The problem of detecting differential gene expression with microarray data has led to innovative approaches to controlling false positives in multiple testing. False discovery rate (FDR) has been widely used as a measure of error in this multiple testing context. Direct estimation of FDR was recently proposed by Storey (2002) as a substantially more powerful alternative to the traditional sequential FDR controlling procedure, pioneered by Benjamini and Hochberg (1995). Direct estimation to FDR requires fixing a rejection region of interest and then conservatively estimating the associated FDR. On the other hand, sequential FDR procedure requires fixing a FDR control level and then estimating the rejection region. Thus, sequential and direct approaches to FDR control appear fundamentally different. However, these approaches can be unified and the methods compared using computational experiments designed to more reflect exploratory DNA microarray studies often implemented in p! ractice. Using simulation, we illustrate that modified sequential FDR algorithms are equivalent to the direct estimates of FDR and, hence, are as powerful. In addition, both approaches simply approximate the least conservative (optimal) sequential FDR procedure.