ArticleBiostatistics (Oxford, England)2017
Clustering of mRNA-Seq data based on alternative splicing patterns.
Article in Biostatistics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
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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
3 citing papers in PubMed.
- ACTOR: a latent Dirichlet model to compare expressed isoform proportions to a reference panel.Biostatistics (Oxford, England) · 2023Article
- Profiling Cell Type Abundance and Expression in Bulk Tissues with CIBERSORTx.Methods in molecular biology (Clifton, N.J.) · 2020Article
- A Single-Subject Method to Detect Pathways Enriched With Alternatively Spliced Genes.Frontiers in genetics · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Sequencing of messenger RNA (mRNA) can provide estimates of the levels of individual isoforms within the cell. It remains to adapt many standard statistical methods commonly used for analyzing gene expression levels to take advantage of this additional information. One novel question is whether we can find clusters of samples that are distinguished not by their gene expression but by their isoform usage. We propose a novel approach for clustering mRNA-Seq data that identifies such clusters. We show via simulation that our methods are more sensitive to finding clusters based on isoform usage than standard clustering techniques. We demonstrate its performance by finding a technical artifact that resulted in different batches having different isoform usage patterns, and illustrate its usage on several The Cancer Genome Atlas datasets.
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Registered trials
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