
Yejin Choi developed an end-to-end single-cell RNA-seq analysis pipeline for the childhealthbiostatscore/CHCO-Code repository, enabling researchers to perform pseudotime analysis, gene expression profiling, and cell-cell communication studies. The pipeline leveraged R and Python, utilizing Seurat, SingleCellExperiment, and nebula for core analyses, and integrated CellChat workflows for communication inference and visualization. Yejin created reproducible R Markdown notebooks with detailed templates and documentation, supporting scalable and shareable reporting. The work demonstrated depth through iterative integration of LIANA and enhanced CellChat support, providing a robust foundation for downstream bioinformatics analyses and facilitating biological insight generation without introducing bugs during the development period.

June 2025 CHCO-Code monthly summary: Delivered an end-to-end single-cell RNA-seq analysis pipeline with pseudotime, gene expression profiling, and cell-cell communication analyses; created reproducible R Markdown notebooks; initiated integrated CellChat/LIANA workflows; enabling researchers to derive biological insights and generate shareable reports at scale.
June 2025 CHCO-Code monthly summary: Delivered an end-to-end single-cell RNA-seq analysis pipeline with pseudotime, gene expression profiling, and cell-cell communication analyses; created reproducible R Markdown notebooks; initiated integrated CellChat/LIANA workflows; enabling researchers to derive biological insights and generate shareable reports at scale.
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