Enabling Genomics Pipelines in Commodity Personal Computers With Flash Storage
Name
fgene-12-615958.pdf
Size
4.78 MB
Format
Adobe PDF
Checksum (MD5)
ab181bb5661f7c25aae42f90dddb4bde
Author(s)
Polo, Jordà
Cadenelli, Nicola
Jun, Sang-Woo
Wright, Andrew
Carrera, David
Date Issued
April 29, 2021
Journal
Frontiers in Genetics
Publisher
Frontiers Media SA
Citation
Cadenelli N, Jun S-W, Polo J, Wright A, Carrera D and Arvind (2021) Enabling Genomics Pipelines in Commodity Personal Computers With Flash Storage. Front. Genet. 12:615958.
Version
Final published version
Abstract
Analysis of a patient's genomics data is the first step toward 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 referencefree 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.
Subjects
precision medicine
N-grams
K-mers
flash storage
NVME
asynchronous key-value store
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.3389/fgene.2021.615958
