Evidence map›Paper›PMID 39454023›Full record

ArticleAnalytical chemistry2024

Rapid QC-MS: Interactive Dashboard for Synchronous Mass Spectrometry Data Acquisition Quality Control.

Wasim Sandhu, Ira J Gray, Sarah Lin, Joshua E Elias, Brian C DeFelice

Abstract read
In one paragraph

Article in Analytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. A framework for quality control in quantitative proteomics.bioRxiv : the preprint server for biology · 2024
    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

5 authors.

Wasim SandhuChan Zuckerberg Biohub, San Francisco, California 94158, United States.
Ira J GrayChan Zuckerberg Biohub, San Francisco, California 94158, United States.
Sarah LinChan Zuckerberg Biohub, San Francisco, California 94158, United States.
Joshua E EliasChan Zuckerberg Biohub, San Francisco, California 94158, United States.ORCID 0000-0002-8063-3259
Brian C DeFeliceChan Zuckerberg Biohub, San Francisco, California 94158, United States.ORCID 0000-0001-8243-0300

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Consistently collecting high-quality liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) data is a time-consuming hurdle for untargeted workflows. Analytical controls such as internal and biological standards are commonly included in high-throughput workflows, helping researchers recognize low-integrity specimens regardless of their biological source. However, evaluating these standards as data are collected has remained a considerable bottleneck─in both person-hours and accuracy. Here we present Rapid QC-MS, an automated, interactive dashboard for assessing LC-MS/MS data quality. Minutes after a new data file is written, a browser-viewable dashboard is updated with quality control results spanning multiple performance dimensions such as instrument sensitivity, in-run retention time shifts, and mass accuracy drift. Rapid QC-MS provides interactive visualizations that help users recognize acute deviations in these performance metrics, as well as gradual drifts over periods of hours, days, months, or years. Rapid QC-MS is open-source, simple to install, and highly configurable. By integrating open-source Python libraries and widely used MS analysis software, it can adapt to any LC-MS/MS workflow. Rapid QC-MS runs locally and offers optional remote quality control by syncing with Google Drive. Furthermore, Rapid QC-MS can operate in a semiautonomous fashion, alerting users to specimens with potentially poor analytical integrity via frequently used messaging applications. Initially developed for integration with Thermo Orbitrap workflows, Rapid QC-MS offers a fast, straightforward approach to help users collect high-quality untargeted LC-MS/MS data by eliminating many of the most time-consuming steps in manual data curation. Download for free: https://github.com/czbiohub-sf/Rapid-QC-MS.

Indexed as

Quality ControlSoftwareTandem Mass SpectrometryChromatography, LiquidHumans

Identifiers

PMID39454023
PMCPMC11541893

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.