Evidence map›Paper›PMID 36369064›Full record

ArticleGenome biology2022

Retained introns in long RNA-seq reads are not reliably detected in sample-matched short reads.

Julianne K David, Sean K Maden, Mary A Wood, Reid F Thompson, Abhinav Nellore

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.9field-weighted citation impact, top 3% of its field
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

22 citing papers in PubMed, 29 citations in OpenAlex.

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  15. RNA in axons, dendrites, synapses and beyond.Frontiers in molecular neuroscience · 2024
    Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. Long-Read Sequencing in Blood Group Genetics.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2023
    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

5 authors at 2 institutions in 1 country.

Julianne K David *Computational Biology Program, Oregon Health & Science University, Portland, OR, USA.
Sean K Maden *Computational Biology Program, Oregon Health & Science University, Portland, OR, USA.
Mary A WoodComputational Biology Program, Oregon Health & Science University, Portland, OR, USA.
Reid F ThompsonComputational Biology Program, Oregon Health & Science University, Portland, OR, USA. thompsre@ohsu.edu.
Abhinav NelloreComputational Biology Program, Oregon Health & Science University, Portland, OR, USA. anellore@gmail.com.ORCID 0000-0001-8145-1484
Oregon Health & Science University · USJohns Hopkins University · US

Funding

CSRD VA IK2 CX002049
6 · The paper itself

Abstract

backgroundThere is growing interest in retained introns in a variety of disease contexts including cancer and aging. Many software tools have been developed to detect retained introns from short RNA-seq reads, but reliable detection is complicated by overlapping genes and transcripts as well as the presence of unprocessed or partially processed RNAs.

resultsWe compared introns detected by 8 tools using short RNA-seq reads with introns observed in long RNA-seq reads from the same biological specimens. We found significant disagreement among tools (Fleiss' [Formula: see text]) such that 47.7% of all detected intron retentions were not called by more than one tool. We also observed poor performance of all tools, with none achieving an F1-score greater than 0.26, and qualitatively different behaviors between general-purpose alternative splicing detection tools and tools confined to retained intron detection.

conclusionsShort-read tools detect intron retention with poor recall and precision, calling into question the completeness and validity of a large percentage of putatively retained introns called by commonly used methods.

Indexed as

Alternative SplicingSoftwareIntronsRNA-SeqSequence Analysis, RNAIntron retentionRNA-seqSplicing

Identifiers

PMID36369064
PMCPMC9652823
OpenAlexW4308764936

What Socratic 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 Socratic graph.