Evidence map›Paper›PMID 35191776›Full record

ArticlemSystems2022

Using AnnoTree to Get More Assignments, Faster, in DIAMOND+MEGAN Microbiome Analysis.

Anupam Gautam, Hendrik Felderhoff, Caner Bağci, Daniel H Huson

Open access · goldAbstract 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 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
4.1field-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

23 citing papers in PubMed, 42 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Anupam GautamInstitute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany.
Hendrik FelderhoffInstitute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany.
Caner BağciInstitute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany.
Daniel H HusonInstitute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany.
University of Tübingen · DEGerman Center for Infection Research · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In microbiome analysis, one main approach is to align metagenomic sequencing reads against a protein reference database, such as NCBI-nr, and then to perform taxonomic and functional binning based on the alignments. This approach is embodied, for example, in the standard DIAMOND+MEGAN analysis pipeline, which first aligns reads against NCBI-nr using DIAMOND and then performs taxonomic and functional binning using MEGAN. Here, we propose the use of the AnnoTree protein database, rather than NCBI-nr, in such alignment-based analyses to determine the prokaryotic content of metagenomic samples. We demonstrate a 2-fold speedup over the usage of the prokaryotic part of NCBI-nr and increased assignment rates, in particular assigning twice as many reads to KEGG. In addition to binning to the NCBI taxonomy, MEGAN now also bins to the GTDB taxonomy.

Indexed as

MicrobiotaSoftwareDatabases, GeneticMetagenomeSequence Analysis, DNAalignmentAnnoTreefunctionfunctional analysismicrobiome analysisNCBI-nrprotein sequencessoftwaretaxonomy

Identifiers

PMID35191776
PMCPMC8862659
OpenAlexW4220804245

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.