Evidence map›Paper›PMID 40940023›Full record

ArticleAnalytical chemistry2025

rtmsEcho: An Open-Source R Package for Automated Analysis of Acoustic Ejection Mass Spectrometry Data.

Mary Ashley Rimmer, Nathaniel Twarog, Tharindu A Ranathunge, Jingheng Wang, Yong Li, Taosheng Chen, Anang A Shelat, Lei Yang

Abstract read
In one paragraph

Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Mary Ashley RimmerAnalytical Technologies Center, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis ,Tennessee 38105, United States.
Nathaniel TwarogLead Discovery Informatics, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.
Tharindu A RanathungeAnalytical Technologies Center, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis ,Tennessee 38105, United States.ORCID 0000-0002-1152-6679
Jingheng WangDepartment of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.
Yong LiAnalytical Technologies Center, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis ,Tennessee 38105, United States.
Taosheng ChenDepartment of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.ORCID 0000-0001-6420-3809
Anang A ShelatLead Discovery Informatics, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, United States.ORCID 0000-0002-6266-2910
Lei YangAnalytical Technologies Center, Department of Chemical Biology and Therapeutics, St. Jude Children's Research Hospital, Memphis ,Tennessee 38105, United States.ORCID 0000-0002-3060-0790

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mass spectrometry (MS) is a well-established technology in biological research, enabling the sensitive and precise quantitative analysis of complex samples. While traditional LC-MS systems provide robust performance for targeted analyses, their reliance on chromatographic separation limits throughput, rendering large-scale studies inefficient. The emergence of Acoustic Ejection Mass Spectrometry (AEMS) has revolutionized high-throughput workflows by eliminating chromatography and enabling direct nanoliter-scale sampling, achieving hundreds to thousands of measurements per hour. However, AEMS's full potential remains constrained by software limitations─existing tools lack robust automated processing capabilities for critical tasks such as peak detection, integration, and multimodal data analysis (e.g., multiple reaction monitoring, precursor ion, and neutral loss scans). To address this gap, we developed rtmsEcho, an open-source R package that extends our previously published rtms framework. This specialized solution provides direct access to AEMS data, enabling customizable processing of both MRM and full-scan acquisitions (precursor ion and neutral loss modes) while automating shot-to-peak association and spectral analysis. By streamlining data extraction and quantification, rtmsEcho enhances efficiency and reproducibility in high-throughput applications, including drug discovery, quality control, and clinical diagnostics. This innovation bridges a critical gap in AEMS data analysis, allowing researchers to fully leverage the speed and precision of next-generation mass spectrometry.

Indexed as

AcousticsMass SpectrometrySoftwareAutomation

Identifiers

PMID40940023
PMCPMC12462762

What OpenQuestion holds

Textmetadata
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.