diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 61961d58c63a045ccb55e7426f53d6001180ccad..304d7c4aaf0ab0320455d66fc3f3e61a6a519f57 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -6,6 +6,5 @@ default:
my_tests:
# Good to put a small description here of what this job does
script:
- - pip install -r requirements_dev.txt
- - black cdna
+ - pip install -e -r requirements_dev.txt
- pylint cdna
diff --git a/cdna/cdna.py b/cdna/cdna.py
index 326d90584a7d616329e0191378142d423bc61115..c88b39188b859fa0315b4585154405b2895c3ff5 100644
--- a/cdna/cdna.py
+++ b/cdna/cdna.py
@@ -45,6 +45,9 @@ def seq_compliment(sequence: str) -> str:
class CDNAGen:
+ """
+ Module that performs the cDNA synthesis.
+ """
def __init__(self, ifasta: str, igtf: str, icpn: str, ofasta: str, ocsv: str):
# inputs
self.fasta = ifasta
@@ -56,7 +59,7 @@ class CDNAGen:
# variables
self.fasta_dict = None
self.fasta_records = None
- self.df_input_GTF = None
+ self.gtf_df = None
self.run()
def run(self) -> None:
@@ -77,7 +80,7 @@ class CDNAGen:
def add_records(self) -> None:
self.fasta_records = []
- for index, row in self.df_input_GTF.iterrows():
+ for index, row in self.gtf_df.iterrows():
if row["compliment"] is not None:
copy_number = row["Transcript_Copy_Number"]
record = SeqRecord(
@@ -94,7 +97,7 @@ class CDNAGen:
Returns: None
"""
- self.df_input_GTF["priming_site"] = self.df_input_GTF.apply(
+ self.gtf_df["priming_site"] = self.gtf_df.apply(
lambda row: self.read_primingsite(row["seqname"], row["start"]),
axis=1,
)
@@ -105,7 +108,7 @@ class CDNAGen:
Returns: None
"""
- self.df_input_GTF["compliment"] = self.df_input_GTF["priming_site"].apply(
+ self.gtf_df["compliment"] = self.gtf_df["priming_site"].apply(
lambda x: seq_compliment(x)
)
@@ -147,11 +150,11 @@ class CDNAGen:
Returns: None
"""
- df_input_CSV = pd.read_csv(self.cpn, index_col=False)
- df_input_CSV = (
- df_input_CSV.reset_index()
+ df_csv = pd.read_csv(self.cpn, index_col=False)
+ df_csv = (
+ df_csv.reset_index()
) # make sure indexes pair with number of rows
- self.df_input_CSV = df_input_CSV
+ self.csv_df = df_csv
def read_gtf(self) -> None:
"""Read and process the GTF file.
@@ -163,43 +166,43 @@ class CDNAGen:
"""
# returns GTF with essential columns such as "feature", "seqname", "start", "end"
# alongside the names of any optional keys which appeared in the attribute column
- df_input_GTF = read_gtf(self.gtf)
- df_input_GTF["Binding_Probability"] = pd.to_numeric(
- df_input_GTF["Binding_Probability"]
+ gtf_df = read_gtf(self.gtf)
+ gtf_df["Binding_Probability"] = pd.to_numeric(
+ gtf_df["Binding_Probability"]
) # convert to numeric
- df_normalization_bind_probablility = df_input_GTF.groupby("seqname")[
+ df_normalization_bind_probablility = gtf_df.groupby("seqname")[
"Binding_Probability"
- ].sum() # extract binding probablility
+ ].sum() # extract binding probability
count = 0
prev_id = None
# Adds Normalized_Binding_Probability and Transcript_Copy_Number to each transcript in the dataframe
- for index, row in df_input_GTF.iterrows():
+ for index, row in gtf_df.iterrows():
# GTF transcript ID
- id_GTF = str(row["seqname"])
- if id_GTF == prev_id:
+ id_ = str(row["seqname"])
+ if id_ == prev_id:
count += 1
else:
prev_id = None
count = 0
# CVS transcript ID
- id_CSV = str(row["seqname"]).split("_")[1]
+ id_csv = str(row["seqname"]).split("_")[1]
# Calculate Normalized_Binding_Probability and add to GTF dataframe
- df_input_GTF.loc[index, "Normalized_Binding_Probability"] = (
- row["Binding_Probability"] / df_normalization_bind_probablility[id_GTF]
+ gtf_df.loc[index, "Normalized_Binding_Probability"] = (
+ row["Binding_Probability"] / df_normalization_bind_probablility[id_]
)
# Calculate Normalized_Binding_Probability and add to GTF dataframe
- csv_transcript_copy_number = self.df_input_CSV.loc[
- self.df_input_CSV["ID of transcript"] == int(id_CSV),
+ csv_transcript_copy_number = self.csv_df.loc[
+ self.csv_df["ID of transcript"] == int(id_csv),
"Transcript copy number",
].iloc[0]
- df_input_GTF.loc[index, "Transcript_Copy_Number"] = round(
+ gtf_df.loc[index, "Transcript_Copy_Number"] = round(
csv_transcript_copy_number
- * df_input_GTF.loc[index, "Normalized_Binding_Probability"]
+ * gtf_df.loc[index, "Normalized_Binding_Probability"]
)
- df_input_GTF.loc[index, "cdna_ID"] = f"{id_GTF}_{count}"
- prev_id = id_GTF
+ gtf_df.loc[index, "cdna_ID"] = f"{id_}_{count}"
+ prev_id = id_
- self.df_input_GTF = df_input_GTF
+ self.gtf_df = gtf_df
def write_fasta(self) -> None:
"""Writes cDNA fasta records to file.
@@ -220,7 +223,7 @@ class CDNAGen:
Returns: None
"""
- self.df_input_GTF[["cdna_ID", "Transcript_Copy_Number"]].to_csv(
+ self.gtf_df[["cdna_ID", "Transcript_Copy_Number"]].to_csv(
self.output_csv, index=False
)
print(f"Copy number csv file successfully written to: {self.output_csv}")
diff --git a/cdna/cli.py b/cdna/cli.py
index e8e2cd7e3ab674cf8ed90a7b8b2c8cdb077bbeac..daf4ebfa6f28756705687aa161f5a633476af8f3 100644
--- a/cdna/cli.py
+++ b/cdna/cli.py
@@ -4,7 +4,14 @@ import logging
from cdna import CDNAGen
-def parser():
+def parser() -> None:
+ """ Parser for cDNA generator
+
+ Parses command line arguments for cDNA generation.
+
+ Returns: None
+
+ """
parser = argparse.ArgumentParser(
prog="cDNA generator",
description="Generate cDNA sequences based on primer probabilities.",
@@ -48,4 +55,4 @@ if __name__ == "__main__":
print("**********************")
print("Running cDNA generator")
print("**********************")
- cnda_object = parser()
+ parser()