Multiple testing in the genomics era: findings from Genetic Analysis Workshop 15, Group 15.
Recent advances in molecular technologies have resulted in the ability to screen hundreds of thousands of single nucleotide polymorphisms and tens of thousands of gene expression profiles. While these data have the potential to inform investigations into disease etiologies and advance medicine, the question of how to adequately control both type I and type II error rates remains. Genetic Analysis Workshop 15 datasets provided a unique opportunity for participants to evaluate multiple testing strategies applicable to microarray and single nucleotide polymorphism data. The Genetic Analysis Workshop 15 multiple testing and false discovery rate group (Group 15) investigated three general categories for multiple testing corrections, which are summarized in this review: statistical independence, error rate adjustment, and data reduction. We show that while each approach may have certain advantages, adequate error control is largely dependent upon the question under consideration and often requires the use of multiple analytic strategies.
Martin
Lisa J
LJ
Department of Pediatrics, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45229, USA. lisa.martin@cchmc.org
Woo
Jessica G
JG
Avery
Christy L
CL
Chen
Huann-Sheng
HS
North
Kari E
KE
Au
Kinman
K
Broët
Philippe
P
Dalmasso
Cyril
C
Guedj
Mickael
M
Holmans
Peter
P
Huang
Baisong
B
Kuo
Po-Hsiu
PH
Lam
Alex C
AC
Li
Hao
H
Manning
Alisa
A
Nikolov
Ivan
I
Sinha
Ritwik
R
Shi
Jianxin
J
Song
Kijoung
K
Tabangin
Meredith
M
Tang
Rui
R
Yamada
Ryo
R
D020869:Gene Expression Profiling; D005820:Genetic Testing / Q000379:methods*; D015894:Genome, Human; D006801:Humans; D020641:Polymorphism, Single Nucleotide