ArticleProceedings of the National Academy of Sciences of the United States of America2008
Defining diversity, specialization, and gene specificity in transcriptomes through information theory.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.
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Who cites it
69 citing papers in PubMed.
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- Standardized metrics for assessment and reproducibility of imaging-based spatial transcriptomics datasets.Nature biotechnology · 2026Article
- Multi-Tissue Genetic Regulation of RNA Editing in Pigs.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
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- Assessment of Potential Toxic Effects of RNAi-Based Transgenic Cotton on the Non-Target PredatorBiology · 2025Article
- Perplexity as a Metric for Isoform Diversity in the Human Transcriptome.bioRxiv : the preprint server for biology · 2025Article
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- Spinal neuron diversity scales exponentially with swim-to-limb transformation during frog metamorphosis.bioRxiv : the preprint server for biology · 2024Article
- Calorie restriction and rapamycin distinctly mitigate aging-associated protein phosphorylation changes in mouse muscles.Communications biology · 2024Article
- Nitrogen and sulfur for phosphorus: Lipidome adaptation of anaerobic sulfate-reducing bacteria in phosphorus-deprived conditions.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Selective lipid recruitment by an archaeal DPANN symbiont from its host.Nature communications · 2024Article
- Estimating Transcriptome Diversity and Specialization inPlants (Basel, Switzerland) · 2024Article
- Quantifying transcriptome diversity: a review.Briefings in functional genomics · 2024Review
- Comparative analysis of models in predicting the effects of SNPs on TF-DNA binding using large-scale in vitro and in vivo data.Briefings in bioinformatics · 2024Article
9 more citing papers are in PubMed but not listed here.
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2 authors.
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Abstract
The transcriptome is a set of genes transcribed in a given tissue under specific conditions and can be characterized by a list of genes with their corresponding frequencies of transcription. Transcriptome changes can be measured by counting gene tags from mRNA libraries or by measuring light signals in DNA microarrays. In any case, it is difficult to completely comprehend the global changes that occur in the transcriptome, given that thousands of gene expression measurements are involved. We propose an approach to define and estimate the diversity and specialization of transcriptomes and gene specificity. We define transcriptome diversity as the Shannon entropy of its frequency distribution. Gene specificity is defined as the mutual information between the tissues and the corresponding transcript, allowing detection of either housekeeping or highly specific genes and clarifying the meaning of these concepts in the literature. Tissue specialization is measured by average gene specificity. We introduce the formulae using a simple example and show their application in two datasets of gene expression in human tissues. Visualization of the positions of transcriptomes in a system of diversity and specialization coordinates makes it possible to understand at a glance their interrelations, summarizing in a powerful way which transcriptomes are richer in diversity of expressed genes, or which are relatively more specialized. The framework presented enlightens the relation among transcriptomes, allowing a better understanding of their changes through the development of the organism or in response to environmental stimuli.
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