Evidence map›Paper›PMID 24093729›Full record

ArticleBMC bioinformatics2013

afterParty: turning raw transcriptomes into permanent resources.

Martin Jones, Mark Blaxter

Abstract read
In one paragraph

Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Workflow and web application for annotating NCBI BioProject transcriptome data.Database : the journal of biological databases and curation · 2017
    Article
  3. Article
  4. Review
  5. 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

2 authors.

Martin JonesInstitute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3JT, UK. martin.jones@ed.ac.uk.
Mark Blaxter

Funding

Biotechnology and Biological Sciences Research Council BB/I023585/1Wellcome Trust 095831
6 · The paper itself

Abstract

backgroundNext-generation DNA sequencing technologies have made it possible to generate transcriptome data for novel organisms quickly and cheaply, to the extent that the effort required to annotate and publish a new transcriptome is greater than the effort required to sequence it. Often, following publication, details of the annotation effort are only available in summary form, hindering subsequent exploitation of the data. To promote best-practice in annotation and to ensure that data remain accessible, we have written afterParty, a web application that allows users to assemble, annotate and publish novel transcriptomes using only a web browser.

resultsafterParty is a robust web application that implements best-practice transcriptome assembly, annotation, browsing, searching, and visualization. Users can turn a collection of reads (from Roche 454 chemistry) or assembled contigs (from any sequencing chemistry, including Illumina Solexa RNA-Seq) into a searchable, browsable transcriptome resource and quickly make it publicly available. Contigs are functionally annotated based on similarity to known sequences and protein domains. Once assembled and annotated, transcriptomes derived from multiple species or libraries can be compared and searched. afterParty datasets can either be created using the existing afterParty server, or using local instances that can be built easily using a virtual machine. afterParty includes powerful visualization tools for transcriptome dataset exploration and uses a flexible annotation architecture which will allow additional types of annotation to be added in the future.

conclusionsafterParty's main use case scenario is one in which a working biologist has generated a large volume of transcribed sequence data and wishes to turn it into a useful resource that has some durability. By reducing the effort, bioinformatics skills, and computational resources needed to annotate and publish a transcriptome, afterParty will facilitate the annotation and sharing of sequence data that would otherwise remain unavailable. A typical metazoan transcriptome containing several tens of thousands of contigs can be annotated in a few minutes of interactive time and a few days of computational time.

Indexed as

Computational BiologyDatabases, GeneticInternetMolecular Sequence AnnotationSequence Analysis, DNASoftwareTranscriptome

Identifiers

PMID24093729
PMCPMC3856601

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.