ReviewCurrent opinion in immunology2019
Multimodal single-cell approaches shed light on T cell heterogeneity.
Review in Current opinion in immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Sketching T cell atlases in the single-cell era: challenges and recommendations.Immunology and cell biology · 2025Review
- InTraSeq: A Multimodal Assay that Uncovers New Single-Cell Biology and Regulatory Mechanisms.Research square · 2024Article
- Multimodal and spatially resolved profiling identifies distinct patterns of T cell infiltration in nodal B cell lymphoma entities.Nature cell biology · 2024Article
- Single-cell RNA sequencing in melanoma: what have we learned so far?EBioMedicine · 2024Review
- Dynamic regulatory elements in single-cell multimodal data implicate key immune cell states enriched for autoimmune disease heritability.Nature genetics · 2023Article
- Understanding blood development and leukemia using sequencing-based technologies and human cell systems.Frontiers in molecular biosciences · 2023Review
- Distinguishing activated T regulatory cell and T conventional cells by single-cell technologies.Immunology · 2022Article
- Multimodal detection of protein isoforms and nucleic acids from low starting cell numbers.Lab on a chip · 2021Article
- Multimodally profiling memory T cells from a tuberculosis cohort identifies cell state associations with demographics, environment and disease.Nature immunology · 2021Observational
- Computational methods for the integrative analysis of single-cell data.Briefings in bioinformatics · 2021Review
- Static array of droplets and on-demand recovery for biological assays.Biomicrofluidics · 2020Article
- Applications of Single-Cell Omics to Dissect Tumor Microenvironment.Frontiers in genetics · 2020Review
- Single-cell biology: beyond the sum of its parts.Nature methods · 2020Article
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
Abstract
Single-cell methods have revolutionized the study of T cell biology by enabling the identification and characterization of individual cells. This has led to a deeper understanding of T cell heterogeneity by generating functionally relevant measurements - like gene expression, surface markers, chromatin accessibility, T cell receptor sequences - in individual cells. While these methods are independently valuable, they can be augmented when applied jointly, either on separate cells from the same sample or on the same cells. Multimodal approaches are already being deployed to characterize T cells in diverse disease contexts and demonstrate the value of having multiple insights into a cell's function. But, these data sets pose new statistical challenges for integration and joint analysis.
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.