Evidence map›Paper›PMID 41572167›Full record

ArticleBMC bioinformatics2026

QuAPPro: an R shiny app for quantification and alignment of polysome profiles.

Chiara Schiller, Matthias Lemmer, Sonja Reitter, Janina A Lehmann, Kai Fenzl, Johanna Schott

Abstract read
In one paragraph

Article in BMC bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Polysome Profiling Method for Low-Input Human Postmortem Brain.bioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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.

Chiara SchillerMannheim Institute for Innate Immunoscience (MI3) and Mannheim Cancer Center (MCC), Medical Faculty Mannheim, Heidelberg University, Franz-Volhard-Str. 6, 68167, Mannheim, Germany.
Matthias LemmerMannheim Institute for Innate Immunoscience (MI3) and Mannheim Cancer Center (MCC), Medical Faculty Mannheim, Heidelberg University, Franz-Volhard-Str. 6, 68167, Mannheim, Germany.
Sonja ReitterMannheim Institute for Innate Immunoscience (MI3) and Mannheim Cancer Center (MCC), Medical Faculty Mannheim, Heidelberg University, Franz-Volhard-Str. 6, 68167, Mannheim, Germany.
Janina A LehmannMannheim Institute for Innate Immunoscience (MI3) and Mannheim Cancer Center (MCC), Medical Faculty Mannheim, Heidelberg University, Franz-Volhard-Str. 6, 68167, Mannheim, Germany.
Kai FenzlCenter for Molecular Biology of Heidelberg University (ZMBH) and German Cancer Research Center (DKFZ), DKFZ-ZMBH Alliance, Im Neuenheimer Feld 329, 69120, Heidelberg, Germany.
Johanna SchottMannheim Institute for Innate Immunoscience (MI3) and Mannheim Cancer Center (MCC), Medical Faculty Mannheim, Heidelberg University, Franz-Volhard-Str. 6, 68167, Mannheim, Germany. johanna.schott@medma.uni-heidelberg.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPolysome profiling is a widespread technique to study mRNA translation. After separation of cellular particles by ultracentrifugation on a sucrose-density gradient, a UV absorbance profile is recorded during elution, which mostly reflects RNA content and shows distinct peaks for ribosomal subunits, monosomes and polysomes with increasing number of ribosomes. This profile can be used to assess global translational activity, or to reveal changes in ribosome biogenesis and translation elongation. In addition, it is also possible to measure the association of fluorescently tagged proteins with ribosomal subunits or polysomes. Alignment and quantification of polysome profiles usually relies on spreadsheet programs, custom R/Python scripts or commercial software.

resultsWith QuAPPro, we present the first interactive web app that allows quantification and alignment of polysome profiles, independently of the device or software that was used to generate the profiles. QuAPPro was written in R, with a graphical user interface implemented in R shiny. It supports interactive visualization and analysis of polysome profiles, including profile smoothing, baseline selection, alignment along a defined point on the x-axis, quantification of profile subsections and deconvolution for resolving individual peaks. Fluorescence profiles can be aligned and quantified in parallel. Finally, quantification results can be summarized and visualized as bar plots. Every interactive plot can be exported directly in a publication-ready format.

conclusionsThis user-friendly tool does not only speed up the analysis of polysome profiles but also facilitates reproducibility and documentation of the process, without the need for programming abilities or commercial software.

Indexed as

PolyribosomesSoftwareProtein BiosynthesisRibosome ProfilingRNA, MessengerRNA, MessengerPolysome profilingPolysomesProtein biosynthesisR shinyTranslation

Identifiers

PMID41572167
PMCPMC12849056

What Socratic holds

Textmetadata
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 Socratic graph.