ArticleMethods in molecular biology (Clifton, N.J.)2025
Immune Single-Cell Annotation by Molecular Signature-Based Deconvolution with MIXTURE.
Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Cell type-specific pharmacological modulation of the neuro-immune axis: the role of ADRB2 signaling in reshaping the tumor ecosystem.Frontiers in pharmacology · 2026Review
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Authors and funding
6 authors.
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Abstract
Accurate cell type identification in single-cell RNA sequencing (scRNA-seq) datasets is essential for dissecting the tumor immune microenvironment (TIME) and optimizing immunotherapy strategies. Here, we present an annotation protocol based on MIXTURE, our v-SVR deconvolution algorithm, which addresses the limitations of unsupervised annotation methods. We applied MIXTURE to an annotated melanoma scRNA-seq dataset, demonstrating its effectiveness in enhancing detailed cell type annotation and composition analysis of unannotated clusters. Our protocol successfully explores the composition of clusters, by providing detailed insights into cluster heterogeneity, enabling more accurate and granular identification of distinct cell types within complex single-cell RNA sequencing datasets.
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