Evidence map›Paper›PMID 41301479›Full record

ArticleBiomolecules2025

SMAnalyst: A Web Server for Spatial Metabolomic Data Analysis and Annotation.

Zhanlong Mei, Xiaolian Ning, Haoke Deng, Lingyun Chen, Yun Zhao, Jin Zi

Abstract read
In one paragraph

Article in Biomolecules, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Zhanlong MeiBGI Genomics, Shenzhen 518083, China.ORCID 0000-0003-2203-2495
Xiaolian NingBGI Research, Shenzhen 518083, China.
Haoke DengBGI Genomics, Shenzhen 518083, China.
Lingyun ChenBGI Research, Shenzhen 518083, China.
Yun ZhaoBGI Genomics, Shenzhen 518083, China.
Jin ZiBGI Genomics, Shenzhen 518083, China.

Funding

the National Key R&D Program of China 2021YFA0805100the Sustainable Development Program of Shenzhen Science and Technology Major Program KCXFZ20240903093925033
6 · The paper itself

Abstract

Spatial metabolomics is a rapidly advancing field offering powerful insights into metabolic heterogeneity in biological tissues. However, its widespread adoption is hindered by fragmented tools and the lack of comprehensive, open-source GUI software covering the full analytical workflow (quality control, preprocessing, identification, pattern, and differential analysis). To address this, we developed SMAnalyst, an open-source, integrated web-based platform. SMAnalyst consolidates core functionalities, including multi-dimensional data quality assessment (background consistency, intensity, missing values), a comprehensive metabolite annotation scoring system (mass accuracy, isotopic similarity, adduct evidence), and dual-dimension spatial pattern discovery (metabolite co-expression and pixel clustering). It also offers flexible differential analysis (cluster- or user-defined regions). With its intuitive GUI and modular workflow, SMAnalyst significantly lowers the analysis barrier, by providing a unified solution that eliminates the need for tool switching and advanced computational skills. Tested with a mouse brain dataset, SMAnalyst efficiently handles large-scale data (e.g., >14,000 pixels, >3000 ion peaks), effectively filling a critical gap in integrated analytical solutions for spatial metabolomics.

Indexed as

MetabolomicsSoftwareAnimalsBrainData AnalysisInternetMiceWorkflowdifferential analysismetabolite annotationquality controlspatial metabolomicsspatial pattern discoveryweb-based platform

Identifiers

PMID41301479
PMCPMC12650421

What OpenQuestion holds

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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.