preprocess_million.py

# This script is used for preprocessing the Zheng Mouse dataset
# Modified from https://github.com/berenslab/rna-seq-tsne/blob/master/server-10xdata.py

import numpy as np
import pandas as pd
import scanpy as sc

np.random.seed(0)
data_folder = "" # Please specify your path to the data


def main():
    # Save the information in another format
    sc.settings.verbosity = 2

    # Data file is from here 
    # https://support.10xgenomics.com/single-cell-gene-expression/datasets/1.3.0/1M_neurons
    adata = sc.read_10x_h5(data_folder + '/1M_neurons_filtered_gene_bc_matrices_h5.h5')
    print(f"1M data has shape: {adata.X.shape}")
    sc.pp.recipe_zheng17(adata)

    X = np.copy(adata.X)
    X = X - X.mean(axis=0)
    U, s, V = np.linalg.svd(X, full_matrices=False)
    U[:, np.sum(V,axis=1)<0] *= -1
    X = np.dot(U, np.diag(s))
    X = X[:, np.argsort(s)[::-1]][:,:100] # 100 Dimensions
    np.save(data_folder + '/1M_neurons_100pc_npy.npy', X)

    # load cluster labels
    # https://github.com/theislab/scanpy_usage/blob/master/170522_visualizing_one_million_cells/results/louvain.csv.gz
    clusters = pd.read_csv(data_folder + '/louvain.csv.gz', header=None).values[:,1].astype(int)
    np.save(data_folder + '/1M_neurons_cluster_npy.npy', clusters)


if __name__ == "__main__":
    main()