TopHat is an efficient read-mapping algorithm designed to align RNA-Seq reads to a reference genome without relying on known splice sites. It maps reads to splice sites at a rate of approximately 2.2 million reads per CPU hour, significantly faster than previous systems. TopHat identifies novel splice junctions by mapping all reads to the reference genome using Bowtie, followed by an assembly step using Maq. The algorithm then assembles the mapped reads into islands of contiguous sequence, inferring them as putative exons. Splice junctions are identified by enumerating canonical donor and acceptor sites within these islands and checking for reads that span the junctions. TopHat's sensitivity and specificity are evaluated through comparisons with other methods, demonstrating its ability to detect both known and novel splice junctions. The software is freely available and has been shown to be effective in processing entire RNA-Seq experiments in less than a day on a standard desktop computer.TopHat is an efficient read-mapping algorithm designed to align RNA-Seq reads to a reference genome without relying on known splice sites. It maps reads to splice sites at a rate of approximately 2.2 million reads per CPU hour, significantly faster than previous systems. TopHat identifies novel splice junctions by mapping all reads to the reference genome using Bowtie, followed by an assembly step using Maq. The algorithm then assembles the mapped reads into islands of contiguous sequence, inferring them as putative exons. Splice junctions are identified by enumerating canonical donor and acceptor sites within these islands and checking for reads that span the junctions. TopHat's sensitivity and specificity are evaluated through comparisons with other methods, demonstrating its ability to detect both known and novel splice junctions. The software is freely available and has been shown to be effective in processing entire RNA-Seq experiments in less than a day on a standard desktop computer.