ArticleBMC genomics2020
A large-scale comparative study of isoform expressions measured on four platforms.
Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 14 citations in OpenAlex.
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- On the predictability of progression-free survival in ovarian cancer from NanoString gene expression data.bioRxiv : the preprint server for biology · 2026Article
- Comparison of real-time PCR and nCounter NanoString techniques to validate copy number alterations in oral cancer.Scientific reports · 2025Article
- Transcriptomics of Anterior Shoulder Instability: Differences in Gene Expression in the Blood of Patients With and Without Significant Glenoid Bone Loss.Orthopaedic journal of sports medicine · 2025Article
- Assessing concordance between RNA-Seq and NanoString technologies in Ebola-infected nonhuman primates using machine learning.BMC genomics · 2025Article
- A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines.Nature methods · 2025Article
- Strong correlation of gene counts and differentially expressed genes between a 3' RNA-Seq and an RNA hybridization platform in transcriptome analyses from canine archival tissues.Frontiers in veterinary science · 2025Article
- TrAnnoScope: A Modular Snakemake Pipeline for Full-Length Transcriptome Analysis and Functional Annotation.Genes · 2024Article
- Characterizing the tumor immune microenvironment of ependymomas using targeted gene expression profiles and RNA sequencing.Cancer immunology, immunotherapy : CII · 2023Article
- Multiplexed mRNA analysis of brain-derived extracellular vesicles upon experimental stroke in mice reveals increased mRNA content with potential relevance to inflammation and recovery processes.Cellular and molecular life sciences : CMLS · 2022Article
- Reduced expression of innate immunity-related genes in lymph node metastases of luminal breast cancer patients.Scientific reports · 2021Article
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Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundMost eukaryotic genes produce different transcripts of multiple isoforms by inclusion or exclusion of particular exons. The isoforms of a gene often play diverse functional roles, and thus it is necessary to accurately measure isoform expressions as well as gene expressions. While previous studies have demonstrated the strong agreement between mRNA sequencing (RNA-seq) and array-based gene and/or isoform quantification platforms (Microarray gene expression and Exon-array), the more recently developed NanoString platform has not been systematically evaluated and compared, especially in large-scale studies across different cancer domains.
resultsIn this paper, we present a large-scale comparative study among RNA-seq, NanoString, array-based, and RT-qPCR platforms using 46 cancer cell lines across different cancer types. The goal is to understand and evaluate the calibers of the platforms for measuring gene and isoform expressions in cancer studies. We first performed NanoString experiments on 59 cancer cell lines with 404 custom-designed probes for measuring the expressions of 478 isoforms in 155 genes, and additional RT-qPCR experiments for a subset of the measured isoforms in 13 cell lines. We then combined the data with the matched RNA-seq, Exon-array, and Microarray data of 46 of the 59 cell lines for the comparative analysis.
conclusionIn the comparisons of the platforms for measuring the expressions at both isoform and gene levels, we found that (1) the agreement on isoform expressions is lower than the agreement on gene expressions across the four platforms; (2) NanoString and Exon-array are not consistent on isoform quantification even though both techniques are based on hybridization reactions; (3) RT-qPCR experiments are more consistent with RNA-seq and Exon-array than NanoString in isoform quantification; (4) different RNA-seq isoform quantification methods show varying estimation results, and among the methods, Net-RSTQ and eXpress are more consistent across the platforms; and (5) RNA-seq has the best overall consistency with the other platforms on gene expression quantification.
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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.