Evidence map›Paper›PMID 36104797›Full record

ArticleGenome biology2022

Comprehensive and scalable quantification of splicing differences with MntJULiP.

Guangyu Yang, Sarven Sabunciyan, Liliana Florea

Abstract read
PubMed Full text at PMC Publisher
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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

3 authors.

Guangyu YangDepartment of Computer Science, Johns Hopkins University, 733 N Broadway, MRB 462, Baltimore, MD, 21205, USA.
Sarven SabunciyanDepartment of Pediatrics, Johns Hopkins School of Medicine, 600 N Wolfe St, Blalock 1147, Baltimore, MD, 21287, USA.
Liliana FloreaMcKusick-Nathans Department of Genetic Medicine, Johns Hopkins School of Medicine, 733 N Broadway, MRB 453, Baltimore, MD, 21205, USA. florea@jhu.edu.ORCID 0000-0001-8124-2324

Funding

Computational Methods to Characterize Alternative Splicing from Massive Collections of RNA-seq DataR01GM129085 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI FLOREA, LILIANA D · 2019 to 2022
$1.5M
Exonizaton of Alu Insertion PolymorphismsR01GM124531 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI BURNS, KATHLEEN H, FLOREA, LILIANA D · 2017 to 2020
$1.3M
NIGMS NIH HHS R01 GM124531NIGMS NIH HHS R01GM124531NIGMS NIH HHS R01 GM129085
6 · The paper itself

Abstract

Tools for differential splicing detection have failed to provide a comprehensive and consistent view of splicing variation. We present MntJULiP, a novel method for comprehensive and accurate quantification of splicing differences between two or more conditions. MntJULiP detects both changes in intron splicing ratios and changes in absolute splicing levels with high accuracy, and can find classes of variation overlooked by other tools. MntJULiP identifies over 29,000 differentially spliced introns in 1398 GTEx brain samples, including 11,242 novel introns discovered in this dataset. Highly scalable, MntJULiP can process thousands of samples within hours to reveal splicing constituents of phenotypic differentiation.

Indexed as

RNA SplicingIntronsMutationAlternative splicingDifferential splicingRNA-seqTranscriptomics

Identifiers

PMID36104797
PMCPMC9472403

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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.