan, G. ; Amin, T.B.* ; Goke, J.* ; Müller, N.S. ; Kellis, M.* ; Kundaje, A.* ; Beer, M.A.* ; Keles, S.* ; Gifford, D.K.* ; Yosef, N.*

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

Hum. Mutat. 38, 1240-1250 (2017)
Postprint DOI PMC
Open Access Green
In many human diseases, associated genetic changes tend to occur within non-coding regions, whose effect might be related to transcriptional control. A central goal in human genetics is to understand the function of such non-coding 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.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Eqtls ; Functional Genomics ; Gene Regulation ; Massive Paralleled Reporter Assays; Protein-dna Interactions; Binding Microarray Data; Human Genome; In-vivo; Transcriptional Regulation; Systematic Dissection; Regulatory Motifs; Online Database; Chromatin; Variants
Sprache englisch
Veröffentlichungsjahr 2017
HGF-Berichtsjahr 2017
ISSN (print) / ISBN 1059-7794
e-ISSN 1098-1004
Zeitschrift Human Mutation
Quellenangaben Band: 38, Heft: 9, Seiten: 1240-1250 Artikelnummer: , Supplement: ,
Verlag Wiley
Verlagsort Hoboken
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-503800-001
DOI 10.1002/humu.23197
WOS ID WOS:000407861100020
Scopus ID 85014799167
PubMed ID 28220625
Erfassungsdatum 2017-05-24
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