minor [skip ci]

scripts/run_arboretum.py

@@ -14,11 +14,11 @@
 parser = argparse.ArgumentParser()
 parser.add_argument('-i', type=str, required=True, help='the expression matrix file (required)')
 parser.add_argument('-tf', type=str, required=True, help='the transcription factors file (required)')
-parser.add_argument('-o', type=str, required=True, help='the file for the network output (requires)')
+parser.add_argument('-o', type=str, required=True, help='the file for the network output (required)')
 parser.add_argument('-a', '--scheduler_address', required=False, help='Dask scheduler address (optional)')
 parser.add_argument('--genie3', help='use GENIE3', action='store_true')
 parser.add_argument('--grnboost2', help='use GRNBoost2 (default)', action='store_true')
-parser.add_argument('--dry-run', action='store_true')
+parser.add_argument('--dry-run', action='store_true', help='test input without launching inference runs (optional)')
 parser.add_argument('--seed', type=int, required=False, default=None,
                     help='Seed value for regressor random state initialization (optional)')
 

scripts/run_diff_seeds_dream5_standardized.py

@@ -0,0 +1,98 @@
+"""
+Python script for running Arboretum multiple times on the DREAM5 dataset,
+initialized with a different random seed for each run.
+
+The objective is to assess the stability of the inference quality of GRNBoost2
+compared with GENIE3/Arboretum and the GENIE3 results as reported in the Dream5 paper.
+"""
+
+import pandas as pd
+import time
+
+from arboretum.algo import genie3, grnboost2
+from arboretum.utils import load_tf_names
+from distributed import Client
+
+from sklearn.preprocessing import StandardScaler
+
+DEFAULT_N_RUNS = 100
+
+wd = '../resources/dream5/'
+
+net1_expression = wd + 'net1/net1_expression_data.tsv'
+net3_expression = wd + 'net3/net3_expression_data.tsv'
+net4_expression = wd + 'net4/net4_expression_data.tsv'
+
+net1_tfs = wd + 'net1/net1_transcription_factors.tsv'
+net3_tfs = wd + 'net3/net3_transcription_factors.tsv'
+net4_tfs = wd + 'net4/net4_transcription_factors.tsv'
+
+datasets = [('net1', net1_expression, net1_tfs),
+            ('net3', net3_expression, net3_tfs),
+            ('net4', net4_expression, net4_tfs)]
+
+# algo = 'grnboost2'
+algo = 'genie3'
+out_dir = '../output/dream5/{}.std/'.format(algo)
+
+seeds = [seed * 100 for seed in range(0, 100)]
+# seeds = [seed * 100 for seed in range(0, 1)]
+
+# dry_run = True
+dry_run = False
+
+
+def run_algo(client, algo_name, seed_value):
+
+    if algo_name == 'genie3':
+        inf_algo = genie3
+    elif algo_name == 'grnboost2':
+        inf_algo = grnboost2
+    else:
+        raise ValueError('Houston, we have a problem between desk and chair.. ({})'.format(algo_name))
+
+    scaler = StandardScaler()
+
+    for network_name, exp_path, tfs_path in datasets:
+        start_time = time.time()
+
+        print('inferring {0} with seed {1}'.format(network_name, seed))
+
+        exp_matrix = pd.read_csv(exp_path, sep='\t')
+
+        scaled_values = scaler.fit_transform(exp_matrix)
+
+        exp_matrix_scaled = pd.DataFrame(scaled_values, columns=exp_matrix.columns)
+
+        tf_names = load_tf_names(tfs_path)
+        network_df = inf_algo(client_or_address=client,
+                              expression_data=exp_matrix_scaled,
+                              tf_names=tf_names,
+                              seed=seed_value,
+                              limit=100000)
+
+        inf_time = time.time()
+        delta_time = inf_time - start_time
+
+        print('inferred {0} with seed {1} in {2} seconds'.format(network_name, seed, str(delta_time)))
+
+        network_out_path = '{0}{1}.seed_{2}.csv'.format(out_dir, network_name, seed)
+
+        network_df.to_csv(network_out_path, sep='\t', index=None, header=None)
+
+        print('{0} with seed {1} written to {2}'.format(network_name, seed, network_out_path))
+
+
+if __name__ == '__main__':
+
+    client = Client()
+
+    print(str(client))
+
+    for seed in seeds[:3]:
+        print('running {0} with seed {1}'.format(algo, seed))
+
+        if not dry_run:
+            run_algo(client, algo, seed)
+
+    client.shutdown()

scripts/run_dream5_net1_grnboost2.sh

@@ -1,3 +1,5 @@
+#!/usr/bin/env bash
+
 python run_arboretum.py --grnboost2 \
 -i ../resources/dream5/net1/net1_expression_data.tsv \
 -tf ../resources/dream5/net1/net1_transcription_factors.tsv \