Evidence map›Paper›PMID 38508189›Full record

ArticleCell reports methods2024

Detecting differential transcript usage in complex diseases with SPIT.

Beril Erdogdu, Ales Varabyou, Stephanie C Hicks, Steven L Salzberg, Mihaela Pertea

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Comprehensive Transcriptome Annotation of Thousands of HIV-1 Genomes.bioRxiv : the preprint server for biology · 2025
    Article
  4. Isoswitching drives the aging process in human brains.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Beril ErdogduCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA. Electronic address: berdogd1@jhu.edu.
Ales VarabyouCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Stephanie C HicksCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA.
Steven L SalzbergCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Mihaela PerteaCenter for Computational Biology, Johns Hopkins University, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins School of Medicine and Whiting School of Engineering, Baltimore, MD, USA; Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA; Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA. Electronic address: elapertea@gmail.com.

Funding

Computational Methods for Genome Assembly, Transcript Assembly, and Variant DiscoveryR01HG006677 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI SALZBERG, STEVEN L. · 2011 to 2025
$10.7M
Comprehensive Human Expressed Sequences in Brain (CHESS-BRAIN) and their roles in neuropsychiatric illnessR01MH123567 · NIMH · JOHNS HOPKINS UNIVERSITY · PI SALZBERG, STEVEN L. · 2021 to 2025
$2.8M
NHGRI NIH HHS R01 HG006677NIMH NIH HHS R01 MH123567
6 · The paper itself

Abstract

Differential transcript usage (DTU) plays a crucial role in determining how gene expression differs among cells, tissues, and developmental stages, contributing to the complexity and diversity of biological systems. In abnormal cells, it can also lead to deficiencies in protein function and underpin disease pathogenesis. Analyzing DTU via RNA sequencing (RNA-seq) data is vital, but the genetic heterogeneity in populations with complex diseases presents an intricate challenge due to diverse causal events and undetermined subtypes. Although the majority of common diseases in humans are categorized as complex, state-of-the-art DTU analysis methods often overlook this heterogeneity in their models. We therefore developed SPIT, a statistical tool that identifies predominant subgroups in transcript usage within a population along with their distinctive sets of DTU events. This study provides comprehensive assessments of SPIT's methodology and applies it to analyze brain samples from individuals with schizophrenia, revealing previously unreported DTU events in six candidate genes.

Indexed as

Gene Expression ProfilingRNAHumansSequence Analysis, RNARNAalternative splicingcomplex diseasesCP: systems biologyDTUheterogeneityRNA-seqschizophrenia

Identifiers

PMID38508189
PMCPMC10985272

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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.