Resources

A curated index of articles, updates, events, and published work across single-cell research.

Showing 61–66 of 66

Tracking early mammalian organogenesis – prediction and validation of differentiation trajectories at whole organism scale
Publication

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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Single cell multi-omics analysis of chronic myeloid leukemia links cellular heterogeneity to therapy response
Publication

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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CTEC: a cross-tabulation ensemble clustering approach for single-cell RNA sequencing data analysis
Publication Tools

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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A guide to single-cell RNA sequencing analysis using web-based tools for non-bioinformatician
Publication ScarfWeb Tools

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
Publication

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
Publication ScarfWeb

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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