Swapping Metagenomics Preprocessing Pipeline Components Offers Speed and Sensitivity Increases

Author:

Armstrong George12ORCID,Martino Cameron123ORCID,Morris Justin45,Khaleghi Behnam6,Kang Jaeyoung5,DeReus Jeff13,Zhu Qiyun78,Roush Daniel78ORCID,McDonald Daniel1,Gonazlez Antonio1,Shaffer Justin P.1ORCID,Carpenter Carolina39,Estaki Mehrbod1ORCID,Wandro Stephen3,Eilert Sean10,Akel Ameen10,Eno Justin10,Curewitz Ken10,Swafford Austin D.3,Moshiri Niema6,Rosing Tajana356,Knight Rob1611ORCID

Affiliation:

1. Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA

2. Bioinformatics and Systems Biology Program, University of California, San Diego, California, USA

3. Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA

4. Department of Electrical and Computer Engineering, San Diego State University, San Diego, California, USA

5. Department of Electrical and Computer Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA

6. Department of Computer Science and Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA

7. School of Life Sciences, Arizona State University, Tempe, Arizona, USA

8. Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, Arizona, USA

9. Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA

10. Micron Technology, Inc., Folsom, California, USA

11. Department of Bioengineering, University of California, San Diego, La Jolla, California, USA

Abstract

In shotgun metagenomics studies that seek to relate changes in microbial DNA across samples, processing the data on a computer often takes longer than obtaining the data from the sequencing instrument. Recently developed software packages that perform individual steps in the pipeline of data processing in principle offer speed advantages, but in practice they may contain pitfalls that prevent their use, for example, they may make approximations that introduce unacceptable errors in the data.

Funder

HHS | NIH | National Institute of General Medical Sciences

Publisher

American Society for Microbiology

Subject

Computer Science Applications,Genetics,Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Biochemistry,Physiology,Microbiology

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