From 2cd7037bbe9317a630ae537c7ec3e58e3bf42d49 Mon Sep 17 00:00:00 2001
From: Fontrodona Nicolas <nicolas.fontrodona@ens-lyon.fr>
Date: Fri, 23 Oct 2020 16:12:40 +0200
Subject: [PATCH] src.bed_handler: creation of bed of regulated exons by
DDX5/17
---
src/bed_handler/__main__.py | 8 ++
src/bed_handler/get_gene_regulated_by_ddx.py | 8 +-
.../select_regulated_near_ctcf_exons.py | 122 ++++++++++++++++++
3 files changed, 134 insertions(+), 4 deletions(-)
create mode 100644 src/bed_handler/select_regulated_near_ctcf_exons.py
diff --git a/src/bed_handler/__main__.py b/src/bed_handler/__main__.py
index 4f87f0c..79bc3dc 100644
--- a/src/bed_handler/__main__.py
+++ b/src/bed_handler/__main__.py
@@ -10,6 +10,7 @@ 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
+from .select_regulated_near_ctcf_exons import create_bed_ctcf_exon
def launcher():
@@ -19,6 +20,13 @@ def launcher():
write_regulated_gene_file()
create_filtered_bed()
create_region_bed()
+ create_bed_ctcf_exon("down", 0, "both")
+ create_bed_ctcf_exon("down", 1000, "both")
+ create_bed_ctcf_exon("down", 2000, "both")
+ create_bed_ctcf_exon("down", 1000, "upstream")
+ create_bed_ctcf_exon("down", 2000, "upstream")
+ create_bed_ctcf_exon("down", 1000, "downstream")
+ create_bed_ctcf_exon("down", 2000, "downstream")
launcher()
diff --git a/src/bed_handler/get_gene_regulated_by_ddx.py b/src/bed_handler/get_gene_regulated_by_ddx.py
index b48e5b2..dd4b6f9 100644
--- a/src/bed_handler/get_gene_regulated_by_ddx.py
+++ b/src/bed_handler/get_gene_regulated_by_ddx.py
@@ -49,7 +49,7 @@ def format_exon_bed(exon_bed: Path, gene_bed: Path) -> pd.DataFrame:
'exon_name']]
-def load_sipp_vs_ctct(sipp_file: Path, exon_table: pd.DataFrame
+def load_sipp_vs_ctcf(sipp_file: Path, exon_table: pd.DataFrame
) -> pd.DataFrame:
"""
Load the file containing exons regulated by DDX5 17 and containing their \
@@ -60,7 +60,7 @@ def load_sipp_vs_ctct(sipp_file: Path, exon_table: pd.DataFrame
containing their distance to CTCF.
:return: Same input table as a dataframe
- >>> df = load_sipp_vs_ctct(TestConfig.sipp_vs_ctcf,
+ >>> df = load_sipp_vs_ctcf(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
@@ -85,7 +85,7 @@ def get_ddx_genes(df: pd.DataFrame) -> List[int]:
: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,
+ >>> df = load_sipp_vs_ctcf(TestConfig.sipp_vs_ctcf,
... format_exon_bed(TestConfig.exon_bed, TestConfig.gene_bed))
>>> get_ddx_genes(df)
[1]
@@ -99,7 +99,7 @@ def write_regulated_gene_file():
"""
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)
+ final_table = load_sipp_vs_ctcf(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:
diff --git a/src/bed_handler/select_regulated_near_ctcf_exons.py b/src/bed_handler/select_regulated_near_ctcf_exons.py
new file mode 100644
index 0000000..8c1bab0
--- /dev/null
+++ b/src/bed_handler/select_regulated_near_ctcf_exons.py
@@ -0,0 +1,122 @@
+#!/usr/bin/env python3
+
+# -*- coding: UTF-8 -*-
+
+"""
+Description: Create bed of exons regulated by DDX5/17 and near CTCF
+"""
+
+from .config import TestConfig, BedConfig
+from .get_gene_regulated_by_ddx import load_sipp_vs_ctcf, format_exon_bed
+import pandas as pd
+from doctest import testmod
+
+
+def filter_ctcf_distance_table(df: pd.DataFrame, reg: str, threshold: int,
+ location: str) -> pd.DataFrame:
+ """
+ Filter the dataframe to recover only regulated exons near CTCF.
