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Max shift plots #178

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7 changes: 7 additions & 0 deletions modules/local/combinebeds/shifts/environment.yml
Original file line number Diff line number Diff line change
@@ -0,0 +1,7 @@
channels:
- conda-forge
- bioconda
dependencies:
- conda-forge::polars=1.8.2
- conda-forge::altair=5.5.0
- conda-forge::vl-convert-python==1.7.0
21 changes: 21 additions & 0 deletions modules/local/combinebeds/shifts/main.nf
Original file line number Diff line number Diff line change
@@ -0,0 +1,21 @@
process COMBINEBEDS_SHIFTS {
tag "$meta.id"
label "process_low"

conda "${moduleDir}/environment.yml"
container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?
'oras://community.wave.seqera.io/library/altair_polars_vl-convert-python:e6f1dca28de76d13' :
'community.wave.seqera.io/library/altair_polars_vl-convert-python:a6c5ee679445250d' }"

input:
tuple val(meta), path(beds)

output:
path "*.png" , emit: plots
path "*.json" , emit: multiqc
path "versions.yml", emit: versions

script:
prefix = task.ext.prefix ?: "${meta.id}"
template "shifts.py"
}
120 changes: 120 additions & 0 deletions modules/local/combinebeds/shifts/templates/shifts.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,120 @@
#!/usr/bin/env python

import platform
import base64
import json
from itertools import product

import polars as pl
import altair as alt

def format_yaml_like(data: dict, indent: int = 0) -> str:
"""Formats a dictionary to a YAML-like string.

Args:
data (dict): The dictionary to format.
indent (int): The current indentation level.

Returns:
str: A string formatted as YAML.
"""
yaml_str = ""
for key, value in data.items():
spaces = " " * indent
if isinstance(value, dict):
yaml_str += f"{spaces}{key}:\\n{format_yaml_like(value, indent + 1)}"
else:
yaml_str += f"{spaces}{key}: {value}\\n"
return yaml_str

meta_id = "${meta.id}"

df = pl.scan_csv("${beds}".split(" "),
separator="\\t",
has_header=False,
new_columns=["chr", "start", "end", "name", "score", "strand", "sample", "tool"])

df = df.group_by("chr", "start", "end", "strand").agg(tools=pl.col("tool").unique(), samples=pl.col("sample").unique())

def get_group_sizes(df: pl.LazyFrame, max_shift: int, consider_strand: bool) -> pl.LazyFrame:
df = df.sort("end" ).with_columns(end_group =pl.col("end" ).diff().fill_null(0).gt(max_shift).cum_sum())
df = df.sort("start").with_columns(start_group=pl.col("start").diff().fill_null(0).gt(max_shift).cum_sum())

group_cols = ["chr", "start_group", "end_group"] + (["strand"] if consider_strand else [])
df = df.join(df, on=group_cols, how="inner")
df = df.filter((pl.col("start") - pl.col("start_right")).abs() <= max_shift)
df = df.filter((pl.col("end") - pl.col("end_right")).abs() <= max_shift)
df = df.select(["chr", "start", "end", "strand", "samples_right", "tools_right"])
df = df.group_by(["chr", "start", "end", "strand"]).agg(**{
"samples": pl.col("samples_right").flatten().unique(),
"tools": pl.col("tools_right").flatten().unique()
}).with_columns(n_samples=pl.col("samples").map_elements(lambda x: len(x), return_dtype=int),
n_tools=pl.col("tools").map_elements(lambda x: len(x), return_dtype=int))

df_sample_counts = (df.group_by("n_samples").agg(count=pl.col("n_samples").count())
.sort("n_samples")
.rename({"n_samples": "value"})
.with_columns(metric=pl.lit("n_samples")))
df_tool_counts = (df.group_by("n_tools").agg(count=pl.col("n_tools").count())
.sort("n_tools")
.rename({"n_tools": "value"})
.with_columns(metric=pl.lit("n_tools")))

df = (pl.concat([df_sample_counts, df_tool_counts])
.with_columns(max_shift=max_shift, consider_strand=consider_strand))

return df

shifts = [0, 1, 2, 3, 4, 5, 10, 20, 50]
consider_strands = [True, False]

dfs = []
for max_shift, consider_strand in product(shifts, consider_strands):
df_ = get_group_sizes(df, max_shift, consider_strand)
dfs.append(df_.collect())

df = pl.concat(dfs).with_columns(max_shift=pl.col("max_shift"))

