ArticleProceedings of the National Academy of Sciences of the United States of America2023
sccomp: Robust differential composition and variability analysis for single-cell data.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.
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Who cites it
49 citing papers in PubMed.
- BCMA-directed mRNA CAR-T cell therapy for myasthenia gravis: exploratory biomarker analysis of a placebo-controlled phase 2b trial.Nature medicine · 2026Trial
- PLCG2 downregulation impairs synaptic function and increases Alzheimer's disease hallmarks in neuronal cultures.Nature genetics · 2026Article
- Article
- Characterization of Electrophysiological and Transcriptomic Alterations in Patient-Derived Neurons from CHAMP1 Syndrome.bioRxiv : the preprint server for biology · 2026Article
- Single-cell analysis reveals impaired Müller glia-mediated intercellular communication and photoreceptor pathology in USH1C retinal organoids.Cellular and molecular life sciences : CMLS · 2026Article
- Spatial transcriptomics identifies immune-stromal niches associated with cancer in adult dermatomyositis.Nature communications · 2026Article
- Argonaute proteins orchestrate Meiotic Sex Chromosome Inactivation and timing of the spermatogenic transcriptional program.PLoS genetics · 2026Article
- Article
- Deep phenotyping of skin tissue remodeling in patients with systemic sclerosis treated with CD19-CAR T cells.Nature communications · 2026Article
- Single-nucleus profiling reveals age-associated remodeling opposed by parity in the postmenopausal human ovary.bioRxiv : the preprint server for biology · 2026Article
- Molecular features of response and resistance to glofitamab, a T-cell engager for treatment of large B-cell lymphoma.Blood advances · 2026Article
- Single-nucleus RNA sequencing reveals the cellular composition and the mechanism underlying adrenal myelolipoma.Endocrine · 2026Article
- A single-cell multiomic analysis identifies molecular and gene-regulatory mechanisms dysregulated in developing Down syndrome neocortex.Science (New York, N.Y.) · 2026Article
- Antiviral CD4Communications medicine · 2026Article
- Upregulation of an Epithelial miRNA Is Associated with Immune Evasion in Progressive Bronchial Premalignant Lesions.Cancer immunology research · 2026Article
- Non-microglial downregulation ofbioRxiv : the preprint server for biology · 2026Article
- A highly resolved integrated single-cell atlas of HPV-negative head and neck cancer.Communications medicine · 2026Article
- Single-cell atlas of the developing Down syndrome brain cortex.Nature medicine · 2026Article
- EZH2 directs HER2+ breast cancer progression through the modulation of epithelial plasticity.EMBO reports · 2026Article
- A highly resolved integrated single-cell atlas of human breast cancers.NAR genomics and bioinformatics · 2026Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cellular omics such as single-cell genomics, proteomics, and microbiomics allow the characterization of tissue and microbial community composition, which can be compared between conditions to identify biological drivers. This strategy has been critical to revealing markers of disease progression, such as cancer and pathogen infection. A dedicated statistical method for differential variability analysis is lacking for cellular omics data, and existing methods for differential composition analysis do not model some compositional data properties, suggesting there is room to improve model performance. Here, we introduce sccomp, a method for differential composition and variability analyses that jointly models data count distribution, compositionality, group-specific variability, and proportion mean-variability association, being aware of outliers. sccomp provides a comprehensive analysis framework that offers realistic data simulation and cross-study knowledge transfer. Here, we demonstrate that mean-variability association is ubiquitous across technologies, highlighting the inadequacy of the very popular Dirichlet-multinomial distribution. We show that sccomp accurately fits experimental data, significantly improving performance over state-of-the-art algorithms. Using sccomp, we identified differential constraints and composition in the microenvironment of primary breast cancer.
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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.