Evidence map›Paper›PMID 28066816›Full record

ArticlemSystems

From Genomes to Phenotypes: Traitar, the Microbial Trait Analyzer.

Aaron Weimann, Kyra Mooren, Jeremy Frank, Phillip B Pope, Andreas Bremges, Alice C McHardy

Open access · goldAbstract read
In one paragraph

Article in mSystems. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
91citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 5% of its field
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

91 citing papers in PubMed, 1 synthesis or guideline pooled it, 163 citations in OpenAlex.

  1. Pooled it
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  14. Noncanonical genetic markers resolve the pre-GOE emergence of aerobic bacteria in Earth's history.Proceedings of the National Academy of Sciences of the United States of America · 2026
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31 more citing papers are in PubMed but not listed here.

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

6 authors at 4 institutions in 2 countries.

Aaron WeimannComputational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany; German Center for Infection Research (DZIF), Partner Site Hannover-Braunschweig, Braunschweig, Germany; Department for Algorithmic Bioinformatics, Heinrich Heine University, Düsseldorf, Germany.
Kyra MoorenComputational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany; Department for Algorithmic Bioinformatics, Heinrich Heine University, Düsseldorf, Germany.
Jeremy FrankDepartment of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway.
Phillip B PopeDepartment of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway.
Andreas BremgesComputational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany; German Center for Infection Research (DZIF), Partner Site Hannover-Braunschweig, Braunschweig, Germany.
Alice C McHardyComputational Biology of Infection Research, Helmholtz Center for Infection Research, Braunschweig, Germany; German Center for Infection Research (DZIF), Partner Site Hannover-Braunschweig, Braunschweig, Germany; Department for Algorithmic Bioinformatics, Heinrich Heine University, Düsseldorf, Germany.
Helmholtz Centre for Infection Research · DENorwegian University of Life Sciences · NOGerman Center for Infection Research · DEHeinrich Heine University Düsseldorf · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The number of sequenced genomes is growing exponentially, profoundly shifting the bottleneck from data generation to genome interpretation. Traits are often used to characterize and distinguish bacteria and are likely a driving factor in microbial community composition, yet little is known about the traits of most microbes. We describe Traitar, the microbial trait analyzer, which is a fully automated software package for deriving phenotypes from a genome sequence. Traitar provides phenotype classifiers to predict 67 traits related to the use of various substrates as carbon and energy sources, oxygen requirement, morphology, antibiotic susceptibility, proteolysis, and enzymatic activities. Furthermore, it suggests protein families associated with the presence of particular phenotypes. Our method uses L1-regularized L2-loss support vector machines for phenotype assignments based on phyletic patterns of protein families and their evolutionary histories across a diverse set of microbial species. We demonstrate reliable phenotype assignment for Traitar to bacterial genomes from 572 species of eight phyla, also based on incomplete single-cell genomes and simulated draft genomes. We also showcase its application in metagenomics by verifying and complementing a manual metabolic reconstruction of two novel

Indexed as

ancestral trait reconstructiongenotype-phenotype inferencemetagenomicsmicrobial traitsphenotypesphyletic patternssingle-cell genomicssupport vector machines

Identifiers

PMID28066816
PMCPMC5192078
OpenAlexW2952310764

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.