Evidence map›Paper›PMID 35605202›Full record

ArticlePlant communications2022

scCloudMine: A cloud-based app for visualization, comparison, and exploration of single-cell transcriptomic data.

Mathew G Lewsey, Changyu Yi, Oliver Berkowitz, Felipe Ayora, Maurice Bernado, James Whelan

Open access · goldAbstract read
In one paragraph

Article in Plant communications, 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
0.4field-weighted citation impact, top 43% of its field
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, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  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

6 authors at 3 institutions in 2 countries.

Mathew G LewseyLa Trobe Institute for Agriculture and Food, La Trobe University, AgriBio Building, Bundoora, VIC 3086, Australia; Australian Research Council Research Hub for Medicinal Agriculture, La Trobe University, AgriBio Building, Bundoora, VIC 3086, Australia.
Changyu YiLa Trobe Institute for Agriculture and Food, La Trobe University, AgriBio Building, Bundoora, VIC 3086, Australia.
Oliver BerkowitzLa Trobe Institute for Agriculture and Food, La Trobe University, AgriBio Building, Bundoora, VIC 3086, Australia; Australian Research Council Research Hub for Medicinal Agriculture, La Trobe University, AgriBio Building, Bundoora, VIC 3086, Australia.
Felipe AyoraBizData, Level 9/278, Collins Street, Melbourne, VIC 3000, Australia; Research and Advanced Computing, BizData, Level 31, 2-6, Gilmer Terrace, Wellington, 6011, New Zealand. Electronic address: felipe.ayora@bizdata.co.nz.
Maurice BernadoBizData, Level 9/278, Collins Street, Melbourne, VIC 3000, Australia.
James WhelanLa Trobe Institute for Agriculture and Food, La Trobe University, AgriBio Building, Bundoora, VIC 3086, Australia; Australian Research Council Research Hub for Medicinal Agriculture, La Trobe University, AgriBio Building, Bundoora, VIC 3086, Australia; Department of Animal, Plant and Soil Sciences, School of Life Science, La Trobe University, Bundoora, VIC 3086, Australia. Electronic address: j.whelan@latrobe.edu.au.
Australian Research Council · AULa Trobe University · AUStatistics New Zealand · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

scCloudMine is a cloud-based application for visualization, comparison, and exploration of single-cell transcriptome data. It does not require an on-site, high-power computing server, installation, or associated expertise and expense. Users upload their own or publicly available scRNA-seq datasets after pre-processing for visualization using a web browser. The data can be viewed in two color modes-Cluster, representing cell identity, and Values, showing levels of expression-and data can be queried using keywords or gene identification number(s). Using the app to compare studies, we determined that some genes frequently used as cell-type markers are in fact study specific. The apparent cell-specific expression of PHO1;H3 differed between GFP-tagging and scRNA-seq studies. Some phosphate transporter genes were induced by protoplasting, but they retained cell specificity, suggesting that cell-specific responses to stress (i.e., protoplasting) can occur. Examination of the cell specificity of hormone response genes revealed that 132 hormone-responsive genes display restricted expression and that the jasmonate response gene TIFY8 is expressed in endodermal cells, in contrast to previous reports. It also appears that JAZ repressors have cell-type-specific functions. These features identified using scCloudMine highlight the need for resources to enable biological researchers to compare their datasets of interest under a variety of parameters. scCloudMine enables researchers to form new hypotheses and perform comparative studies and allows for the easy re-use of data from this emerging technology by a wide variety of users who may not have access or funding for high-performance on-site computing and support.

Indexed as

Mobile ApplicationsTranscriptomeCloud ComputingHormonesSequence Analysis, RNASingle-Cell AnalysisHormonescomparisondiscoveryRNA sequencingsingle cellvisualization

Identifiers

PMID35605202
PMCPMC9284053
OpenAlexW4207008935

What OpenQuestion 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 OpenQuestion graph.