Current best practices in single‐cell RNA‐seq analysis: a tutorial | Molecular Systems Biology
Sensors | Free Full-Text | Designing a Simple Fiducial Marker for Localization in Spatial Scenes Using Neural Networks | HTML
Chapter 11 Marker gene detection | Orchestrating Single-Cell Analysis with Bioconductor
Data visualization methods in Seurat • Seurat
Quick start to Harmony • harmony
Plotting heatmap of Marker genes in each celltypes in Seurat
A rank-based marker selection method for high throughput scRNA-seq data | BMC Bioinformatics | Full Text
Seurat - Guided Clustering Tutorial • Seurat
How to interpret the output of FindConservedMarkers · Issue #1705 · satijalab/seurat · GitHub
Current best practices in single‐cell RNA‐seq analysis: a tutorial | Molecular Systems Biology
Introduction to scRNA-seq integration • Seurat
GSEA User Guide
Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling | Nature Methods
Manipulating, analyzing and exporting data with tidyverse
Optimal marker gene selection for cell type discrimination in single cell analyses | Nature Communications
Explore Your Dataset (EDA) in R — Little Miss Data
FindMarkers on integrated dataset · Issue #3451 · satijalab/seurat · GitHub
FindMarkers with several dataset (4) · Issue #836 · satijalab/seurat · GitHub
Introduction to scRNA-seq integration • Seurat
FindMarkers with several dataset (4) · Issue #836 · satijalab/seurat · GitHub
Single-nucleus transcriptome analysis reveals dysregulation of angiogenic endothelial cells and neuroprotective glia in Alzheimer's disease | PNAS
Combinatorial prediction of marker panels from single‐cell transcriptomic data | Molecular Systems Biology
Detection of differentially abundant cell subpopulations in scRNA-seq data | PNAS
A rank-based marker selection method for high throughput scRNA-seq data | BMC Bioinformatics | Full Text
A rank-based marker selection method for high throughput scRNA-seq data | BMC Bioinformatics | Full Text
