ABCA1, ABCA3, TEME

df = pd.read_csv('Genes.csv', index_col=0)
    X = df.values
    means = X.mean(axis=0)
    stdevs = X.std(axis=0)
    Xcent = X - means
    Xnorm = Xcent / stdevs
    features = ['ABCA1', 'ABCA3', ..., 'TEME'] #all the genes
    df_norm = df.copy()
    df_norm[features] = StandardScaler().fit(df_norm[features]).transform(df_norm[features])
    X_tsne = TSNE(learning_rate=500, n_components=2).fit_transform(df_norm[features])
    figure(figsize=(11, 5))
    cmap = plt.get_cmap('nipy_spectral')
    scatter(X_tsne[:, 0], X_tsne[:, 1])
    title('TSNE')