Evidence map›Paper›PMID 35293792›Full record

ArticlemSystems2022

Swapping Metagenomics Preprocessing Pipeline Components Offers Speed and Sensitivity Increases.

George Armstrong, Cameron Martino, Justin Morris, Behnam Khaleghi, Jaeyoung Kang, Jeff DeReus, Qiyun Zhu, Daniel Roush, Daniel McDonald, Antonio Gonazlez and 12 more

Abstract read
In one paragraph

Article in mSystems, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Environmental and Maternal Imprints on Infant Gut Metabolic Programming.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. The microbiome diversifiesbioRxiv : the preprint server for biology · 2024
    Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

George Armstrong *Department of Pediatrics, School of Medicine, University of California, San Diegogrid.266100.3, California, USA.ORCID 0000-0002-1061-3295
Cameron Martino *Department of Pediatrics, School of Medicine, University of California, San Diegogrid.266100.3, California, USA.ORCID 0000-0001-9334-1258
Justin MorrisDepartment of Electrical and Computer Engineering, San Diego State University, San Diego, California, USA.
Behnam KhaleghiDepartment of Computer Science and Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA.
Jaeyoung KangDepartment of Electrical and Computer Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA.
Jeff DeReusDepartment of Pediatrics, School of Medicine, University of California, San Diegogrid.266100.3, California, USA.
Qiyun ZhuSchool of Life Sciences, Arizona State Universitygrid.215654.1, Tempe, Arizona, USA.
Daniel RoushSchool of Life Sciences, Arizona State Universitygrid.215654.1, Tempe, Arizona, USA.ORCID 0000-0001-8025-2117
Daniel McDonaldDepartment of Pediatrics, School of Medicine, University of California, San Diegogrid.266100.3, California, USA.
Antonio GonazlezDepartment of Pediatrics, School of Medicine, University of California, San Diegogrid.266100.3, California, USA.
Justin P ShafferDepartment of Pediatrics, School of Medicine, University of California, San Diegogrid.266100.3, California, USA.ORCID 0000-0002-9371-6336
Carolina CarpenterCenter for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA.
Mehrbod EstakiDepartment of Pediatrics, School of Medicine, University of California, San Diegogrid.266100.3, California, USA.ORCID 0000-0003-4556-8444
Stephen WandroCenter for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA.
Sean EilertMicron Technology, Inc., Folsom, California, USA.
Ameen AkelMicron Technology, Inc., Folsom, California, USA.
Justin EnoMicron Technology, Inc., Folsom, California, USA.
Ken CurewitzMicron Technology, Inc., Folsom, California, USA.
Austin D SwaffordCenter for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA.
Niema MoshiriDepartment of Computer Science and Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA.
Tajana RosingCenter for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA.
Rob KnightDepartment of Pediatrics, School of Medicine, University of California, San Diegogrid.266100.3, California, USA.ORCID 0000-0002-0975-9019

Funding

UCSD/SDSU IRACDAK12GM068524 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI TREJO, JOANN · 2003 to 2025
$24.4M
NIGMS NIH HHS K12 GM068524
6 · The paper itself

Abstract

Increasing data volumes on high-throughput sequencing instruments such as the NovaSeq 6000 leads to long computational bottlenecks for common metagenomics data preprocessing tasks such as adaptor and primer trimming and host removal. Here, we test whether faster recently developed computational tools (Fastp and Minimap2) can replace widely used choices (Atropos and Bowtie2), obtaining dramatic accelerations with additional sensitivity and minimal loss of specificity for these tasks. Furthermore, the taxonomic tables resulting from downstream processing provide biologically comparable results. However, we demonstrate that for taxonomic assignment, Bowtie2's specificity is still required. We suggest that periodic reevaluation of pipeline components, together with improvements to standardized APIs to chain them together, will greatly enhance the efficiency of common bioinformatics tasks while also facilitating incorporation of further optimized steps running on GPUs, FPGAs, or other architectures. We also note that a detailed exploration of available algorithms and pipeline components is an important step that should be taken before optimization of less efficient algorithms on advanced or nonstandard hardware.

Indexed as

MetagenomicsSoftwareAlgorithmsComputational BiologyHigh-Throughput Nucleotide Sequencingalignmenthost filteringmetagenomics

Identifiers

PMID35293792
PMCPMC9040843

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.