A rank-based marker selection method for high throughput scRNA-seq data | BMC Bioinformatics | Full Text
Combinatorial prediction of marker panels from single‐cell transcriptomic data | Molecular Systems Biology
FindMarkers with several dataset (4) · Issue #836 · satijalab/seurat · GitHub
Introduction to scRNA-seq integration • Seurat
A rank-based marker selection method for high throughput scRNA-seq data | BMC Bioinformatics | Full Text
Introduction to scRNA-seq integration • Seurat
How to find dataset differences in R Quickly Compare Datasets | R-bloggers
Explore Your Dataset (EDA) in R — Little Miss Data
Detection of differentially abundant cell subpopulations in scRNA-seq data | PNAS
GSEA User Guide
Introduction to scRNA-seq integration • Seurat
Current best practices in single‐cell RNA‐seq analysis: a tutorial | Molecular Systems Biology
Current best practices in single‐cell RNA‐seq analysis: a tutorial | Molecular Systems Biology
Plotting time-series data — Climate Data Store Toolbox 1.1.1 documentation
A rank-based marker selection method for high throughput scRNA-seq data | BMC Bioinformatics | Full Text
Proteome activity landscapes of tumor cell lines determine drug responses | Nature Communications
Manipulating, analyzing and exporting data with tidyverse
FindMarkers on integrated dataset · Issue #3451 · satijalab/seurat · GitHub
FindMarkers with several dataset (4) · Issue #836 · satijalab/seurat · GitHub
Manipulating data with R
Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling | Nature Methods
Chapter 11 Marker gene detection | Orchestrating Single-Cell Analysis with Bioconductor
Single-cell resolution analysis of the human pancreatic ductal progenitor cell niche | PNAS
Data visualization methods in Seurat • Seurat
How to interpret the output of FindConservedMarkers · Issue #1705 · satijalab/seurat · GitHub
Trajectory-based differential expression analysis for single-cell sequencing data | Nature Communications
