Work efficiency: a new criterion for comprehensive comparison and evaluation of statistical methods in large-scale identification of differentially expressed genes.

Abstract:

:Receiver operating characteristic (ROC) has been widely used to evaluate statistical methods, but a fatal problem is that ROC cannot evaluate estimation of the false discovery rate (FDR) of a statistical method and hence the area under of curve as a criterion cannot tell us if a statistical method is conservative. To address this issue, we propose an alternative criterion, work efficiency. Work efficiency is defined as the product of the power and degree of conservativeness of a statistical method. We conducted large-scale simulation comparisons among the optimizing discovery procedure (ODP), the Bonferroni (B-) procedure, Local FDR (Localfdr), ranking analysis of the F-statistics (RAF), the Benjamini-Hochberg (BH-) procedure, and significance analysis of microarray data (SAM). The results show that ODP, SAM, and the B-procedure perform with low efficiencies while the BH-procedure, RAF, and Localfdr work with higher efficiency. ODP and SAM have the same ROC curves but their efficiencies are significantly different.

journal_name

Genomics

journal_title

Genomics

authors

Tan YD

doi

10.1016/j.ygeno.2011.05.006

subject

Has Abstract

pub_date

2011-11-01 00:00:00

pages

390-9

issue

5

eissn

0888-7543

issn

1089-8646

pii

S0888-7543(11)00130-3

journal_volume

98

pub_type

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