Evidence map›Paper›PMID 31167636›Full record

ArticleBMC genomics2019

RiboStreamR: a web application for quality control, analysis, and visualization of Ribo-seq data.

Patrick Perkins, Serina Mazzoni-Putman, Anna Stepanova, Jose Alonso, Steffen Heber

Abstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Peptidomics Methods Applied to the Study of Flower Development.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  6. Article
  7. Article
  8. Experimental Validation of the Noncoding Potential for lncRNAs.Methods in molecular biology (Clifton, N.J.) · 2021
    Review
  9. Article
  10. Article
  11. 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

5 authors.

Patrick PerkinsBioinformatics Research Center, North Carolina State University, Raleigh, NC, 27607, USA.
Serina Mazzoni-PutmanDepartment of Plant and Microbial Biology, North Carolina State University, Raleigh, NC, 27607, USA.
Anna StepanovaDepartment of Plant and Microbial Biology, North Carolina State University, Raleigh, NC, 27607, USA.
Jose AlonsoDepartment of Plant and Microbial Biology, North Carolina State University, Raleigh, NC, 27607, USA.
Steffen HeberBioinformatics Research Center, North Carolina State University, Raleigh, NC, 27607, USA. sheber@ncsu.edu.

Funding

GRADUATE TRAINING IN BIOINFORMATICST32ES007329 · NIEHS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Fred A. Wright · 2000 to 2026
$6.8M
NIEHS NIH HHS T32 ES007329
6 · The paper itself

Abstract

backgroundRibo-seq is a popular technique for studying translation and its regulation. A Ribo-seq experiment produces a snap-shot of the location and abundance of actively translating ribosomes within a cell's transcriptome. In practice, Ribo-seq data analysis can be sensitive to quality issues such as read length variation, low read periodicities, and contaminations with ribosomal and transfer RNA. Various software tools for data preprocessing, quality assessment, analysis, and visualization of Ribo-seq data have been developed. However, many of these tools require considerable practical knowledge of software applications, and often multiple different tools have to be used in combination with each other.

resultsWe present riboStreamR, a comprehensive Ribo-seq quality control (QC) platform in the form of an R Shiny web application. RiboStreamR provides visualization and analysis tools for various Ribo-seq QC metrics, including read length distribution, read periodicity, and translational efficiency. Our platform is focused on providing a user-friendly experience, and includes various options for graphical customization, report generation, and anomaly detection within Ribo-seq datasets.

conclusionsRiboStreamR takes advantage of the vast resources provided by the R and Bioconductor environments, and utilizes the Shiny R package to ensure a high level of usability. Our goal is to develop a tool which facilitates in-depth quality assessment of Ribo-seq data by providing reference datasets and automatically highlighting quality issues and anomalies within datasets.

Indexed as

SoftwareWeb BrowserComputer GraphicsGenomicsHigh-Throughput Nucleotide SequencingHumansProtein BiosynthesisQuality ControlRibosomesRNA, MessengerSequence Analysis, RNATranscriptomeRNA, MessengerData analysisNext-generation sequencingRibo-seqWeb application

Identifiers

PMID31167636
PMCPMC6551240

What OpenQuestion 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 OpenQuestion graph.