title: An adaptive alpha spending algorithm improves the power of statistical inference in microarray data analysis.
abstract: The adaptive alpha-spending algorithm incorporates additional contextual evidence (including correlations among genes) about differential expression to adjust the initial p-values to yield the alpha-spending adjusted p-values. The alpha-spending algorithm is named so because of its similarity with the alpha-spending algorithm in interim analysis of clinical trials in which stage-specific significance levels are assigned to each stage of the clinical trial. We show that the Bonferroni correction applied to the alpha-spending adjusted p-values approximately controls the Family Wise Error Rate under the complete null hypothesis. Using simulations we also show that the use of the alpha spending algorithm yields increased power over the unadjusted p-values while controlling FDR. We found the greater benefits of the alpha spending algorithm with increasing sample sizes and correlation among genes. The use of the alpha spending algorithm will result in microarray experiments that make more efficient use of their data and may help conserve resources.
authors.affiliation: Genomic Technologies Section - Research Technology Branch, NIH / NIAID, 50 South Drive, Room 5505, Bethesda, MD 20892-8005, USA. brandj@niaid.nih.gov
authors.forename: Jacob P L
authors.initials: JP
authors.lastname: Brand
authors.forename: Lang
authors.initials: L
authors.lastname: Chen
authors.forename: Xiangqin
authors.initials: X
authors.lastname: Cui
authors.forename: Alfred A
authors.initials: AA
authors.lastname: Bartolucci
authors.forename: Grier P
authors.initials: GP
authors.lastname: Page
authors.forename: Kyoungmi
authors.initials: K
authors.lastname: Kim
authors.forename: Stephen
authors.initials: S
authors.lastname: Barnes
authors.forename: Vinodh
authors.initials: V
authors.lastname: Srinivasasainagendra
authors.forename: Mark T
authors.initials: MT
authors.lastname: Beasley
authors.forename: David B
authors.initials: DB
authors.lastname: Allison