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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