metrics = {
"n_samples": "Number of samples",
"n_tools": "Number of tools"
}

for metric, title in metrics.items():
n_unique = df.filter(pl.col("metric") == metric).select("value").n_unique("value")
df_ = df.filter(pl.col("metric") == metric)
plot = df_.plot.bar(x="max_shift:N", y="count", color=f"value:{("Q" if n_unique > 10 else "N")}", column="consider_strand")
plot = plot.properties(title=title)

plot_file = f"{metric}.png"
plot.save(plot_file)

image_string = base64.b64encode(open(plot_file, "rb").read()).decode("utf-8")
image_html = f'<div class="mqc-custom-content-image"><img src="data:image/png;base64,{image_string}" /></div>'

multiqc = {
'id': f"{meta_id}_shifts_{metric}",
'parent_id': "shift_plots",
'parent_name': 'Shift Plots',
'parent_description': 'Stacked bar plots showing the agreement between tools and samples for different shift values',
'section_name': title,
'description': f'Stacked bar plot showing the agreement between tools and samples for different shift values, {"considering" if consider_strand else "ignoring"} strand',
'plot_type': 'image',
'data': image_html
}

with open(f"{metric}.shifts_mqc.json", "w") as f:
f.write(json.dumps(multiqc, indent=4))

# Versions

versions = {
"${task.process}": {
"python": platform.python_version(),
"polars": pl.__version__,
"altair": alt.__version__
}
}

with open("versions.yml", "w") as f:
f.write(format_yaml_like(versions))
15 changes: 12 additions & 3 deletions subworkflows/local/bsj_detection.nf
Original file line number Diff line number Diff line change
Expand Up @@ -4,9 +4,10 @@ include { CSVTK_JOIN as COMBINE_COUNTS_PER_TOOL } from '../../modules/n
include { GAWK as FILTER_BSJS } from '../../modules/nf-core/gawk'
include { GAWK as BED_ADD_SAMPLE_TOOL } from '../../modules/nf-core/gawk'
include { COMBINEBEDS_FILTER as COMBINE_TOOLS_PER_SAMPLE } from '../../modules/local/combinebeds/filter'
include { COMBINEBEDS_SHIFTS as INVESTIGATE_SHIFTS } from '../../modules/local/combinebeds/shifts'
include { COMBINEBEDS_FILTER as COMBINE_SAMPLES } from '../../modules/local/combinebeds/filter'
include { AGAT_SPADDINTRONS as ADD_INTRONS } from '../../modules/nf-core/agat/spaddintrons'
include { GAWK as EXTRACT_EXONS_INTRONS } from '../../modules/nf-core/gawk'
include { AGAT_SPADDINTRONS as ADD_INTRONS } from '../../modules/nf-core/agat/spaddintrons'
include { GAWK as EXTRACT_EXONS_INTRONS } from '../../modules/nf-core/gawk'
include { BEDTOOLS_GETFASTA as FASTA_COMBINED } from '../../modules/nf-core/bedtools/getfasta'
include { BEDTOOLS_GETFASTA as FASTA_PER_SAMPLE } from '../../modules/nf-core/bedtools/getfasta'
include { BEDTOOLS_GETFASTA as FASTA_PER_SAMPLE_TOOL } from '../../modules/nf-core/bedtools/getfasta'
Expand Down Expand Up @@ -148,8 +149,12 @@ workflow BSJ_DETECTION {
ch_bsj_bed_per_sample = COMBINE_TOOLS_PER_SAMPLE.out.combined
.filter{ meta, bed -> !bed.isEmpty() }

ch_all_samples = ch_bsj_bed_per_sample_tool_meta
.map{ meta, bed -> [[id: "all"], bed] }
.groupTuple()

COMBINE_SAMPLES(
ch_bsj_bed_per_sample_tool_meta.map{ meta, bed -> [[id: "all"], bed] }.groupTuple(),
ch_all_samples,
params.max_shift,
params.consider_strand,
params.min_tools,
Expand All @@ -160,6 +165,10 @@ workflow BSJ_DETECTION {
.filter{ meta, bed -> !bed.isEmpty() }
.collect()

INVESTIGATE_SHIFTS(ch_all_samples)
ch_versions = ch_versions.mix(INVESTIGATE_SHIFTS.out.versions)
ch_multiqc_files = INVESTIGATE_SHIFTS.out.multiqc

//
// ANNOTATION
//
Expand Down
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