ReviewScience advances2018
Accelerating a paradigm shift: The Common Fund Single Cell Analysis Program.
Review in Science advances, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Comparative analysis of nuclei isolation methods for brain single-nucleus RNA sequencing.Cell reports methods · 2026Article
- SenNet Portal: Build, Optimization and Usage.bioRxiv : the preprint server for biology · 2026Article
- Enhancing lipid production in plant cells through automated high-throughput genome engineering and phenotyping.The Plant cell · 2025Article
- A ligand-receptor interactome platform for discovery of pain mechanisms and therapeutic targets.Science signaling · 2021Article
- CaMKIIα-Positive Interneurons Identified via a microRNA-Based Viral Gene Targeting Strategy.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020Article
- Article
- Single-Cell RNA Sequencing-Based Computational Analysis to Describe Disease Heterogeneity.Frontiers in genetics · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
It has become exceedingly important to understand the precise molecular profiles of the nearly 40 trillion cells in an adult human because of their role in determining health, disease, and therapeutic outcome. The National Institutes of Health (NIH) Common Fund-supported Single Cell Analysis Program (SCAP) was designed to address this challenge. In this review, we outline the original program goals and provide a perspective on the impact of the program as a catalyst for exploration of heterogeneity of human tissues at the cellular level. We believe that the technological advances in single-cell RNA sequencing and multiplexed imaging combined with computational methods made by this program will undoubtedly have an impact on broad and robust applications of single-cell analyses in both health and disease research.
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.