tiger.py finishing touches

tiger.py

@@ -275,6 +275,9 @@ def predict_off_target(off_targets: pd.DataFrame, model: tf.keras.Model):
     lfc_estimate = model.predict(model_inputs, batch_size=BATCH_SIZE_COMPUTE, verbose=False)
     off_targets[SCORE_COL] = prediction_transform(tf.squeeze(lfc_estimate).numpy())
 
+    # trim context sequence
+    off_targets[SEQ_COL] = off_targets[SEQ_COL].apply(lambda seq: seq[CONTEXT_5P:len(seq) - CONTEXT_3P])
+
     return off_targets.sort_values(SCORE_COL, ascending=False).reset_index(drop=True)
 
 
@@ -313,7 +316,7 @@ def tiger_exhibit(transcripts: pd.DataFrame, mode: str, check_off_targets: bool,
     if check_off_targets and len(off_target_predictions) > 0:
         off_target_predictions[GUIDE_COL] = off_target_predictions[GUIDE_COL].apply(lambda s: s[::-1])
 
-    return on_target_predictions.reset_index(drop=True), off_target_predictions.reset_index(drop=True)
+    return on_target_predictions, off_target_predictions
 
 
 if __name__ == '__main__':