What is Single Cell Transcriptomics?
Discover single-cell transcriptomics, a transformative technique for analyzing gene expression at the cellular level in biology and medicine.
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A curated index of articles, updates, events, and published work across single-cell research.
Overcoming Bioinformatics Skill Gaps in Single-Cell Research
Discover solutions to bridge bioinformatics skill gaps in single-cell research, enabling easier scRNA-seq analysis for wet-lab scientists.
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CTEC: a cross-tabulation ensemble clustering approach for single-cell RNA sequencing data analysis
Liang Wang et al. present CTEC, an ensemble clustering method for robust scRNA-seq data analysis.
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Single cell multi-omics analysis of chronic myeloid leukemia links cellular heterogeneity to therapy response
Rebecca Warfvinge et al. link single-cell multi-omics heterogeneity in CML to variations in therapy response.
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Characterization of regeneration initiating cells during Xenopus laevis tail regeneration
Radek Sindelka et al. characterize cells that initiate regeneration during Xenopus tail regrowth.
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Tracking early mammalian organogenesis – prediction and validation of differentiation trajectories at whole organism scale
Ivan Imaz-Rosshandler et al. predict and validate cell differentiation trajectories during early mammalian organogenesis.
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EpiCarousel: memory- and time-efficient identification of metacells for atlas-level single-cell chromatin accessibility data
Sijie Li et al. introduce EpiCarousel for efficient metacell identification in large-scale chromatin accessibility datasets.
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Spatiotemporal transcriptomic map of glial cell response in a mouse model of acute brain ischemia
Daniel Zucha et al. map glial cell responses over time in a mouse brain ischemia model using spatial transcriptomics.
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A guide to single-cell RNA sequencing analysis using web-based tools for non-bioinformatician
Sagnik Yarlagadda and Todd D. Giorgio provide a practical guide to scRNA-seq analysis using web-based platforms.
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Single-cell multiomics of human fetal hematopoiesis define a developmental-specific population and a fetal signature
Mikael N. E. Sommarin et al. define developmental-specific populations in human fetal blood formation using multi-omics.
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Scarf enables a highly memory-efficient analysis of large-scale single-cell genomics data
Parashar Dhapola et al. introduce Scarf for memory-efficient single-cell sequencing analysis, published in Nature Communications.
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