Evidence map›Paper›PMID 29921759›Full record

ArticleToxins2018

Evaluating the Performance of De Novo Assembly Methods for Venom-Gland Transcriptomics.

Matthew L Holding, Mark J Margres, Andrew J Mason, Christopher L Parkinson, Darin R Rokyta

Abstract read
In one paragraph

Article in Toxins, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Article
  2. Review
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  13. Venom phenotype conservation suggests integrated specialization in a lizard-eating snake.Toxicon : official journal of the International Society on Toxinology · 2023
    Article
  14. Article
  15. Article
  16. Review
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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

5 authors.

Matthew L HoldingDepartment of Biological Sciences, Clemson University, Clemson, SC 29634, USA. matthewholding28@gmail.com.
Mark J MargresSchool of Biological Sciences, Washington State University, Pullman, WA 99164, USA. mark.margres@wsu.edu.ORCID 0000-0002-6153-6701
Andrew J MasonDepartment of Biological Sciences, Clemson University, Clemson, SC 29634, USA. ajmason@g.clemson.edu.ORCID 0000-0003-0297-1313
Christopher L ParkinsonDepartment of Biological Sciences, Clemson University, Clemson, SC 29634, USA. viper@clemson.edu.ORCID 0000-0002-2020-6992
Darin R RokytaDepartment of Biological Science, Florida State University, Tallahassee, FL 32306, USA. drokyta@bio.fsu.edu.ORCID 0000-0002-0356-2178

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Venom-gland transcriptomics is a key tool in the study of the evolution, ecology, function, and pharmacology of animal venoms. In particular, gene-expression variation and coding sequences gained through transcriptomics provide key information for explaining functional venom variation over both ecological and evolutionary timescales. The accuracy and usefulness of inferences made through transcriptomics, however, is limited by the accuracy of the transcriptome assembly, which is a bioinformatic problem with several possible solutions. Several methods have been employed to assemble venom-gland transcriptomes, with the Trinity assembler being the most commonly applied among them. Although previous evidence of variation in performance among assembly software exists, particularly regarding recovery of difficult-to-assemble multigene families such as snake venom metalloproteinases, much work to date still employs a single assembly method. We evaluated the performance of several commonly used de novo assembly methods for the recovery of both nontoxin transcripts and complete, high-quality venom-gene transcripts across eleven snake and four scorpion transcriptomes. We varied

Indexed as

Gene Expression ProfilingCrotalid VenomsExocrine GlandsSnake VenomsTranscriptomeCrotalid VenomsSnake Venomsscorpionsnaketranscriptome assemblyvenom-gland transcriptome

Identifiers

PMID29921759
PMCPMC6024825

What OpenQuestion holds

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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.