Evidence map›Paper›PMID 42207845›Full record

ArticlePLoS computational biology2026

TIPP-SD: A new method for species detection in microbiomes.

Chengze Shen, Eleanor Wedell, Mihai Pop, Tandy Warnow

Abstract read
In one paragraph

Article in PLoS computational biology, 2026. 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

4 authors.

Chengze ShenSiebel School of Computing and Data Science, University of Illinois Urbana-Champaign, Urbana, Illinois, United States of America.ORCID https://orcid.org/0000-0003-2276-9892
Eleanor WedellSiebel School of Computing and Data Science, University of Illinois Urbana-Champaign, Urbana, Illinois, United States of America.
Mihai PopDepartment of Computer Science, University of Maryland at College Park, College Park, Maryland, United States of America.
Tandy WarnowSiebel School of Computing and Data Science, University of Illinois Urbana-Champaign, Urbana, Illinois, United States of America.ORCID https://orcid.org/0000-0001-7717-3514

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we present TIPP-SD (i.e., TIPP for Species Detection), a new technique for species detection in a microbiome sample. TIPP-SD uses a substantially modified version of TIPP3, which is a recently developed abundance profiling tool based on maximum likelihood phylogenetic placement into marker gene taxonomies. TIPP-SD depends on a parameter (i.e., "threshold") for the required support for species detection, thus allowing us to compute a precision-recall curve as we vary this parameter. In comparing the precision-recall curves for TIPP-SD, TIPP3, Kraken2, Bracken, Metabuli, and Metapresence, we find that TIPP-SD improves on the other methods with respect to accuracy under conditions where there is a highly variable distribution of species abundance or where there is sequencing error. Under other conditions, TIPP-SD is close to the best of these methods. Finally, although TIPP-SD is slower than the other methods, it is still fast enough to be used on large datasets. TIPP-SD is available in github as part of the TIPP3 software package.

Indexed as

Computational BiologyMicrobiotaSoftwareAlgorithmsBacteriaPhylogeny

Identifiers

PMID42207845
PMCPMC13229341

What OpenQuestion holds

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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.