Evidence map›Paper›PMID 30231853›Full record

ArticleBMC plant biology2018

AgriSeqDB: an online RNA-Seq database for functional studies of agriculturally relevant plant species.

Andrew J Robinson, Muluneh Tamiru, Rachel Salby, Clayton Bolitho, Andrew Williams, Simon Huggard, Eva Fisch, Kathryn Unsworth, James Whelan, Mathew G Lewsey

Abstract read
In one paragraph

Article in BMC plant biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. TheJournal of fungi (Basel, Switzerland) · 2023
    Article
  3. LMTFrontiers in plant science · 2023
    Article
  4. Review
  5. Article
  6. Article
  7. 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

10 authors.

Andrew J RobinsonGenomics Platform, La Trobe University, Melbourne, Australia.
Muluneh TamiruDepartment of Animal, Plant and Soil Sciences, School of Life Sciences, La Trobe University, Melbourne, Australia.
Rachel SalbyLibrary, La Trobe University, Melbourne, Australia.
Clayton BolithoLibrary, La Trobe University, Melbourne, Australia.
Andrew WilliamsLibrary, La Trobe University, Melbourne, Australia.
Simon HuggardLibrary, La Trobe University, Melbourne, Australia.
Eva FischLibrary, La Trobe University, Melbourne, Australia.
Kathryn UnsworthAustralian National Data Service, Melbourne, Australia.
James WhelanDepartment of Animal, Plant and Soil Sciences, School of Life Sciences, La Trobe University, Melbourne, Australia.
Mathew G LewseyDepartment of Animal, Plant and Soil Sciences, School of Life Sciences, La Trobe University, Melbourne, Australia. m.lewsey@latrobe.edu.au.ORCID http://orcid.org/0000-0002-2631-4337

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe genome-wide expression profile of genes in different tissues/cell types and developmental stages is a vital component of many functional genomic studies. Transcriptome data obtained by RNA-sequencing (RNA-Seq) is often deposited in public databases that are made available via data portals. Data visualization is one of the first steps in assessment and hypothesis generation. However, these databases do not typically include visualization tools and establishing one is not trivial for users who are not computational experts. This, as well as the various formats in which data is commonly deposited, makes the processes of data access, sharing and utility more difficult. Our goal was to provide a simple and user-friendly repository that meets these needs for data-sets from major agricultural crops. DESCRIPTION: AgriSeqDB ( https://expression.latrobe.edu.au/agriseqdb ) is a database for viewing, analysing and interpreting developmental and tissue/cell-specific transcriptome data from several species, including major agricultural crops such as wheat, rice, maize, barley and tomato. The disparate manner in which public transcriptome data is often warehoused and the challenge of visualizing raw data are both major hurdles to data reuse. The popular eFP browser does an excellent job of presenting transcriptome data in an easily interpretable view, but previous implementation has been mostly on a case-by-case basis. Here we present an integrated visualisation database of transcriptome data-sets from six species that did not previously have public-facing visualisations. We combine the eFP browser, for gene-by-gene investigation, with the Degust browser, which enables visualisation of all transcripts across multiple samples. The two visualisation interfaces launch from the same point, enabling users to easily switch between analysis modes. The tools allow users, even those without bioinformatics expertise, to mine into data-sets and understand the behaviour of transcripts of interest across samples and time. We have also incorporated an additional graphic download option to simplify incorporation into presentations or publications.

conclusionPowered by eFP and Degust browsers, AgriSeqDB is a quick and easy-to-use platform for data analysis and visualization in five crops and Arabidopsis. Furthermore, it provides a tool that makes it easy for researchers to share their data-sets, promoting research collaborations and data-set reuse.

Indexed as

Databases, GeneticRNA, PlantCrops, AgriculturalInternetSequence Analysis, RNATranscriptomeUser-Computer InterfaceRNA, PlantAgricultureBarleyDatabaseGene-expressionMaizeRiceRNA-SeqTomatoTranscriptomicsVisualisationWheat

Identifiers

PMID30231853
PMCPMC6146512

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.