Gene Marker Search and Cell Annotation Tool User Guide

1. Environment configuration

conda install -c conda-forge r-base=4.3.1
conda install -c conda-forge r-optparse=1.7.5
conda install -c conda-forge r-dplyr=1.1.2
conda install -c conda-forge r-tidyr=1.3.1

2.1 Help information

Rscript cell_marker_cli.R -h

Usage: Rscript cell_marker_cli.R –mode MODE [options]

BMKMANU Cell Marker Database CLI – marker search and cell annotation tool

Options:

-m MODE, –mode=MODE
Run mode: marker_search (marker search) or celltype_anno (cell annotation) [required]

-s SPECIES, –species=SPECIES
Species (default: Human)

-t TISSUE, –tissue=TISSUE
Tissue (optional, no filtering by default)

-k MARKERS, –marker=MARKERS
Marker genes, multiple values separated by commas (marker_search mode only)

-g GENES, –genes=GENES
Input gene list, multiple values separated by commas or newlines (celltype_anno mode only)

-o FILE, –output=FILE
Output file path (CSV format; prints to console by default)

–top=N
Return the top N results in cell annotation mode (default: 20)

-d FILE, –data=FILE
Path to the MarkerGene data file (default: cell_marker_cli.txt in the same directory as the script)

–list-species
List all available species

–list-tissues
List all tissues under the specified species

-v, –verbose
Show verbose output

-h, –help
Show this help message and exit

2.2 Usage examples

3. Analysis results

Rscript cell_marker_cli.R --mode celltype_anno --species Human --genes 'CD3D,CD19,CD68'

╔══════════════════════════════════════════════════════════════╗
║BMKMANU Cell Marker Database - Command Line Tool              ║
╠══════════════════════════════════════════════════════════════╣
║Mode 1: marker_search - search cell types by species/tissue   ║
║Mode 2: celltype_anno - predict cell types from gene list     ║
╚══════════════════════════════════════════════════════════════╝

═══════════════════════════════════════════════════════════════
Predicted cell types (Top 20)
═══════════════════════════════════════════════════════════════
Input genes: 3
Matched genes: 3 (CD19, CD3D, CD68)
═══════════════════════════════════════════════════════════════

───────────────────────────────────────────────────────────────
Top predictions:
#1 Activated CD4+ T cell (tissue: Blood) - matched 2/3 genes (66.7%)
#2 Macrophage (tissue: Blood) - matched 2/3 genes (66.7%)
#3 Monocyte (tissue: Peripheral blood) - matched 2/3 genes (66.7%)
#4 Myeloid cell (tissue: Bone marrow) - matched 2/3 genes (66.7%)
#5 Natural killer cell (tissue: Blood) - matched 2/3 genes (66.7%)
───────────────────────────────────────────────────────────────
✅ Done!
Notes:
1. After the script runs, the results are printed to the screen
2. To redirect the results, simply specify the -o parameter
3. Only one result set is shown here; users can explore the other usage examples on their own
4. By default, cell_marker_cli.txt in the same directory as the script is used; users can of course configure their own