Evidence map›Paper›PMID 36035799›Full record

ArticleSTAR protocols2022

End-to-end pipeline for differential analysis of pausing in ribosome profiling data.

Keegan Flanagan, Wanxin Li, Ethan J Greenblatt, Khanh Dao Duc

Abstract read
In one paragraph

Article in STAR protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

4 authors.

Keegan FlanaganDepartment of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada; Department of Mathematics, University of British Columbia, Vancouver, BC, Canada.
Wanxin LiSchool of Computer Science, University of Waterloo, Waterloo, ON, Canada; Department of Computer Science, University of British Columbia, Vancouver, BC, Canada.
Ethan J GreenblattDepartment of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada. Electronic address: ethan.greenblatt@ubc.ca.
Khanh Dao DucDepartment of Mathematics, University of British Columbia, Vancouver, BC, Canada; Department of Computer Science, University of British Columbia, Vancouver, BC, Canada. Electronic address: kdd@math.ubc.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ribosome profiling is a powerful technique which maps the distribution of ribosomes along mRNAs to analyze translation genome-wide. Ribosome density can be affected by multiple factors, such as changes to translation initiation or elongation rates. We describe the application of a metric for identifying genes rate-limited by these rates by analyzing the relative distribution of ribosome footprints along transcripts. This protocol also details two sample analyses comparing gene translation efficiencies and the distribution of ribosome densities on downloadable datasets. For complete details on the use and execution of this protocol, please refer to Flanagan et al. (2022).

Indexed as

Protein BiosynthesisRibosomesRNA, MessengerRNA, MessengerBioinformaticsGenomicsSequence analysis

Identifiers

PMID36035799
PMCPMC9405084

What Socratic 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 Socratic graph.