ArticleBMC genomics2014
Improving reliability and absolute quantification of human brain microarray data by filtering and scaling probes using RNA-Seq.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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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
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
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- Microstructural imaging and transcriptomics of the basal forebrain in first-episode psychosis.Translational psychiatry · 2022Article
- Transcriptome-based polygenic score links depression-related corticolimbic gene expression changes to sex-specific brain morphology and depression risk.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2021Article
- Mapping gene transcription and neurocognition across human neocortex.Nature human behaviour · 2021Article
- Genetic influences on hub connectivity of the human connectome.Nature communications · 2021Observational
- Dynamical consequences of regional heterogeneity in the brain's transcriptional landscape.Science advances · 2021Article
- Downregulation of glial genes involved in synaptic function mitigates Huntington's disease pathogenesis.eLife · 2021Article
- Characterization of Human Genes Modulated byFrontiers in immunology · 2021Article
- Comparison Between Expression Microarrays and RNA-Sequencing Using UKBEC Dataset Identified aFrontiers in neurology and neuroscience research · 2020Article
- Interpretation of differential gene expression results of RNA-seq data: review and integration.Briefings in bioinformatics · 2019Review
- It is time to apply biclustering: a comprehensive review of biclustering applications in biological and biomedical data.Briefings in bioinformatics · 2019Review
- Investigation of optimal pathways for preeclampsia using network-based guilt by association algorithm.Experimental and therapeutic medicine · 2019Article
- Transcriptomic Characterization of the Human Insular Cortex and Claustrum.Frontiers in neuroanatomy · 2019Article
- Transcriptomic characterization of MRI contrast with focus on the T1-w/T2-w ratio in the cerebral cortex.NeuroImage · 2018Article
- An anatomic transcriptional atlas of human glioblastoma.Science (New York, N.Y.) · 2018Article
- Complement Gene Expression Correlates with Superior Frontal Cortical Thickness in Humans.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2018Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundHigh-throughput sequencing is gradually replacing microarrays as the preferred method for studying mRNA expression levels, providing nucleotide resolution and accurately measuring absolute expression levels of almost any transcript, known or novel. However, existing microarray data from clinical, pharmaceutical, and academic settings represent valuable and often underappreciated resources, and methods for assessing and improving the quality of these data are lacking.
resultsTo quantitatively assess the quality of microarray probes, we directly compare RNA-Seq to Agilent microarrays by processing 231 unique samples from the Allen Human Brain Atlas using RNA-Seq. Both techniques provide highly consistent, highly reproducible gene expression measurements in adult human brain, with RNA-Seq slightly outperforming microarray results overall. We show that RNA-Seq can be used as ground truth to assess the reliability of most microarray probes, remove probes with off-target effects, and scale probe intensities to match the expression levels identified by RNA-Seq. These sequencing scaled microarray intensities (SSMIs) provide more reliable, quantitative estimates of absolute expression levels for many genes when compared with unscaled intensities. Finally, we validate this result in two human cell lines, showing that linear scaling factors can be applied across experiments using the same microarray platform.
conclusionsMicroarrays provide consistent, reproducible gene expression measurements, which are improved using RNA-Seq as ground truth. We expect that our strategy could be used to improve probe quality for many data sets from major existing repositories.
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Registered trials
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.