ArticleBMC genomics2017
RNA sequencing and transcriptome arrays analyses show opposing results for alternative splicing in patient derived samples.
Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.
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Who cites it
49 citing papers in PubMed, 1 synthesis or guideline pooled it, 91 citations in OpenAlex.
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- Circular RNA-based liquid biopsy: a promising approach for monitoring drug resistance in cancer.Cancer drug resistance (Alhambra, Calif.) · 2025Review
- Geriatric Surgery Produces a Hypoactive Molecular Phenotype in the Monocyte Immune Gene Transcriptome.Journal of clinical medicine · 2023Article
- Transcriptome alterations in peripheral blood B cells of patients with multiple sclerosis receiving immune reconstitution therapy.Journal of neuroinflammation · 2023Article
- Transcriptomics for Clinical and Experimental Biology Research: Hang on a Seq.Advanced genetics (Hoboken, N.J.) · 2023Review
- The problem of selection bias in studies of pre-mRNA splicing.Nature communications · 2023Article
- Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis.Biology · 2022Article
- Comprehensive analysis of gene expression profiles to identify differential prognostic factors of primary and metastatic breast cancer.Saudi journal of biological sciences · 2022Article
- Exploration of the Immunotyping Landscape and Immune Infiltration-Related Prognostic Markers in Ovarian Cancer Patients.Frontiers in oncology · 2022Article
- Exploration of a Novel Prognostic Nomogram and Diagnostic Biomarkers Based on the Activity Variations of Hallmark Gene Sets in Hepatocellular Carcinoma.Frontiers in oncology · 2022Article
- Status of diagnosis and treatment of esophageal cancer and non-coding RNA correlation research: a narrative review.Translational cancer research · 2021Review
- Combining Multiple RNA-Seq Data Analysis Algorithms Using Machine Learning Improves Differential Isoform Expression Analysis.Methods and protocols · 2021Article
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- Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth.Cell reports. Medicine · 2021Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRNA sequencing (RNA-seq) and microarrays are two transcriptomics techniques aimed at the quantification of transcribed genes and their isoforms. Here we compare the latest Affymetrix HTA 2.0 microarray with Illumina 2000 RNA-seq for the analysis of patient samples - normal lung epithelium tissue and squamous cell carcinoma lung tumours. Protein coding mRNAs and long non-coding RNAs (lncRNAs) were included in the study.
resultsBoth platforms performed equally well for protein-coding RNAs, however the stochastic variability was higher for the sequencing data than for microarrays. This reduced the number of differentially expressed genes and genes with predictive potential for RNA-seq compared to microarray data. Analysis of this variability revealed a lack of reads for short and low abundant genes; lncRNAs, being shorter and less abundant RNAs, were found especially susceptible to this issue. A major difference between the two platforms was uncovered by analysis of alternatively spliced genes. Investigation of differential exon abundance showed insufficient reads for many exons and exon junctions in RNA-seq while the detection on the array platform was more stable. Nevertheless, we identified 207 genes which undergo alternative splicing and were consistently detected by both techniques.
conclusionsDespite the fact that the results of gene expression analysis were highly consistent between Human Transcriptome Arrays and RNA-seq platforms, the analysis of alternative splicing produced discordant results. We concluded that modern microarrays can still outperform sequencing for standard analysis of gene expression in terms of reproducibility and cost.
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