diff --git a/src/bed_handler/__main__.py b/src/bed_handler/__main__.py
index 32ae9c689aa1a446b812bc8d32b60ebbff260690..4f87f0c1e89a50b46615fd487fd9e6d0b09094ad 100644
--- a/src/bed_handler/__main__.py
+++ b/src/bed_handler/__main__.py
@@ -9,12 +9,14 @@ visualisation
from .filter_gene import create_filtered_bed
from .get_gene_locations import create_region_bed
+from .get_gene_regulated_by_ddx import write_regulated_gene_file
def launcher():
"""
Create the necessary bed file to visualise bigwig file
"""
+ write_regulated_gene_file()
create_filtered_bed()
create_region_bed()
diff --git a/src/bed_handler/config.py b/src/bed_handler/config.py
index e5316a5801eaebb7593811dd6d23ef167c9283b6..69b49e39a87772870be848f6045e8ec9338ec991 100644
--- a/src/bed_handler/config.py
+++ b/src/bed_handler/config.py
@@ -19,6 +19,7 @@ class OutputBed:
tss_gene = output / "tss_gene.bed"
tts_gene = output / "tts_gene.bed"
after_gene = output / "after_gene.bed"
+ ddx_genes = output / "DDX5_17_genes.txt"
class BedConfig:
@@ -26,9 +27,9 @@ class BedConfig:
A class containing all the variables used in this submodule
"""
base = Path(__file__).parents[2]
- ddx_genes = base / "data" / "DDX5_17_genes.txt"
gene_bed = base / "data" / "bed" / "gene.bed"
exon_bed = base / "data" / "bed" / "exon.bed"
+ sipp_vs_ctcf = base / "data" / "Sipp_exon_vs_CTCF.csv"
bed = OutputBed
size = 5000
@@ -39,4 +40,5 @@ class TestConfig:
list_genes = base / "list_genes.txt"
gene_bed = base / "genes.bed"
exon_bed = base / "exons.bed"
- small_bw = base / "small.bw"
\ No newline at end of file
+ small_bw = base / "small.bw"
+ sipp_vs_ctcf = base / 'Sipp_exon_vs_CTCF.csv'
\ No newline at end of file
diff --git a/src/bed_handler/filter_gene.py b/src/bed_handler/filter_gene.py
index 0918807d908807687b898d8999699f8dbd8cc51d..944e72c656dc442a3c7e32acc807e8e5988579e2 100644
--- a/src/bed_handler/filter_gene.py
+++ b/src/bed_handler/filter_gene.py
@@ -51,9 +51,8 @@ def create_filtered_bed() -> None:
"""
Create a bed file containing only the genes of interest.
"""
- gene_list = select_gene_of_interest(BedConfig.ddx_genes)
+ gene_list = select_gene_of_interest(BedConfig.bed.ddx_genes)
df = filter_bed(BedConfig.gene_bed, gene_list)
- BedConfig.bed.output.mkdir(exist_ok=True, parents=True)
df.to_csv(BedConfig.bed.filtered_gene, sep="\t", index=False)
diff --git a/src/bed_handler/get_gene_regulated_by_ddx.py b/src/bed_handler/get_gene_regulated_by_ddx.py
new file mode 100644
index 0000000000000000000000000000000000000000..b48e5b281ca944aa984d4d668d44d576211d9b7f
--- /dev/null
+++ b/src/bed_handler/get_gene_regulated_by_ddx.py
@@ -0,0 +1,110 @@
+#!/usr/bin/env python3
+
+# -*- coding: UTF-8 -*-
+
+"""
+Description: The goal of this script is to get genes regulated by \
+DDX5/17
+"""
+
+from .config import BedConfig, TestConfig
+from pathlib import Path
+import pandas as pd
+from doctest import testmod
+from typing import List
+
+
+def format_exon_bed(exon_bed: Path, gene_bed: Path) -> pd.DataFrame:
+ """
+
+ :param exon_bed: A bed file containing fasterDB exons
+ :param gene_bed: A bed file containing fasterDB genes
+ :return: A dataframe of exon with it's coordinate id + it's \
+ id corresponding to it's gene id and it's position within the gene
+
+ >>> format_exon_bed(TestConfig.exon_bed, TestConfig.gene_bed)
+ exon_id id gene_id gene_name exon_pos exon_name
+ 0 18:28681866-28682388 1_1 1 DSC2 1 DSC2_1
+ 1 18:28681184-28681432 1_2 1 DSC2 2 DSC2_2
+ 2 18:28673522-28673606 1_3 1 DSC2 3 DSC2_3
+ 3 18:28672064-28672263 1_4 1 DSC2 4 DSC2_4
+ 4 18:28671490-28671530 1_5 1 DSC2 5 DSC2_5
+ 5 18:28670991-28671110 1_6 1 DSC2 6 DSC2_6
+ 6 18:28669402-28669557 1_7 1 DSC2 7 DSC2_7
+ 7 18:28667632-28667776 1_8 1 DSC2 8 DSC2_8
+ 8 18:28666539-28666705 1_9 1 DSC2 9 DSC2_9
+ """
+ exon_bed = pd.read_csv(exon_bed, sep="\t")
+ exon_bed['exon_id'] = exon_bed['#ref'].astype(str) + ':' + \
+ (exon_bed['start'] + 1).astype(str) + '-' + \
+ exon_bed['end'].astype(str)
+ exon_bed['gene_id'] = exon_bed['id'].str.replace(r'_\d+', '').astype(int)
+ exon_bed['exon_pos'] = exon_bed['id'].str.replace(r'\d+_', '').astype(int)
+ df_gene = pd.read_csv(gene_bed, sep="\t")[["id", "score"]]
+ df_gene.columns = ['gene_id', 'gene_name']
+ exon_bed = exon_bed.merge(df_gene, how="left", on=['gene_id'])
+ exon_bed['exon_name'] = exon_bed['gene_name'] + "_" + \
+ exon_bed['exon_pos'].astype(str)
+ return exon_bed[['exon_id', 'id', 'gene_id', 'gene_name', 'exon_pos',
+ 'exon_name']]
+
+
+def load_sipp_vs_ctct(sipp_file: Path, exon_table: pd.DataFrame
+ ) -> pd.DataFrame:
+ """
+ Load the file containing exons regulated by DDX5 17 and containing their \
+ distance to CTCF. Finaly merge this table to `exon_table` to get \
+ aditional data
+
+ :param sipp_file:file containing exons regulated by DDX5 17 and \
+ containing their distance to CTCF.
