AMASC

AMASC (Automated Marker Analysis for Single-Cell RNA-seq) is a workflow for identifying a gene sets that can be applied in cell-type annotation for single-cell RNA-seq data.

Prerequisites

• R >= 3.6
• Python > 3.7
• XGBoost (Python)
• scikit-learn
• numpy
• pandas
• matplotlib

Usage

1. Prepare preprocessed (library-size-adjusted, log1p-transformed) CITE-Seq data sets in the CSV format as <MY_DATASET>_rna.csv and <MY_DATASET>_pe.csv
2. Modify the paths in AMASC.R
3. Run AMASC.R
4. The selected features will be in file features_<TIME>.txt

Please note that the process is stochastic and the parameters may require adjustments by data set.

Contributors

AMASC was developed by Tai-Hsien Ou Yang, Wei-Yi Cheng, and James Cai