ReviewNature biotechnology2025
Cell type inference in cell-free nucleic acid liquid biopsy.
Review in Nature biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Integrated inference of cancer gene expression from cell-free plasma chromatin.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cell-free nucleic acid (cfNA) liquid biopsy offers a versatile, noninvasive alternative to needle biopsy procedures for the diagnosis or surveillance of a broad range of diseases and physiological conditions. Although these noninvasive molecular measurements enable diagnostic biomarker discovery, they often lack the cellular resolution afforded by invasive needle biopsy. Cell type-specific changes frequently form the basis of disease and contribute to the molecular changes observed in a cfNA liquid biopsy. Recent experimental and computational advances in cfNA detection, alongside detailed molecular definitions across cell types of the human body from single-cell transcriptomic data, can enable cell type inference. In this Review, we delineate the respective strengths of cell-free DNA and cell-free RNA relative to the diagnostic use case. We then describe computational frameworks to infer cell type contributions in cfNA and the distinct opportunity afforded by single-cell transcriptomic data. Finally, we highlight current applications, future directions, and outstanding questions related to this paradigm in cfNA liquid biopsy.
Indexed as
Identifiers
41299043What OpenQuestion holds
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.