+ :return: Same input table as a dataframe
+
+ >>> df = load_sipp_vs_ctct(TestConfig.sipp_vs_ctcf,
+ ... format_exon_bed(TestConfig.exon_bed, TestConfig.gene_bed))
+ >>> df[['exon_name', "exon_id", 'group', 'id', 'gene_id']]
+ exon_name exon_id group id gene_id
+ 0 DSC2_1 18:28681866-28682388 siPP_DOWN 1_1 1
+ 1 DSC2_2 18:28681184-28681432 siPP_DOWN 1_2 1
+ 2 DSC2_3 18:28673522-28673606 siPP_DOWN 1_3 1
+ 3 DSC2_4 18:28672064-28672263 siPP_UP 1_4 1
+ 4 DSC2_5 18:28671490-28671530 siPP_DOWN 1_5 1
+ 5 DSC2_6 18:28670991-28671110 siPP_DOWN 1_6 1
+ 6 DSC2_7 18:28669402-28669557 siPP_DOWN 1_7 1
+ 7 DSC2_8 18:28667632-28667776 siPP_DOWN 1_8 1
+ 8 DSC2_9 18:28666539-28666705 siPP_DOWN 1_9 1
+ """
+ df = pd.read_csv(sipp_file, sep="\t")
+ return df.merge(exon_table, how="left", on=["exon_id", "exon_name"])
+
+
+def get_ddx_genes(df: pd.DataFrame) -> List[int]:
+ """
+ Return the unique values in gene_id column.
+
+ :param df: A dataframe of DDX regulated exons
+ :return: Return the unique values in gene_id column.
+
+ >>> df = load_sipp_vs_ctct(TestConfig.sipp_vs_ctcf,
+ ... format_exon_bed(TestConfig.exon_bed, TestConfig.gene_bed))
+ >>> get_ddx_genes(df)
+ [1]
+ """
+ return list(df['gene_id'].unique())
+
+
+def write_regulated_gene_file():
+ """
+ Write file file containing the regulated exons by DDX5/17
+ """
+ BedConfig.bed.output.mkdir(exist_ok=True, parents=True)
+ exon_table = format_exon_bed(BedConfig.exon_bed, BedConfig.gene_bed)
+ final_table = load_sipp_vs_ctct(BedConfig.sipp_vs_ctcf, exon_table)
+ list_gene = get_ddx_genes(final_table)
+ with BedConfig.bed.ddx_genes.open('w')as outfile:
+ for gene in list_gene:
+ outfile.write(f"{gene}\n")
+
+
+if __name__ == "__main__":
+ testmod()
diff --git a/tests/files/Sipp_exon_vs_CTCF.csv b/tests/files/Sipp_exon_vs_CTCF.csv
new file mode 100644
index 0000000000000000000000000000000000000000..d42cf046bd7214f74d0dab106795d571479c8ad4
--- /dev/null
+++ b/tests/files/Sipp_exon_vs_CTCF.csv
@@ -0,0 +1,10 @@
+exon_name dist exon_id CTCF_hit_id group strand deltaPSI
+DSC2_1 1 18:28681866-28682388 18:28681866-28682388 siPP_DOWN - -0.33
+DSC2_2 2 18:28681184-28681432 18:28681184-28681432 siPP_DOWN + -0.23
+DSC2_3 3 18:28673522-28673606 18:28673522-28673606 siPP_DOWN + -0.17
+DSC2_4 4 18:28672064-28672263 18:28672064-28672263 siPP_UP - 0.20
+DSC2_5 5 18:28671490-28671530 18:28671490-28671530 siPP_DOWN - -0.17
+DSC2_6 6 18:28670991-28671110 18:28670991-28671110 siPP_DOWN - -0.49
+DSC2_7 7 18:28669402-28669557 18:28669402-28669557 siPP_DOWN + -0.32
+DSC2_8 8 18:28667632-28667776 18:28667632-28667776 siPP_DOWN - -0.32
+DSC2_9 9 18:28666539-28666705 18:28666539-28666705 siPP_DOWN - -0.14