fix checkqc

GlimpseImputationPipeline/Glimpse2CheckQC.wdl

@@ -52,11 +52,11 @@ import pandas as pd
 data = pd.read_csv('~{qc_metrics}', sep='\t')
 qc_metric_thresholds = pd.read_csv('~{qc_metrics_thresholds}', sep='\t')
 
-data = data.melt(id_vars=['s'], var_name='metric', value_name='value', value_vars=qc_metric_thresholds.metric)
+data = data.melt(id_vars=['sample_id'], var_name='metric', value_name='value', value_vars=qc_metric_thresholds.metric)
 data = data.merge(qc_metric_thresholds, on=['metric'])
 
-samples_out_of_spec = data.loc[(data['value'] < data['min']) | (data['value'] > data['max'])].sort_values(['s', 'metric'])
-samples_out_of_spec.rename(columns={'s': 'sample_id'}).to_csv('~{output_basename}.qc_failures.tsv', sep='\t', index=False)
+samples_out_of_spec = data.loc[(data['value'] < data['min']) | (data['value'] > data['max'])].sort_values(['sample_id', 'metric'])
+samples_out_of_spec.to_csv('~{output_basename}.qc_failures.tsv', sep='\t', index=False)
 
 with open('~{output_basename}.qc_passed.txt', 'w') as qc_passed:
     qc_passed.write('true\n' if len(samples_out_of_spec) == 0 else 'false\n')