Evidence map›Paper›PMID 32421805›Full record

ArticleNucleic acids research2020

IRIS3: integrated cell-type-specific regulon inference server from single-cell RNA-Seq.

Anjun Ma, Cankun Wang, Yuzhou Chang, Faith H Brennan, Adam McDermaid, Bingqiang Liu, Chi Zhang, Phillip G Popovich, Qin Ma

Abstract readEvaluation Study
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Androgen conspires with the CD8Science immunology · 2022
    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

9 authors.

Anjun MaDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
Cankun WangDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
Yuzhou ChangDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
Faith H BrennanDepartment of Neuroscience, Center for Brain and Spinal Cord Repair, Belford Center for Spinal Cord Injury, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Adam McDermaidImagenetics, Sanford Health, Sioux Falls, SD 57104, USA.
Bingqiang LiuSchool of Mathematics, Shandong University, Jinan 250100, China.
Chi ZhangDepartment of Medical & Molecular Genetics, Indiana University, School of Medicine, Indianapolis, IN 46202, USA.
Phillip G PopovichDepartment of Neuroscience, Center for Brain and Spinal Cord Repair, Belford Center for Spinal Cord Injury, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Qin MaDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.

Funding

Construction of cell specific gene co-regulations signatures based on single cell transcriptomics analysisR01GM131399 · NIGMS · SOUTH DAKOTA STATE UNIVERSITY · PI MA, QIN · 2018 to 2021
$1.3M
NIGMS NIH HHS R01 GM131399
6 · The paper itself

Abstract

A group of genes controlled as a unit, usually by the same repressor or activator gene, is known as a regulon. The ability to identify active regulons within a specific cell type, i.e., cell-type-specific regulons (CTSR), provides an extraordinary opportunity to pinpoint crucial regulators and target genes responsible for complex diseases. However, the identification of CTSRs from single-cell RNA-Seq (scRNA-Seq) data is computationally challenging. We introduce IRIS3, the first-of-its-kind web server for CTSR inference from scRNA-Seq data for human and mouse. IRIS3 is an easy-to-use server empowered by over 20 functionalities to support comprehensive interpretations and graphical visualizations of identified CTSRs. CTSR data can be used to reliably characterize and distinguish the corresponding cell type from others and can be combined with other computational or experimental analyses for biomedical studies. CTSRs can, therefore, aid in the discovery of major regulatory mechanisms and allow reliable constructions of global transcriptional regulation networks encoded in a specific cell type. The broader impact of IRIS3 includes, but is not limited to, investigation of complex diseases hierarchies and heterogeneity, causal gene regulatory network construction, and drug development. IRIS3 is freely accessible from https://bmbl.bmi.osumc.edu/iris3/ with no login requirement.

Indexed as

RegulonRNA-SeqSingle-Cell AnalysisSoftwareAnimalsBrainCluster AnalysisMice

Identifiers

PMID32421805
PMCPMC7319566

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.