Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data

Infer cell types in scRNA-seq data using bulk RNA-seq or gene sets

marker-based purification of cell types from single-cell RNA-seq datasets

A machine learning method for the discovery of the minimum marker gene combinations for cell type identification from single-cell RNA sequencing

Accurate and fast cell marker gene identification with COSG

Marker gene profile estimation method used in NeuroExpresso manuscript

Processing NEON soil microbe marker gene sequence data into ASV tables.

A tool for identifying phylogenetic marker genes in Nucleocytoviricota (giant viruses) and generating concatenated alignments.

Interactive visualization of marker genes and clustering in Slide-seq and single cell RNAseq data.

MiCV is a python dash-based web-application that enables researchers to upload raw scRNA-seq data and perform filtering, analysis, and manual annotation.

Compare several feature selection methods in scRNA-seq analysis

A library for differential expression and gene set enrichment analysis based on hydra and pydantic.

The goal of LRcell is to identify specific sub-cell types that drives the changes observed in a bulk RNA-seq differential gene expression experiment. To achieve this, LRcell utilizes sets of cell marker genes acquired from single-cell RNA-sequencing (scRNA-seq) as indicators for various cell types in the tissue of interest. Next, for each cell t…

Software suite for marker gene identification and cell type integration from single cell RNA-sequencing data

A hybrid approach to find spatially relevant marker genes in image based spatial transcriptomics data

scCTS: identifying the cell type-specific marker genes from population-level single-cell RNA-seq

Permutation testing in single cell analysis

MICTI- Marker gene Identification for Cell Type Identity

neonMicrobe: Processing NEON soil microbe marker gene sequence data into ASV tables, duplicated from https://github.com/claraqin/neonMicrobe