Evidence map›Paper›PMID 38895276›Full record

ArticlebioRxiv : the preprint server for biology2024

Lightweight taxonomic profiling of long-read metagenomic datasets with Lemur and Magnet.

Nicolae Sapoval, Yunxi Liu, Kristen D Curry, Bryce Kille, Wenyu Huang, Natalie Kokroko, Michael G Nute, Alona Tyshaieva, Alexander Dilthey, Erin K Molloy and 1 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Nicolae SapovalDepartment of Computer Science, Rice University, Houston, TX 77005, USA.ORCID 0000-0002-0736-5075
Yunxi LiuDepartment of Computer Science, Rice University, Houston, TX 77005, USA.ORCID 0000-0003-2657-1816
Kristen D CurryDepartment of Computer Science, Rice University, Houston, TX 77005, USA.ORCID 0000-0001-8375-397X
Bryce KilleDepartment of Computer Science, Rice University, Houston, TX 77005, USA.ORCID 0000-0003-2946-6915
Wenyu HuangDepartment of Computer Science, Rice University, Houston, TX 77005, USA.ORCID 0009-0000-0318-048X
Natalie KokrokoDepartment of Computer Science, Rice University, Houston, TX 77005, USA.ORCID 0009-0007-5548-9287
Michael G NuteDepartment of Computer Science, Rice University, Houston, TX 77005, USA.ORCID 0000-0003-4129-6525
Alona TyshaievaDepartment of Computer Science, University of Maryland, College Park, MD 20742, USA.
Alexander DiltheyDepartment of Computer Science, University of Maryland, College Park, MD 20742, USA.ORCID 0000-0002-6394-4581
Erin K MolloyDepartment of Bioengineerings, Rice University, Houston, TX 77005, USA.ORCID 0000-0001-5553-3312
Todd J TreangenDepartment of Computer Science, Rice University, Houston, TX 77005, USA.ORCID 0000-0002-3760-564X

Funding

TRAINING PROGRAM IN COMPUTATIONAL BIOLOGY AND MEDICINET15LM007093 · NLM · RICE UNIVERSITY · PI Lydia E. Kavraki · 1992 to 2026
$20.8M
Project 3: Functional Microbiome and Host Signatures in Transition from Commensal to pathogenP01AI152999 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ARIAS, CESAR AUGUSTO, SAVIDGE, TOR C. · 2020 to 2025
$12.0M
NIAID NIH HHS P01 AI152999NLM NIH HHS T15 LM007093
6 · The paper itself

Abstract

The advent of long-read sequencing of microbiomes necessitates the development of new taxonomic profilers tailored to long-read shotgun metagenomic datasets. Here, we introduce Lemur and Magnet, a pair of tools optimized for lightweight and accurate taxonomic profiling for long-read shotgun metagenomic datasets. Lemur is a marker-gene-based method that leverages an EM algorithm to reduce false positive calls while preserving true positives; Magnet is a whole-genome read-mapping-based method that provides detailed presence and absence calls for bacterial genomes. We demonstrate that Lemur and Magnet can run in minutes to hours on a laptop with 32 GB of RAM, even for large inputs, a crucial feature given the portability of long-read sequencing machines. Furthermore, the marker gene database used by Lemur is only 4 GB and contains information from over 300,000 RefSeq genomes. Lemur and Magnet are open-source and available at https://github.com/treangenlab/lemur and https://github.com/treangenlab/magnet.

Identifiers

PMID38895276
PMCPMC11185576

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Registered trials

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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.