ArticleNucleic acids research2014
SigFuge: single gene clustering of RNA-seq reveals differential isoform usage among cancer samples.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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.
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Who cites it
11 citing papers in PubMed, 23 citations in OpenAlex.
- The offonome reveals on and off states of gene expression near the detection limit of RNA-seq.Scientific reports · 2025Article
- FAM64A contributes to ovarian cancer proliferation and metastasis by suppressing TWIST1 ubiquitination and degradation.Endocrine-related cancer · 2025Article
- CRTC1/MAML2 directs a PGC-1α-IGF-1 circuit that confers vulnerability to PPARγ inhibition.Cell reports · 2021Article
- Integrative Analysis of miRNAs Identifies Clinically Relevant Epithelial and Stromal Subtypes of Head and Neck Squamous Cell Carcinoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2021Article
- SCISSOR: a framework for identifying structural changes in RNA transcripts.Nature communications · 2021Article
- Aberrant FAM64A mRNA expression is an independent predictor of poor survival in pancreatic cancer.PloS one · 2019Article
- TAPAS: tool for alternative polyadenylation site analysis.Bioinformatics (Oxford, England) · 2018Article
- Gene Regulatory Network Perturbation by Genetic and Epigenetic Variation.Trends in biochemical sciences · 2018Review
- A survey of high dimension low sample size asymptotics.Australian & New Zealand journal of statistics · 2018Article
- The impact of the Cancer Genome Atlas on lung cancer.Translational research : the journal of laboratory and clinical medicine · 2015Review
- PIMREG, a Marker of Proliferation, Facilitates Aggressive Development of Cholangiocarcinoma Cells Partly Through Regulating Cell Cycle-Related Markers.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
High-throughput sequencing technologies, including RNA-seq, have made it possible to move beyond gene expression analysis to study transcriptional events including alternative splicing and gene fusions. Furthermore, recent studies in cancer have suggested the importance of identifying transcriptionally altered loci as biomarkers for improved prognosis and therapy. While many statistical methods have been proposed for identifying novel transcriptional events with RNA-seq, nearly all rely on contrasting known classes of samples, such as tumor and normal. Few tools exist for the unsupervised discovery of such events without class labels. In this paper, we present SigFuge for identifying genomic loci exhibiting differential transcription patterns across many RNA-seq samples. SigFuge combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. We apply SigFuge to RNA-seq cohorts of 177 lung and 279 head and neck squamous cell carcinoma samples from the Cancer Genome Atlas, and identify several cases of differential isoform usage including CDKN2A, a tumor suppressor gene known to be inactivated in a majority of lung squamous cell tumors. By not restricting attention to known sample stratifications, SigFuge offers a novel approach to unsupervised screening of genetic loci across RNA-seq cohorts. SigFuge is available as an R package through Bioconductor.
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Registered trials
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.