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Ensure column ordering on get_mag_depths.py #911

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Merged
dialvarezs merged 3 commits into from
Nov 4, 2025
Merged

Ensure column ordering on get_mag_depths.py #911

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c9b49d3
Update get_mag_depths.py to ensure column ordering
dialvarezs Nov 4, 2025
79dae93
Update CHANGELOG
dialvarezs Nov 4, 2025
c5fd6b9
Update bin/get_mag_depths.py
dialvarezs Nov 4, 2025
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

- [#896](https://github.com/nf-core/mag/pull/896) - Remove obsolete execution command from README (by @dialvarezs)
- [#907](https://github.com/nf-core/mag/pull/907) - Include refined bins from all binners in the `DASTool/bins` output folder (by @AlexHoratio)
- [#911](https://github.com/nf-core/mag/pull/911) - Ensure column order is consistent when generating depth summaries to prevent swapped results on merged depth summary (by @dialvarezs)

### `Dependencies`

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107 changes: 47 additions & 60 deletions bin/get_mag_depths.py
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@@ -1,15 +1,14 @@
#!/usr/bin/env python

## Originally written by Sabrina Krakau and released under the MIT license.
## Originally written by Sabrina Krakau and updated by Diego Alvarez. Released under the MIT license.
## See git repository (https://github.com/nf-core/mag) for full license text.

import sys
import argparse
import os.path
import pandas as pd
import csv
import gzip
import os.path
import statistics
import sys

from Bio import SeqIO

Expand All @@ -29,17 +28,14 @@ def parse_args(args=None):
"--depths",
required=True,
metavar="FILE",
help="(Compressed) TSV file containing contig depths for each sample: contigName, contigLen, totalAvgDepth, sample1_avgDepth, sample1_var [, sample2_avgDepth, sample2_var, ...].",
)
parser.add_argument(
"-a", "--assembler", required=True, type=str, help="Assembler name."
)
parser.add_argument(
"-i", "--id", required=True, type=str, help="Sample or group id."
)
parser.add_argument(
"-m", "--binner", required=True, type=str, help="Binning method."
help=(
"Produces (compressed) TSV file containing contig depths for each sample: contigName, contigLen, "
+ "totalAvgDepth, sample1_avgDepth, sample1_var [, sample2_avgDepth, sample2_var, ...]."
),
)
parser.add_argument("-a", "--assembler", required=True, type=str, help="Assembler name.")
parser.add_argument("-i", "--id", required=True, type=str, help="Sample or group id.")
parser.add_argument("-m", "--binner", required=True, type=str, help="Binning method.")
return parser.parse_args(args)


Expand All @@ -53,57 +49,48 @@ def main(args=None):
sample_names = []
dict_contig_depths = {}
with gzip.open(args.depths, "rt") as infile:
reader = csv.reader(infile, delimiter="\t")
# process header
header = next(reader)
for sample in range(int((len(header) - 3) / 2)):
col_name = header[3 + 2 * sample]
reader = csv.DictReader(infile, delimiter="\t")
# process header to extract sample names from column names
depth_columns = []
for col_name in reader.fieldnames[3::2]: # Every 2nd column starting from index 3
# retrieve sample name: "<assembler>-<id>-<other sample_name>.bam"
sample_name = col_name[len(args.assembler) + 1 + len(args.id) + 1 : -4]
sample_names.append(sample_name)
depth_columns.append(col_name)
# process contig depths
for row in reader:
contig_depths = []
for sample in range(int((len(row) - 3) / 2)):
contig_depths.append(float(row[3 + 2 * sample]))
dict_contig_depths[str(row[0])] = contig_depths

# Initialize output files
n_samples = len(sample_names)
with open(
args.assembler + "-" + args.binner + "-" + args.id + "-binDepths.tsv", "w"
) as outfile:
print("bin", "\t".join(sample_names), sep="\t", file=outfile)

# for each bin, access contig depths and compute mean bin depth (for all samples)
for file in args.bins:
all_depths = [[] for i in range(n_samples)]

if file.endswith(".gz"):
with gzip.open(file, "rt") as infile:
for rec in SeqIO.parse(infile, "fasta"):
contig_depths = dict_contig_depths[rec.id]
for sample in range(n_samples):
all_depths[sample].append(contig_depths[sample])
else:
with open(file, "rt") as infile:
for rec in SeqIO.parse(infile, "fasta"):
contig_depths = dict_contig_depths[rec.id]
for sample in range(n_samples):
all_depths[sample].append(contig_depths[sample])

binname = os.path.basename(file)
with open(
args.assembler + "-" + args.binner + "-" + args.id + "-binDepths.tsv", "a"
) as outfile:
print(
binname,
"\t".join(
str(statistics.median(sample_depths))
for sample_depths in all_depths
),
sep="\t",
file=outfile,
contig_depths = {}
for sample_name, col_name in zip(sample_names, depth_columns):
contig_depths[sample_name] = float(row[col_name])
dict_contig_depths[row[reader.fieldnames[0]]] = contig_depths

sample_names = sorted(sample_names)

with open(f"{args.assembler}-{args.binner}-{args.id}-binDepths.tsv", "w") as outfile:
writer = csv.writer(outfile, delimiter="\t")
writer.writerow(["bin", *sample_names])

# for each bin, access contig depths and compute mean bin depth (for all samples)
for file in args.bins:
all_depths = {sample: [] for sample in sample_names}

if file.endswith(".gz"):
with gzip.open(file, "rt") as infile:
for rec in SeqIO.parse(infile, "fasta"):
contig_depths = dict_contig_depths[rec.id]
for sample in sample_names:
all_depths[sample].append(contig_depths[sample])
else:
with open(file, "rt") as infile:
for rec in SeqIO.parse(infile, "fasta"):
contig_depths = dict_contig_depths[rec.id]
for sample in sample_names:
all_depths[sample].append(contig_depths[sample])

binname = os.path.basename(file)

writer.writerow(
[binname, *[statistics.median(all_depths[sample]) for sample in sample_names]],
)


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