+
+ :param df: The dataframe of exon regulated by CTCF
+ :param reg: The regulation by CTCF
+ :param threshold: The threshold distance
+ :param location: The location of interest
+ :return: The filtered dataframe
+
+ >>> cdf = load_sipp_vs_ctcf(TestConfig.sipp_vs_ctcf,
+ ... format_exon_bed(TestConfig.exon_bed, TestConfig.gene_bed))
+ >>> rdf = filter_ctcf_distance_table(cdf, 'down', 4, 'upstream')
+ >>> rdf[['exon_name', 'dist', 'group', 'id']]
+ exon_name dist group id
+ 0 DSC2_1 -4 siPP_DOWN 1_1
+ 1 DSC2_2 -3 siPP_DOWN 1_2
+ 2 DSC2_3 -2 siPP_DOWN 1_3
+ 4 DSC2_5 0 siPP_DOWN 1_5
+ >>> rdf = filter_ctcf_distance_table(cdf, 'down', 2, 'upstream')
+ >>> rdf[['exon_name', 'dist', 'group', 'id']]
+ exon_name dist group id
+ 2 DSC2_3 -2 siPP_DOWN 1_3
+ 4 DSC2_5 0 siPP_DOWN 1_5
+ >>> rdf = filter_ctcf_distance_table(cdf, 'down', 2, 'downstream')
+ >>> rdf[['exon_name', 'dist', 'group', 'id']]
+ exon_name dist group id
+ 4 DSC2_5 0 siPP_DOWN 1_5
+ 5 DSC2_6 1 siPP_DOWN 1_6
+ 6 DSC2_7 2 siPP_DOWN 1_7
+ >>> rdf = filter_ctcf_distance_table(cdf, 'down', 2, 'both')
+ >>> rdf[['exon_name', 'dist', 'group', 'id']]
+ exon_name dist group id
+ 2 DSC2_3 -2 siPP_DOWN 1_3
+ 4 DSC2_5 0 siPP_DOWN 1_5
+ 5 DSC2_6 1 siPP_DOWN 1_6
+ 6 DSC2_7 2 siPP_DOWN 1_7
+ >>> rdf = filter_ctcf_distance_table(cdf, 'up', 2, 'both')
+ >>> rdf[['exon_name', 'dist', 'group', 'id']]
+ exon_name dist group id
+ 3 DSC2_4 -1 siPP_UP 1_4
+ >>> rdf = filter_ctcf_distance_table(cdf, 'up', 2, 'downstream')
+ >>> rdf[['exon_name', 'dist', 'group', 'id']]
+ Empty DataFrame
+ Columns: [exon_name, dist, group, id]
+ Index: []
+ >>> rdf = filter_ctcf_distance_table(cdf, 'all', 2, 'both')
+ >>> rdf[['exon_name', 'dist', 'group', 'id']]
+ exon_name dist group id
+ 2 DSC2_3 -2 siPP_DOWN 1_3
+ 3 DSC2_4 -1 siPP_UP 1_4
+ 4 DSC2_5 0 siPP_DOWN 1_5
+ 5 DSC2_6 1 siPP_DOWN 1_6
+ 6 DSC2_7 2 siPP_DOWN 1_7
+ >>> filter_ctcf_distance_table(cdf, 'lul', 2, 'both')
+ Traceback (most recent call last):
+ ...
+ ValueError: reg parameter should be one in: ['down', 'up', 'all']
+ >>> filter_ctcf_distance_table(cdf, 'up', 2, 'xd')
+ Traceback (most recent call last):
+ ...
+ ValueError: location parameter should be in ['upstream', \
+'downstream', 'both']
+ """
+ if reg not in ['down', 'up', 'all']:
+ raise ValueError(f"reg parameter should be one in: "
+ f"['down', 'up', 'all']")
+ if location not in ['upstream', 'downstream', 'both']:
+ raise ValueError(f"location parameter should be in "
+ f"['upstream', 'downstream', 'both']")
+ if reg != "all":
+ df = df.loc[df["group"] == f"siPP_{reg.upper()}", :]
+ if location == "upstream":
+ df = df.loc[(df["dist"] >= threshold * -1) &
+ (df["dist"] <= 0), :]
+ elif location == "downstream":
+ df = df.loc[(df["dist"] <= threshold) &
+ (df["dist"] >= 0), :]
+ else:
+ df = df.loc[abs(df["dist"]) <= threshold, :]
+ return df
+
+
+def create_bed_ctcf_exon(reg: str, threshold: int,
+ location: str) -> None:
+ """
+ Filter the dataframe to recover only regulated exons near CTCF.
+
+ :param reg: The regulation by CTCF
+ :param threshold: The threshold distance
+ :param location: The location of interest
+ """
+ if threshold < 0:
+ threshold = 0
+ if threshold == 0:
+ location = "both"
+ df = load_sipp_vs_ctcf(BedConfig.sipp_vs_ctcf,
+ format_exon_bed(BedConfig.exon_bed,
+ BedConfig.gene_bed))
+ df = filter_ctcf_distance_table(df, reg, threshold, location)
+ df.to_csv(BedConfig.bed.output / f"CTCF_{threshold}_{location}_"
+ f"ddx_{reg}_exon.bed", sep="\t",
+ index=False)
+
+
+if __name__ == "__main__":
+ testmod()
--
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