As genome sequence data sets continue to grow, there is a pressing need to develop accurate yet memory-efficient means of assembling genomesde novo. Using new computational tools, the authors assembled a human genome using less than 64 gigabytes of memory. A compression algorithm stores the reads efficiently by taking advantage of redundancy between them; the compressed reads are then error-corrected and assembled by String Graph Assembler, which is a new algorithm that is easily parallelizable.