ArticleNature methods2022
Real age prediction from the transcriptome with RAPToR.
Article in Nature methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
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- Enteric viral infections promote systemic accelerated aging inScience advances · 2026Article
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- Imaging-derived biological age across multiple organs links to mortality and aging-related health outcomes.npj aging · 2026Article
- Perinatal brain developmental transition revealed by transcriptomic and proteomic analyses of Bama miniature pigs.Nature communications · 2026Article
- Cell type-agnostic transcriptomic signatures enable uniform comparisons of neural maturation.PLoS biology · 2026Article
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- Advances in multi-omics and aging clock research for female reproductive health and aging.MedScience · 2026Review
- Cell type-independent timekeeping gene modules enable embryonic stage prediction in zebrafish.bioRxiv : the preprint server for biology · 2025Article
- HLH-30/TFEB is necessary for chromatin reorganization and maintenance of cell quiescence during starvation inbioRxiv : the preprint server for biology · 2025Article
- Spatially-restricted inflammation-induced senescent-like glia in multiple sclerosis and patient-derived organoids.Nature communications · 2025Article
- Axon termination of the SAB motor neurons inbioRxiv : the preprint server for biology · 2025Article
- Excretory gland cell and NSPC genes in C. elegans: investigating their physiological roles.Genetics · 2025Article
- The regulatory architecture of gene expression variation in Caenorhabditis elegans revealed by multi-strain allele-specific analysis.Genetics · 2025Article
- The regulatory architecture of gene expression variation inbioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transcriptomic data is often affected by uncontrolled variation among samples that can obscure and confound the effects of interest. This variation is frequently due to unintended differences in developmental stages between samples. The transcriptome itself can be used to estimate developmental progression, but existing methods require many samples and do not estimate a specimen's real age. Here we present real-age prediction from transcriptome staging on reference (RAPToR), a computational method that precisely estimates the real age of a sample from its transcriptome, exploiting existing time-series data as reference. RAPToR works with whole animal, dissected tissue and single-cell data for the most common animal models, humans and even for non-model organisms lacking reference data. We show that RAPToR can be used to remove age as a confounding factor and allow recovery of a signal of interest in differential expression analysis. RAPToR will be especially useful in large-scale single-organism profiling because it eliminates the need for accurate staging or synchronisation before profiling.
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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 Socratic graph.