Evidence map›Paper›PMID 31930375›Full record

ArticleBioinformatics (Oxford, England)2020

RiboFlow, RiboR and RiboPy: an ecosystem for analyzing ribosome profiling data at read length resolution.

Hakan Ozadam, Michael Geng, Can Cenik

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Ribosome Molecular Aging Shapes Translation Dynamics.bioRxiv : the preprint server for biology · 2026
    Article
  7. Article
  8. Article
  9. A Versatile Ribo-seq Workflow for Enhanced Analysis of Ribosome Dynamics.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Landscape and regulation of mRNA translation in the earlybioRxiv : the preprint server for biology · 2025
    Article
  17. Article
  18. Article
  19. Article
  20. Long-read RNA sequencing reveals allele-specific NbioRxiv : 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

3 authors.

Hakan OzadamDepartment of Molecular Biosciences, University of Texas at Austin, Austin, TX 78705, USA.
Michael GengDepartment of Molecular Biosciences, University of Texas at Austin, Austin, TX 78705, USA.
Can CenikDepartment of Molecular Biosciences, University of Texas at Austin, Austin, TX 78705, USA.

Funding

Characterization of recurrent cancer mutations that cause misregulated translationR00CA204522 · NCI · UNIVERSITY OF TEXAS AT AUSTIN · PI CENIK, CAN · 2018 to 2020
$747k
Characterization of recurrent cancer mutations that cause misregulated translationK99CA204522 · NCI · STANFORD UNIVERSITY · PI CENIK, CAN · 2016 to 2017
$207k
NCI NIH HHS K99 CA204522NCI NIH HHS R00 CA204522
6 · The paper itself

Abstract

summaryRibosome occupancy measurements enable protein abundance estimation and infer mechanisms of translation. Recent studies have revealed that sequence read lengths in ribosome profiling data are highly variable and carry critical information. Consequently, data analyses require the computation and storage of multiple metrics for a wide range of ribosome footprint lengths. We developed a software ecosystem including a new efficient binary file format named 'ribo'. Ribo files store all essential data grouped by ribosome footprint lengths. Users can assemble ribo files using our RiboFlow pipeline that processes raw ribosomal profiling sequencing data. RiboFlow is highly portable and customizable across a large number of computational environments with built-in capabilities for parallelization. We also developed interfaces for writing and reading ribo files in the R (RiboR) and Python (RiboPy) environments. Using RiboR and RiboPy, users can efficiently access ribosome profiling quality control metrics, generate essential plots and carry out analyses. Altogether, these components create a software ecosystem for researchers to study translation through ribosome profiling. AVAILABILITY AND IMPLEMENTATION: For a quickstart, please see https://ribosomeprofiling.github.io. Source code, installation instructions and links to documentation are available on GitHub: https://github.com/ribosomeprofiling. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

EcosystemRibosomesProteinsSequence AnalysisSoftwareProteins

Identifiers

PMID31930375
PMCPMC7203755

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.