Evidence map›Paper›PMID 34031440›Full record

ArticleScientific reports2021

Improved methods for RNAseq-based alternative splicing analysis.

Rebecca F Halperin, Apurva Hegde, Jessica D Lang, Elizabeth A Raupach, C4RCD Research Group, Christophe Legendre, Winnie S Liang, Patricia M LoRusso, Aleksandar Sekulic, Jeffrey A Sosman and 4 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.6field-weighted citation impact, top 9% 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

30 citing papers in PubMed, 43 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Article
  16. Short-Read RNA-Seq.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  17. Article
  18. Article
  19. Article
  20. 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

14 authors at 4 institutions in 1 country.

Rebecca F HalperinQuantitative Medicine and Systems Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA. rhalperin@tgen.org.
Apurva HegdeCollaborative Center for Translational Mass Spectrometry, Translational Genomics Research Institute, Phoenix, AZ, USA.
Jessica D LangIntegrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA.
Elizabeth A RaupachIntegrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA.
C4RCD Research Group
Christophe LegendreIntegrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA.
Winnie S LiangIntegrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA.
Patricia M LoRussoYale Cancer Center, New Haven, CT, USA.
Aleksandar SekulicMayo Clinic, Scottsdale, AZ, USA.
Jeffrey A SosmanNorthwestern Medicine, Chicago, IL, USA.
Jeffrey M TrentIntegrated Cancer Genomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA.
Sampathkumar RangasamyNeurogenomics Division, Translational Genomics Research Institute, Phoenix, AZ, USA.
Patrick Pirrotte *Collaborative Center for Translational Mass Spectrometry, Translational Genomics Research Institute, Phoenix, AZ, USA.
Nicholas J Schork *Quantitative Medicine and Systems Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA.
Translational Genomics Research Institute · USMayo Clinic in Arizona · USNorthwestern Medicine · USYale Cancer Center · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Systems BiologyU19AG023122 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI Thomas Girke, NICHOLAS Joseph SCHORK · 2004 to 2026
$102.6M
Transgenic Mouse FacilityP30CA033572 · NCI · CITY OF HOPE/BECKMAN RESEARCH INSTITUTE · PI XIWEI WU · 1985 to 2026
$86.3M
Integrative Resource to Develop Translational Strategies to Promote LongevityU24AG051129 · NIA · CALIFORNIA PACIFIC MED CTR RES INSTITUTE · PI CUMMINGS, STEVEN RON, EVANS, DANIEL SPENCER · 2015 to 2019
$5.3M
The Tumor Suppressor Role of SMARCA4 in SCCOHTR01CA195670 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HUNTSMAN, DAVID, TRENT, JEFFREY M. · 2015 to 2019
$3.7M
Integrative Omics to enhance therapeutics development for healthy agingUH3AG064706 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI MILLER, RICHARD A, SCHORK, NICHOLAS JOSEPH · 2021 to 2024
$3.3M
Integrative Omics to enhance therapeutics development for healthy agingUH2AG064706 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI EVANS, DANIEL SPENCER, MILLER, RICHARD A · 2019 to 2020
$1.4M
Translocations/genes in Premature Ovarian FailureZ01AG000647 · NIA · NATIONAL INSTITUTE ON AGING · PI SCHLESSINGER, DAVID · 1998 to 2008
$1.2M
Intramural NIH HHS Z01 AG000647NCATS NIH HHS UL1 TR001863NCI NIH HHS P30 CA033572NCI NIH HHS P30CA033572NIA NIH HHS U19 AG023122NIA NIH HHS U24 AG051129NIA NIH HHS UH2 AG064706NIA NIH HHS UH3 AG064706NIH HHS R01 CA195670NIH HHS U19 AG023122NIH HHS U24 AG051129NIH HHS U24 AG051129-04S1NIH HHS UH2 AG0647
6 · The paper itself

Abstract

The robust detection of disease-associated splice events from RNAseq data is challenging due to the potential confounding effect of gene expression levels and the often limited number of patients with relevant RNAseq data. Here we present a novel statistical approach to splicing outlier detection and differential splicing analysis. Our approach tests for differences in the percentages of sequence reads representing local splice events. We describe a software package called Bisbee which can predict the protein-level effect of splice alterations, a key feature lacking in many other splicing analysis resources. We leverage Bisbee's prediction of protein level effects as a benchmark of its capabilities using matched sets of RNAseq and mass spectrometry data from normal tissues. Bisbee exhibits improved sensitivity and specificity over existing approaches and can be used to identify tissue-specific splice variants whose protein-level expression can be confirmed by mass spectrometry. We also applied Bisbee to assess evidence for a pathogenic splicing variant contributing to a rare disease and to identify tumor-specific splice isoforms associated with an oncogenic mutation. Bisbee was able to rediscover previously validated results in both of these cases and also identify common tumor-associated splice isoforms replicated in two independent melanoma datasets.

Indexed as

Alternative SplicingComputational BiologyGene Expression ProfilingHumansMass SpectrometryMelanomaMutationOrgan SpecificityProto-Oncogene ProteinsSequence Analysis, RNASoftwareProto-Oncogene Proteins

Identifiers

PMID34031440
PMCPMC8144374
OpenAlexW3164944277

What OpenQuestion 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 OpenQuestion graph.