ArticleBMC genomics2018
Comparison of RNA-seq and microarray platforms for splice event detection using a cross-platform algorithm.
Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Effects of High-Dose Ionizing Radiation in Human Gene Expression: A Meta-Analysis.International journal of molecular sciences · 2020Pooled it
- EPBAM: annotation-robust detection of alternative splicing events and a systematic benchmarking of current tools.Briefings in bioinformatics · 2026Article
- Differential Expression Analyses on Human Aortic Tissue Reveal Novel Genes and Pathways Associated With Abdominal Aortic Aneurysm Onset and Progression.Journal of the American Heart Association · 2024Article
- OMICs approaches and technologies for understanding low-high feed efficiency traits in chicken: implication to breeding.Animal biotechnology · 2023Review
- Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq.Advanced genetics (Hoboken, N.J.) · 2023Review
- EventPointer 3.0: flexible and accurate splicing analysis that includes studying the differential usage of protein-domains.NAR genomics and bioinformatics · 2022Article
- Rapid Transient Transcriptional Adaptation to Hypergravity in Jurkat T Cells Revealed by Comparative Analysis of Microarray and RNA-Seq Data.International journal of molecular sciences · 2021Article
- The Study of Alternative Splicing Events in Human Induced Pluripotent Stem Cells From a Down's Syndrome Patient.Frontiers in cell and developmental biology · 2021Article
- Discovery of a transcriptomic core of genes shared in 8 primary retinoblastoma with a novel detection score analysis.Journal of cancer research and clinical oncology · 2020Article
- Article
- Blood transcriptome profiling captures dysregulated pathways and response to treatment in neuroimmunological disease.EBioMedicine · 2019Article
- Integration of CLIP experiments of RNA-binding proteins: a novel approach to predict context-dependent splicing factors from transcriptomic data.BMC genomics · 2019Article
- Circular RNAs and RNA Splice Variants as Biomarkers for Prognosis and Therapeutic Response in the Liquid Biopsies of Lung Cancer Patients.Frontiers in genetics · 2019Review
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundRNA-seq is a reference technology for determining alternative splicing at genome-wide level. Exon arrays remain widely used for the analysis of gene expression, but show poor validation rate with regard to splicing events. Commercial arrays that include probes within exon junctions have been developed in order to overcome this problem. We compare the performance of RNA-seq (Illumina HiSeq) and junction arrays (Affymetrix Human Transcriptome array) for the analysis of transcript splicing events. Three different breast cancer cell lines were treated with CX-4945, a drug that severely affects splicing. To enable a direct comparison of the two platforms, we adapted EventPointer, an algorithm that detects and labels alternative splicing events using junction arrays, to work also on RNA-seq data. Common results and discrepancies between the technologies were validated and/or resolved by over 200 PCR experiments.
resultsAs might be expected, RNA-seq appears superior in cases where the technologies disagree and is able to discover novel splicing events beyond the limitations of physical probe-sets. We observe a high degree of coherence between the two technologies, however, with correlation of EventPointer results over 0.90. Through decimation, the detection power of the junction arrays is equivalent to RNA-seq with up to 60 million reads.
conclusionsOur results suggest, therefore, that exon-junction arrays are a viable alternative to RNA-seq for detection of alternative splicing events when focusing on well-described transcriptional regions.
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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.