diff --git a/sequence_extractor/preBedtools_new.py b/sequence_extractor/preBedtools_new.py
new file mode 100644
index 0000000000000000000000000000000000000000..0796e8bcc919b02a2360780cffded23b3d56c551
--- /dev/null
+++ b/sequence_extractor/preBedtools_new.py
@@ -0,0 +1,28 @@
+import pandas as pd
+from gtfparse import read_gtf
+
+"""This script defines a BED from exon annotation in a GTF, to get sequences with transcript ID as header after usage in bedtools.
+
+    For each transcript, take exons only and sort exons by start position (reverse order for -ve strand)
+    Input: GTF file 
+    Columns needed for BED: chr, start, end, transcript_id, score, strand, gene_id
+    ...
+    :returns: BED file format
+    :rtype: dataframe
+    """
+
+
+gtf = read_gtf('../scrna-seq-simulation-main/inputs/ref_annotation.gtf')
+
+gtf_exons = gtf[gtf["feature"] == "exon"]
+
+gtf_exons = gtf_exons[["seqname", "start", "end", "transcript_id", "score", "strand", "gene_id"]]
+
+gtf_df_neg = gtf_exons[gtf_exons["strand"] == "-"]
+gtf_df_neg = gtf_df_neg.sort_values(['transcript_id','start'],ascending=False).groupby('transcript_id').head(len(gtf_df_neg. transcript_id))
+
+gtf_df_pos = gtf_exons[gtf_exons["strand"] == "+"]
+gtf_df_pos = gtf_df_pos.sort_values(['transcript_id','start'],ascending=True).groupby('transcript_id').head(len(gtf_df_pos. transcript_id))
+
+pd.concat([gtf_df_pos, gtf_df_neg]).to_csv("bed_file.bed",sep="\t",index=False) #gtf_df_pos and gtf_df_neg must be dataframes
+