Enabling Genomics Pipelines in Commodity Personal Computers With Flash Storage - Cadenelli, Nicola; Jun, Sang-Woo; Polo, Jordà; Wright, Andrew; Carrera, David; Arvind, (Frontiers in Genetics, 2021)
Analysis of a patient’s genomics data is the first step towards precision medicine. Such analyses are performed on expensive enterprise-class server machines because input data sets are large, and the intermediate data structures are even larger (TB-size) and require random-accesses. We present a general method to perform a specific genomics problem, mutation detection, on a cheap commodity Personal Computer (PC) with a small amount of DRAM. We construct and access large histograms of k-mers efficiently on external storage (SSDs) and apply our technique to a state-of-the-art reference-free genomics algorithm, SMUFIN, to create SMUFIN-F. We show that on two PCs, SMUFIN-F can achieve the same throughput at only one third (36%) the hardware cost and half (45%) the energy compared to SMUFIN on an enterprise-class server. To the best of our knowledge, SMUFIN-F is the first reference-free system that can detect somatic mutations on commodity PCs for whole human genomes. We believe our technique should apply to other k-mer or n-gram based algorithms.