ArticleJournal of mass spectrometry and advances in the clinical lab2022
Data parsing in mass spectrometry imaging using R Studio and Cardinal: A tutorial.
Article in Journal of mass spectrometry and advances in the clinical lab, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Clinical Pathology and the Data Science revolution.Journal of mass spectrometry and advances in the clinical lab · 2022Article
- Identification of the hub genes related to adipose tissue metabolism of bovine.Frontiers in veterinary science · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mass spectrometry imaging (MSI) has emerged as a rapidly expanding field in the MS community. The analysis of large spectral data is further complicated by the added spatial dimension of MSI. A plethora of resources exist for expert users to begin parsing MSI data in R, but there is a critical lack of guidance for absolute beginners. This tutorial is designed to serve as a one-stop guide to start using R with MSI data and describe the possibilities that data science can bring to MSI analysis.
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Registered trials
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.