Evidence map›Paper›PMID 27160013›Full record

ArticleBiology direct2016

Estimation of ribosome profiling performance and reproducibility at various levels of resolution.

Alon Diament, Tamir Tuller

Abstract read
In one paragraph

Article in Biology direct, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

  1. Article
  2. Evaluation of Eukaryotic mRNA Coding Potential.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  3. A review of Ribosome profiling and tools used in Ribo-seq data analysis.Computational and structural biotechnology journal · 2024
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Analysis of Ribosome Profiling Data.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. The effects of codon bias and optimality on mRNA and protein regulation.Cellular and molecular life sciences : CMLS · 2021
    Review
  19. Codon-based indices for modeling gene expression and transcript evolution.Computational and structural biotechnology journal · 2021
    Review
  20. 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

2 authors.

Alon DiamentBiomedical Engineering Department, Tel Aviv University, Tel Aviv-Yafo, Israel.
Tamir TullerBiomedical Engineering Department, Tel Aviv University, Tel Aviv-Yafo, Israel. tamirtul@post.tau.ac.il.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRibosome profiling (or Ribo-seq) is currently the most popular methodology for studying translation; it has been employed in recent years to decipher various fundamental gene expression regulation aspects. The main promise of the approach is its ability to detect ribosome densities over an entire transcriptome in high resolution of single codons. Indeed, dozens of ribo-seq studies have included results related to local ribosome densities in different parts of the transcript; nevertheless, the performance of Ribo-seq has yet to be quantitatively evaluated and reported in a large-scale multi-organismal and multi-protocol study of currently available datasets.

resultsHere we provide the first objective evaluation of Ribo-seq at the resolution of a single nucleotide(s) using clear, interpretable measures, based on the analysis of 15 experiments, 6 organisms, and a total of 612, 961 transcripts. Our major conclusion is that the ability to infer signals of ribosomal densities at nucleotide scale is considerably lower than previously thought, as signals at this level are not reproduced well in experimental replicates. In addition, we provide various quantitative measures that connect the expected error rate with Ribo-seq analysis resolution.

conclusionsThe analysis of Ribo-seq data at the resolution of codons and nucleotides provides a challenging task, calls for task-specific statistical methods and further protocol improvements. We believe that our results are important for every researcher studying translation and specifically for researchers analyzing data generated by the Ribo-seq approach. REVIEWERS: This article was reviewed by Dmitrij Frishman, Eugene Koonin and Frank Eisenhaber.

Indexed as

TranscriptomeHigh-Throughput Nucleotide SequencingReproducibility of ResultsRibosomesmRNA translationNext generation sequencingRibosome profiling

Identifiers

PMID27160013
PMCPMC4862193

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Registered trials

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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.