iGenomics: Comprehensive DNA sequence analysis on your Smartphone

Palatnick, A., Zhou, B., Ghedin, E., Schatz, M. C. (December 2020) iGenomics: Comprehensive DNA sequence analysis on your Smartphone. Gigascience, 9 (12). ISSN 2047-217x

URL: https://pubmed.ncbi.nlm.nih.gov/33284326/
DOI: 10.1093/gigascience/giaa138


BACKGROUND: Following the miniaturization of integrated circuitry and other computer hardware over the past several decades, DNA sequencing is on a similar path. Leading this trend is the Oxford Nanopore sequencing platform, which currently offers the hand-held MinION instrument and even smaller instruments on the horizon. This technology has been used in several important applications, including the analysis of genomes of major pathogens in remote stations around the world. However, despite the simplicity of the sequencer, an equally simple and portable analysis platform is not yet available. RESULTS: iGenomics is the first comprehensive mobile genome analysis application, with capabilities to align reads, call variants, and visualize the results entirely on an iOS device. Implemented in Objective-C using the FM-index, banded dynamic programming, and other high-performance bioinformatics techniques, iGenomics is optimized to run in a mobile environment. We benchmark iGenomics using a variety of real and simulated Nanopore sequencing datasets of viral and bacterial genomes and show that iGenomics has performance comparable to the popular BWA-MEM/SAMtools/IGV suite, without necessitating a laptop or server cluster. CONCLUSIONS: iGenomics is available open source (https://github.com/stuckinaboot/iGenomics) and for free on Apple's App Store (https://apple.co/2HCplzr).

Item Type: Paper
Additional Information: 2047-217x Palatnick, Aspyn Zhou, Bin Ghedin, Elodie Schatz, Michael C Journal Article Gigascience. 2020 Dec 7;9(12):giaa138. doi: 10.1093/gigascience/giaa138.
Uncontrolled Keywords: DNA sequencing mobile computing variant analysis
Subjects: bioinformatics > genomics and proteomics > analysis and processing
bioinformatics > genomics and proteomics
bioinformatics > computational biology
CSHL Authors:
Communities: CSHL labs > Schatz lab
Depositing User: Matthew Dunn
Date: 7 December 2020
Date Deposited: 19 Feb 2021 19:44
Last Modified: 01 Feb 2024 16:43
PMCID: PMC7720420
Related URLs:
URI: https://repository.cshl.edu/id/eprint/39874

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