ArticleBioinformatics (Oxford, England)2018
DIEGO: detection of differential alternative splicing using Aitchison's geometry.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Translational Remodeling of the Synaptic Proteome During Aging.Aging cell · 2025Article
- betAS: intuitive analysis and visualization of differential alternative splicing using beta distributions.RNA (New York, N.Y.) · 2024Article
- Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain.Nature genetics · 2023Article
- Using machine learning to detect the differential usage of novel gene isoforms.BMC bioinformatics · 2022Article
- Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma.Nature communications · 2019Article
- psichomics: graphical application for alternative splicing quantification and analysis.Nucleic acids research · 2019Article
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Authors and funding
4 authors.
Funding
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Abstract
Motivation: Alternative splicing is a biological process of fundamental importance in most eukaryotes. It plays a pivotal role in cell differentiation and gene regulation and has been associated with a number of different diseases. The widespread availability of RNA-Sequencing capacities allows an ever closer investigation of differentially expressed isoforms. However, most tools for differential alternative splicing (DAS) analysis do not take split reads, i.e. the most direct evidence for a splice event, into account. Here, we present DIEGO, a compositional data analysis method able to detect DAS between two sets of RNA-Seq samples based on split reads. Results: The python tool DIEGO works without isoform annotations and is fast enough to analyze large experiments while being robust and accurate. We provide python and perl parsers for common formats. Availability and implementation: The software is available at: www.bioinf.uni-leipzig.de/Software/DIEGO. Contact: steve@bioinf.uni-leipzig.de. Supplementary information: Supplementary data are available at Bioinformatics online.
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Registered trials
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