Deep bag-of-genes model for single cell classification
Bin Zhou, Fan Yang, Ting Chen, Feng Zeng. Seeing cells as bags-of-genes: a simple deep generative model for platform-independent single cell classification. Submission. 2021
- Install pytorch according to your computational platform
- Install dependencies:
pip3 install numpy scipy pandas scikit-learn pyro-ppl matplotlib
- scClassifier2 accepts as input the log-transformed gene matrix in the MatrixMarket format usually end in ".mtx", where rows are cells and columns are genes.
- The label file can be either the CSV format or the TSV format, one label per line.
- Data gives some examples of matrix and label files.
Please refer to the PBMC68k example.
usage: scClassifier2.py [-h] [--cuda] [--jit] [-n NUM_EPOCHS] [--aux-loss] [-alm AUX_LOSS_MULTIPLIER] [-enum ENUM_DISCRETE]
[--sup-data-file SUP_DATA_FILE] [--sup-label-file SUP_LABEL_FILE] [--unsup-data-file UNSUP_DATA_FILE]
[--unsup-label-file UNSUP_LABEL_FILE] [-64] [-lt] [--cross-validation-fold CROSS_VALIDATION_FOLD] [-zd Z_DIM]
[-hl HIDDEN_LAYERS [HIDDEN_LAYERS ...]] [-lr LEARNING_RATE] [-dr DECAY_RATE] [-de DECAY_EPOCHS] [-b1 BETA_1]
[-bs BATCH_SIZE] [-rt] [-log LOGFILE] [--seed SEED] [--best-valid-model BEST_VALID_MODEL] [--best-aux-model BEST_AUX_MODEL]