Evidence map›Paper›PMID 37682468›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Single Cell RNA-Sequencing in Arabidopsis Root Tissues.

Yuji Ke, Max Minne, Thomas Eekhout, Bert De Rybel

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. 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. Single-Cell RNA Sequencing Reveals the Cellular Landscape ofInternational journal of molecular sciences · 2024
    Article
  4. Review
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.

Yuji KeGhent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium.
Max MinneGhent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium.
Thomas EekhoutGhent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium.
Bert De RybelGhent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium. bert.derybel@psb.vib-ugent.be.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Droplet-based single-cell RNA-sequencing (scRNA-seq) empowers transcriptomic profiling with an unprecedented resolution, facilitating insights into the cellular heterogeneity of tissues, developmental progressions, stress-response dynamics, and more at single-cell level. In this chapter, we describe the experimental workflow of processing Arabidopsis root tissue into protoplasts and generating single-cell transcriptomes. We also describe the general computational workflow of visualizing and utilizing scRNA-seq data. This protocol can be used as a starting point for establishing a scRNA-seq workflow.

Indexed as

ArabidopsisDisease ProgressionGene Expression ProfilingHumansProtoplastsRNARNAArabidopsisFACSProtoplastRootscRNA-seqSingle cellTranscriptomics

Identifiers

PMID37682468

What OpenQuestion holds

Textmetadata
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.