Evidence map›Paper›PMID 34686194›Full record

ArticleGenome biology2021

MINTIE: identifying novel structural and splice variants in transcriptomes using RNA-seq data.

Marek Cmero, Breon Schmidt, Ian J Majewski, Paul G Ekert, Alicia Oshlack, Nadia M Davidson

Abstract readEvaluation Study
In one paragraph

Article in Genome biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Benchmarking RNA-seq Tools for Real-World Diagnostic Applications.medRxiv : the preprint server for health sciences · 2026
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  12. Review
  13. Toward transcriptomics as a primary tool for rare disease investigation.Cold Spring Harbor molecular case studies · 2022
    Article
  14. Article
  15. Article
  16. 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.

Marek CmeroPeter MacCallum Cancer Centre, Melbourne, VIC, Australia.
Breon SchmidtPeter MacCallum Cancer Centre, Melbourne, VIC, Australia.
Ian J MajewskiWalter and Eliza Hall Institute, Parkville, Australia.
Paul G EkertPeter MacCallum Cancer Centre, Melbourne, VIC, Australia.
Alicia OshlackPeter MacCallum Cancer Centre, Melbourne, VIC, Australia. Alicia.Oshlack@petermac.org.ORCID 0000-0001-9788-5690
Nadia M DavidsonPeter MacCallum Cancer Centre, Melbourne, VIC, Australia. nadia.davidson@petermac.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Calling fusion genes from RNA-seq data is well established, but other transcriptional variants are difficult to detect using existing approaches. To identify all types of variants in transcriptomes we developed MINTIE, an integrated pipeline for RNA-seq data. We take a reference-free approach, combining de novo assembly of transcripts with differential expression analysis to identify up-regulated novel variants in a case sample. We compare MINTIE with eight other approaches, detecting > 85% of variants while no other method is able to achieve this. We posit that MINTIE will be able to identify new disease variants across a range of disease types.

Indexed as

RNA-SeqRNA SplicingSoftwareTranscriptomeAlgorithmsGenetic VariationHumansPrecursor B-Cell Lymphoblastic Leukemia-LymphomaRare Diseases

Identifiers

PMID34686194
PMCPMC8532352

What OpenQuestion holds

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Registered trials

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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.