From 6e73fade89cfa018d0f988bc37aa7c921bd1c7ff Mon Sep 17 00:00:00 2001
From: Fontrodona Nicolas <nicolas.fontrodona@ens-lyon.fr>
Date: Mon, 25 Jan 2021 17:24:33 +0100
Subject: [PATCH] src/find_interaction_cluster/clip_figures/clip_analyser.py:
change in add_regulation_column to display if the gene contains an exons
regulated by a splicing factor rather than the proportion of regulated exon
inside each gene
---
.../clip_figures/clip_analyser.py | 16 ++++++++++------
1 file changed, 10 insertions(+), 6 deletions(-)
diff --git a/src/find_interaction_cluster/clip_figures/clip_analyser.py b/src/find_interaction_cluster/clip_figures/clip_analyser.py
index 96318279..5e53c78c 100644
--- a/src/find_interaction_cluster/clip_figures/clip_analyser.py
+++ b/src/find_interaction_cluster/clip_figures/clip_analyser.py
@@ -240,8 +240,8 @@ def select_community_file(project: str, weight: int, global_weight: int,
def add_regulation_column(df_table: pd.DataFrame, sf_name: str, feature: str,
) -> pd.DataFrame:
"""
- Add a column community_data on df_table corresponding to the mean \
- number of exons regulated in each gene if feature is gene or 1 if \
+ Add a column community_data on df_table corresponding to 1 \
+ if an exon is regulated in a gene (0 elseà if feature is gene or 1 if \
the exon is regulated.
:param df_table: A dataframe containing the peak density for each gene \
@@ -263,9 +263,9 @@ def add_regulation_column(df_table: pd.DataFrame, sf_name: str, feature: str,
... 'community': ['C1', 'C1', 'C2']}
>>> add_regulation_column(pd.DataFrame(dgene), 'TRA2A_B', 'gene')
id_gene clip_peak peak_density community community_data
- 0 11553 0 0.0 C1 0.117647
- 1 3222 1 0.1 C1 0.020408
- 2 1001 0 0.0 C2 0.000000
+ 0 11553 0 0.0 C1 1
+ 1 3222 1 0.1 C1 1
+ 2 1001 0 0.0 C2 0
>>> add_regulation_column(pd.DataFrame(dgene), 'TRAgdghfh', 'gene')
id_gene clip_peak peak_density community
0 11553 0 0.0 C1
@@ -291,7 +291,7 @@ def add_regulation_column(df_table: pd.DataFrame, sf_name: str, feature: str,
df["community_data"] = [0] * df.shape[0]
df.loc[df["id_exon"].isin(exons), "community_data"] = 1
df.drop("id_exon", axis=1, inplace=True)
- df = df.groupby("id_gene").mean().reset_index()
+ df = df.groupby("id_gene").max().reset_index()
df_table = df_table.merge(df, how="left", on="id_gene")
return df_table
@@ -386,3 +386,7 @@ def clip_folder_analysis(clip_folder: Path, project: str, weight: int,
community_file, sl_reg]
processes.append(pool.apply_async(create_figure, args))
[p.get(timeout=None) for p in processes]
+
+if __name__ == "__main__":
+ import doctest
+ doctest.testmod()
\ No newline at end of file
--
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