use zipped fasta file

tiger.py

@@ -1,4 +1,5 @@
 import os
+import gzip
 import numpy as np
 import pandas as pd
 import tensorflow as tf
@@ -85,7 +86,7 @@ def tiger_predict(transcript_seq: str):
 
 
 def find_off_targets(guides, batch_size=1000):
-    with open('gencode.v19.pc_transcripts.fa', 'r') as file:
+    with gzip.open(os.path.join('transcripts', 'gencode.v19.pc_transcripts.fa.gz'), 'rt') as file:
         df_transcripts = pd.DataFrame([(t.id, str(t.seq)) for t in SeqIO.parse(file, 'fasta')], columns=['id', 'seq'])
     df_transcripts['id'] = df_transcripts['id'].apply(lambda s: s.split('|')[4])
     df_transcripts.set_index('id', inplace=True)