ArticleNature methods2017
Sampling strategies to capture single-cell heterogeneity.
Article in Nature methods, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
16 citing papers in PubMed.
- Epigenetics in development, disease, and therapy: from mechanisms to clinical interventions.Science China. Life sciences · 2026Review
- AI-integrated microfluidics for drug screening: From single cell to organ-on-a-chip.Acta pharmaceutica Sinica. B · 2026Review
- MorphoITH: a framework for deconvolving intra-tumor heterogeneity using tissue morphology.Genome medicine · 2025Article
- Exploring a solid-state nanopore approach for single-molecule protein detection from single cells.Chemical science · 2025Article
- Multiplex imaging of localized prostate tumors reveals altered spatial organization of AR-positive cells in the microenvironment.iScience · 2024Article
- Spatial tumor immune microenvironment phenotypes in ovarian cancer.NPJ precision oncology · 2024Article
- Stem-cell states converge in multistage cutaneous squamous cell carcinoma development.Science (New York, N.Y.) · 2024Article
- In silico tissue generation and power analysis for spatial omics.Nature methods · 2023Article
- Optimizing multiplexed imaging experimental design through tissue spatial segregation estimation.Nature methods · 2023Article
- Article
- shRNAs targeting mouse Adam10 diminish cell response to proinflammatory stimuli independently of Adam10 silencing.Biology open · 2022Article
- Currently favored sampling practices for tumor sequencing can produce optimal results in the clinical setting.Scientific reports · 2020Article
- A multi-modal data resource for investigating topographic heterogeneity in patient-derived xenograft tumors.Scientific data · 2019Article
- Eliciting the impacts of cellular noise on metabolic trade-offs by quantitative mass imaging.Nature communications · 2019Article
- The influence of cell morphology on microfluidic single cell analysis.RSC advances · 2018Article
- Collective gradient sensing and chemotaxis: modeling and recent developments.Journal of physics. Condensed matter : an Institute of Physics journal · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Advances in single-cell technologies have highlighted the prevalence and biological significance of cellular heterogeneity. A critical question researchers face is how to design experiments that faithfully capture the true range of heterogeneity from samples of cellular populations. Here we develop a data-driven approach, illustrated in the context of image data, that estimates the sampling depth required for prospective investigations of single-cell heterogeneity from an existing collection of samples.
Indexed as
Identifiers
What 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.