diff --git a/sampletranscript.py b/sampletranscript.py
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+++ b/sampletranscript.py
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+import pandas as pd
+import numpy as np
+
+'''
+Sample transcript 
+
+This part of the code does Poisson sampling proportionally to gene expression levels for each gene. 
+ 
+input:  total transcript number (int) 
+        csv file with gene id and  gene expression levels (columns named 'id' and 'level')
+
+output: csv file with gene id and count
+        gtf file with transcript samples
+'''
+
+def transcript_sampling(total_transcript, transcripts):
+
+    #read file containing representative transcript levels and id
+
+    transcript = pd.read_csv(transcripts)
+    transcript = transcripts
+    levels = []
+
+    #poisson sampling for each gene, proportional to expression levels
+
+    for expression_level in transcript['level']:
+
+        poisson_sampled = np.random.poisson(total_transcript/expression_level)
+        levels.append(poisson_sampled)
+        # note: if levels from input are decimals, total trancript should be multiplied by expr level, not divided
+        # poisson_sampled = np.random.poisson(total_transcript*expression_level)
+
+    #write output csv file containing transcript id and count (representative transcript numbers)
+
+    transcript_numbers = pd.DataFrame({'id': transcript['id'],'count': levels})
+    pd.DataFrame.to_csv(transcript_numbers, "representative_transcript_numbers.csv")
+
+
+'''
+This function writes keeps the representative transcripts from the original input file (gtf)
+and writes them to an output.
+'''
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