why this blog post? I saw a biorxiv paper titled A comparison of marker gene selection methods for single-cell RNA sequencing data Our results highlight the efficacy of simple methods, especially the Wilcoxon rank-sum test, Student’s t-test and logistic regression I am interested in using logistic regression to find marker genes and want to try fitting the model in the tidymodel ecosystem and using different regularization methods.

● 🧬 Keep aside scattered cells of each cluster to analyze separately in certain Seurat metadata!!!!!! Have you ever highlighted your cells and seen the red dots scattered across the whole embeddin...

Codon

Abstract. Understanding gene regulation at single-cell resolution is crucial for unraveling development, disease, and cellular identity. We introduce singl

Use LISI and silhouette scores to assess batch mixing and cluster structure in single-cell RNA-seq embeddings, with practical cautions about labels, embeddings, and interpretation.

Plants reposition and grow their leaves towards optimal light conditions in a canopy. To achieve both horizontal and vertical displacement, plants need to simultaneously elongate their cells unidirect...

Explore foundational advanced downstream analyses: mapping cell-cell communication networks, inferring Transcription Factor (TF) activities, and generating publication-ready plots (SCpubr).

Learn how to infer cell-to-cell signaling networks from scRNA-seq data using state-of-the-art tools like LIANA and CellChat.

Contribute to YaJahn/SPAE development by creating an account on GitHub.

Scientific Reports - Single-cell RNA sequencing of hematopoietic and non-hematopoietic cells defines a distinct signature in atopic and NRG1 mouse lung