--- a
+++ b/bin/plot_pca.py
@@ -0,0 +1,64 @@
+"""
+Basic script for pltoting pca of a dataset(s)
+"""
+
+import os
+import sys
+import argparse
+import logging
+import itertools
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+SRC_DIR = os.path.join(
+    os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "babel",
+)
+assert os.path.isdir(SRC_DIR)
+sys.path.append(SRC_DIR)
+import interpretation
+import adata_utils
+import plot_utils
+import utils
+
+from evaluate_bulk_rna_concordance import load_file_flex_format
+
+
+def var_barplot(var: np.ndarray, fname: str = ""):
+    """Basic barplot of explained variance"""
+    fig, ax = plt.subplots(dpi=300)
+    ax.bar(np.arange(len(var)), var)
+    ax.set(
+        xlabel=f"Principal component",
+        ylabel="Explained variance",
+        title=f"Top {len(var)} PCs ({np.sum(var):.4f} explained variance)",
+    )
+    if fname:
+        fig.savefig(fname, bbox_inches="tight")
+    return fig
+
+
+def build_parser():
+    """Build a basic CLI parser"""
+    parser = argparse.ArgumentParser()
+    parser.add_argument("adata_fname", type=str, help="Adata object to plot PCA for")
+    parser.add_argument("plot_prefix", type=str, help="Prefix to save plots to")
+    parser.add_argument(
+        "--numdims", "-n", type=int, default=16, help="Number of top PCs to consider"
+    )
+    return parser
+
+
+def main():
+    """Run script"""
+    parser = build_parser()
+    args = parser.parse_args()
+
+    adata = load_file_flex_format(args.adata_fname)
+
+    var = adata.uns["pca"]["variance_ratio"][: args.numdims]
+    var_barplot(var, fname=args.plot_prefix + "_explained_var.pdf")
+
+
+if __name__ == "__main__":
+    main()