Evidence map›Paper›PMID 31624564›Full record

ArticleEcology and evolution2019

The Bellerophon pipeline, improving de novo transcriptomes and removing chimeras.

Jesse Kerkvliet, Arthur de Fouchier, Michiel van Wijk, Astrid Tatjana Groot

Abstract read
In one paragraph

Article in Ecology and evolution, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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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

12 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Sex-basedGigaByte (Hong Kong, China) · 2022
    Article
  9. The Arabinogalactan Protein Family ofPlants (Basel, Switzerland) · 2021
    Article
  10. Article
  11. Article
  12. 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

4 authors.

Jesse KerkvlietInstitute for Biodiversity and Ecosystem Dynamics University of Amsterdam Amsterdam The Netherlands.
Arthur de FouchierInstitute for Biodiversity and Ecosystem Dynamics University of Amsterdam Amsterdam The Netherlands.ORCID https://orcid.org/0000-0003-0673-7380
Michiel van WijkInstitute for Biodiversity and Ecosystem Dynamics University of Amsterdam Amsterdam The Netherlands.
Astrid Tatjana GrootInstitute for Biodiversity and Ecosystem Dynamics University of Amsterdam Amsterdam The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcriptome quality control is an important step in RNA-Seq experiments. However, the quality of de novo assembled transcriptomes is difficult to assess, due to the lack of reference genome to compare the assembly to. We developed a method to assess and improve the quality of de novo assembled transcriptomes by focusing on the removal of chimeric sequences. These chimeric sequences can be the result of faulty assembled contigs, merging two transcripts into one. The developed method is incorporated into a pipeline, which we named Bellerophon, that is broadly applicable and easy to use. Bellerophon first uses the quality assessment tool TransRate to indicate the quality, after which it uses a transcripts per million (TPM) filter to remove lowly expressed contigs and CD-HIT-EST to remove highly identical contigs. To validate the quality of this method, we performed three benchmark experiments: (1) a computational creation of chimeras, (2) identification of chimeric contigs in a transcriptome assembly, (3) a simulated RNA-Seq experiment using a known reference transcriptome. Overall, the Bellerophon pipeline was able to remove between 40% and 91.9% of the chimeras in transcriptome assemblies and removed more chimeric than nonchimeric contigs. Thus, the Bellerophon sequence of filtration steps is a broadly applicable solution to improve transcriptome assemblies.

Indexed as

chimeratranscriptome filteringtranscriptome quality assessment

Identifiers

PMID31624564
PMCPMC6787812

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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.