Evidence map›Paper›PMID 25632406›Full record

Article2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics : ACM - BCB 2013 : Washington, D.C., U.S.A., September 22 - 25, 2013. ACM Conference on Bioinformatics, Computational Biology and Biomedical Informa...2013

An Island-Based Approach for Differential Expression Analysis.

Abdallah M Eteleeb, Robert M Flight, Benjamin J Harrison, Jeffrey C Petruska, Eric C Rouchka

Abstract read
In one paragraph

Article in 2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics : ACM - BCB 2013 : Washington, D.C., U.S.A., September 22 - 25, 2013. ACM Conference on Bioinformatics, Computational Biology and Biomedical Informa..., 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. A Comparison of Combined P-value Methods for Gene Differential Expression Using RNA-Seq Data.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2014
    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

5 authors.

Abdallah M EteleebDepartment of Computer, Engineering and Computer, Science, University of Louisville, Louisville, KY, USA, ametel01@louisville.edu.
Robert M FlightDepartment of Chemistry, University of Louisville, Louisville, KY, USA, robert.flight@louisville.edu.
Benjamin J HarrisonDepartment of Anatomical, Sciences and Neurobiology, University of Louisville, Louisville, KY, USA, b.harrison@louisville.edu.
Jeffrey C PetruskaDepartment of Anatomical, Sciences and Neurobiology, University of Louisville, Louisville, KY, USA, j.petruska@louisville.edu.
Eric C RouchkaDepartment of Computer, Engineering and Computer, Science, University of Louisville, Louisville, KY, USA, eric.rouchka@louisville.edu.

Funding

WKU Lead Faculty AwardP20GM103436 · NIGMS · UNIVERSITY OF LOUISVILLE · PI ERIC C ROUCHKA · 2012 to 2026
$60.1M
ZEBRAFISH VISUAL FUNCTION RECOVERY FOLLOWING OPTIC NERVE DAMAGEP20RR016481 · NCRR · UNIVERSITY OF LOUISVILLE · PI BARTON, HAZEL A · 2001 to 2011
$34.8M
Novel transgenic mice for tracing and electrophysiology of stressed neuronsR21NS080091 · NINDS · UNIVERSITY OF LOUISVILLE · PI HAI, TSONWIN, PETRUSKA, JEFFREY C · 2012 to 2014
$451k
NCRR NIH HHS P20 RR016481NIGMS NIH HHS P20 GM103436NINDS NIH HHS R21 NS080091
6 · The paper itself

Abstract

High-throughput mRNA sequencing (also known as RNA-Seq) promises to be the technique of choice for studying transcriptome profiles. This technique provides the ability to develop precise methodologies for transcript and gene expression quantification, novel transcript and exon discovery, and splice variant detection. One of the limitations of current RNA-Seq methods is the dependency on annotated biological features (e.g. exons, transcripts, genes) to detect expression differences across samples. This forces the identification of expression levels and the detection of significant changes to known genomic regions. Any significant changes that occur in unannotated regions will not be captured. To overcome this limitation, we developed a novel segmentation approach, Island-Based (IB), for analyzing differential expression in RNA-Seq and targeted sequencing (exome capture) data without specific knowledge of an isoform. The IB segmentation determines individual islands of expression based on windowed read counts that can be compared across experimental conditions to determine differential island expression. In order to detect differentially expressed genes, the significance of islands (

Indexed as

Alternative SplicingDifferential ExpressionRNA-Seq

Identifiers

PMID25632406
PMCPMC4306332

What OpenQuestion holds

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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.