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Present-day DNA sequencing techniques have evolved considerably from their early beginnings. A modern sequencing project is essentially an assembly-line environment and is therefore improved and accelerated by the degree to which slow and error-prone manual steps can be replaced by reliable and accurate automatic ones. For hardware, this typically means expanding the use of robotics, for example, to execute the multitude of micro-volume fluid transfers that occur for each of the samples processed in a project. Likewise, automated software replaces manual processing and analysis steps for samples wherever possible. In this article, we focus on one particular aspect of software: the automated handling of raw DNA data. Specifically, we discuss a number of critical software algorithms and components and how they have been woven into a framework for largely hands-off processing of Human Genome Project data at the Genome Sequencing Center. These data represent about 25% of the total public human sequencing project.