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Add Scramble metrics to the qc table generated in EvidenceQC #702

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Add Scramble metrics to the qc table generated in EvidenceQC #702

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43a92ce
ammend make_evidence_qc_table.py to add scramble metrics to the qc ta…
kirtanav98 Aug 1, 2024
d2ece9f
address linting issue
kirtanav98 Aug 1, 2024
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31 changes: 25 additions & 6 deletions src/sv-pipeline/scripts/make_evidence_qc_table.py
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Original file line number Diff line number Diff line change
Expand Up @@ -117,12 +117,13 @@ def read_outlier(filename: str, outlier_col_label: str) -> pd.DataFrame:
return outlier_df


def read_all_outlier(outlier_manta_df: pd.DataFrame, outlier_melt_df: pd.DataFrame, outlier_wham_df: pd.DataFrame, outlier_type: str) -> pd.DataFrame:
def read_all_outlier(outlier_manta_df: pd.DataFrame, outlier_melt_df: pd.DataFrame, outlier_wham_df: pd.DataFrame, outlier_scramble_df: pd.DataFrame, outlier_type: str) -> pd.DataFrame:
"""
Args:
outlier_manta_df: Outliers determined in EvidenceQC for Manta.
outlier_melt_df: Outliers determined in EvidenceQC for MELT.
outlier_wham_df: Outliers determined in EvidenceQC for Wham.
outlier_scramble_df: Outliers determined in EvidenceQC for Scramble
outlier_type: high or low. Determined in EvidenceQC for each of the three callers.
Returns:
The total number of times that a sample appears as an outlier
Expand All @@ -140,8 +141,12 @@ def read_all_outlier(outlier_manta_df: pd.DataFrame, outlier_melt_df: pd.DataFra
col_name = get_col_name("wham", outlier_type)
dict_wham = dict(zip(outlier_wham_df[ID_COL], outlier_wham_df[col_name]))

# Scramble:
col_name = get_col_name("scramble", outlier_type)
dict_scramble = dict(zip(outlier_scramble_df[ID_COL], outlier_scramble_df[col_name]))

# merging all the dictionaries
outlier_dicts = [dict_manta, dict_melt, dict_wham]
outlier_dicts = [dict_manta, dict_melt, dict_wham, dict_scramble]
merged_dicts = Counter()
for counted in outlier_dicts:
merged_dicts.update(counted)
Expand All @@ -162,9 +167,11 @@ def merge_evidence_qc_table(
filename_high_manta: str,
filename_high_melt: str,
filename_high_wham: str,
filename_high_scramble: str,
filename_low_manta: str,
filename_low_melt: str,
filename_low_wham: str,
filename_low_scramble: str,
filename_melt_insert_size: str,
output_prefix: str) -> None:
"""
Expand All @@ -178,17 +185,19 @@ def merge_evidence_qc_table(
df_manta_high_outlier = read_outlier(filename_high_manta, get_col_name("manta", "high"))
df_melt_high_outlier = read_outlier(filename_high_melt, get_col_name("melt", "high"))
df_wham_high_outlier = read_outlier(filename_high_wham, get_col_name("wham", "high"))
df_total_high_outliers = read_all_outlier(df_manta_high_outlier, df_melt_high_outlier, df_wham_high_outlier, "high")
df_scramble_high_outlier = read_outlier(filename_high_scramble, get_col_name("scramble", "high"))
df_total_high_outliers = read_all_outlier(df_manta_high_outlier, df_melt_high_outlier, df_wham_high_outlier, df_scramble_high_outlier, "high")
df_manta_low_outlier = read_outlier(filename_low_manta, get_col_name("manta", "low"))
df_melt_low_outlier = read_outlier(filename_low_melt, get_col_name("melt", "low"))
df_wham_low_outlier = read_outlier(filename_low_wham, get_col_name("wham", "low"))
df_total_low_outliers = read_all_outlier(df_manta_low_outlier, df_melt_low_outlier, df_wham_low_outlier, "low")
df_scramble_low_outlier = read_outlier(filename_low_scramble, get_col_name("scramble", "low"))
df_total_low_outliers = read_all_outlier(df_manta_low_outlier, df_melt_low_outlier, df_wham_low_outlier, df_scramble_low_outlier, "low")
df_melt_insert_size = read_melt_insert_size(filename_melt_insert_size)

# all data frames
dfs = [df_ploidy, df_bincov_median, df_wgd_scores, df_non_diploid, df_manta_high_outlier,
df_melt_high_outlier, df_wham_high_outlier, df_total_high_outliers,
df_manta_low_outlier, df_melt_low_outlier, df_wham_low_outlier, df_total_low_outliers,
df_melt_high_outlier, df_wham_high_outlier, df_scramble_high_outlier, df_total_high_outliers,
df_manta_low_outlier, df_melt_low_outlier, df_wham_low_outlier, df_scramble_low_outlier, df_total_low_outliers,
df_melt_insert_size]
for df in dfs:
df[ID_COL] = df[ID_COL].astype(object)
Expand Down Expand Up @@ -241,6 +250,14 @@ def main():
"-r", "--wham-qc-outlier-low-filename",
help="Sets the filename containing Wham QC outlier low.")

parser.add_argument(
"-x", "--scramble-qc-outlier-low-filename",
help="Sets the filename containing Scramble QC outlier low.")

parser.add_argument(
"-t", "--scramble-qc-outlier-high-filename",
help="Sets the filename containing Scramble QC outlier high.")

parser.add_argument(
"-m", "--melt-insert-size-filename",
help="Sets the filename containing Melt insert size. "
Expand All @@ -263,9 +280,11 @@ def main():
args.manta_qc_outlier_high_filename,
args.melt_qc_outlier_high_filename,
args.wham_qc_outlier_high_filename,
args.scramble_qc_outlier_high_filename,
args.manta_qc_outlier_low_filename,
args.melt_qc_outlier_low_filename,
args.wham_qc_outlier_low_filename,
args.scramble_qc_outlier_low_filename,
args.melt_insert_size_filename,
args.output_prefix)

Expand Down
2 changes: 2 additions & 0 deletions wdl/EvidenceQC.wdl
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Original file line number Diff line number Diff line change
Expand Up @@ -246,9 +246,11 @@ task MakeQcTable {
~{"--manta-qc-outlier-high-filename " + manta_qc_high} \
~{"--melt-qc-outlier-high-filename " + melt_qc_high} \
~{"--wham-qc-outlier-high-filename " + wham_qc_high} \
~{"--scramble-qc-outlier-high-filename " + scramble_qc_high} \
~{"--manta-qc-outlier-low-filename " + manta_qc_low} \
~{"--melt-qc-outlier-low-filename " + melt_qc_low} \
~{"--wham-qc-outlier-low-filename " + wham_qc_low} \
~{"--scramble-qc-outlier-low-filename " + scramble_qc_low} \
~{if (length(melt_insert_size) > 0) then "--melt-insert-size mean_insert_size.tsv" else ""} \
~{"--output-prefix " + output_prefix}
>>>
Expand Down
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