TY - JOUR
T1 - The statistical properties of gene-set analysis
AU - De Leeuw, Christiaan A.
AU - Neale, Benjamin M.
AU - Heskes, Tom
AU - Posthuma, Danielle
PY - 2016/6/1
Y1 - 2016/6/1
N2 - The rapid increase in loci discovered in genome-wide association studies has created a need to understand the biological implications of these results. Gene-set analysis provides a means of gaining such understanding, but the statistical properties of gene-set analysis are not well understood, which compromises our ability to interpret its results. In this Analysis article, we provide an extensive statistical evaluation of the core structure that is inherent to all gene- set analyses and we examine current implementations in available tools. We show which factors affect valid and successful detection of gene sets and which provide a solid foundation for performing and interpreting gene-set analysis.
AB - The rapid increase in loci discovered in genome-wide association studies has created a need to understand the biological implications of these results. Gene-set analysis provides a means of gaining such understanding, but the statistical properties of gene-set analysis are not well understood, which compromises our ability to interpret its results. In this Analysis article, we provide an extensive statistical evaluation of the core structure that is inherent to all gene- set analyses and we examine current implementations in available tools. We show which factors affect valid and successful detection of gene sets and which provide a solid foundation for performing and interpreting gene-set analysis.
UR - http://www.scopus.com/inward/record.url?scp=84963595642&partnerID=8YFLogxK
U2 - https://doi.org/10.1038/nrg.2016.29
DO - https://doi.org/10.1038/nrg.2016.29
M3 - Article
C2 - 27070863
SN - 1471-0056
VL - 17
SP - 353
EP - 364
JO - Nature Reviews Genetics
JF - Nature Reviews Genetics
IS - 6
M1 - 6
ER -