multiqc-mapper 0.2.2

Normalize MultiQC metrics across tools into a unified long-format table

multiqc-mapper

Normalize MultiQC metrics across tools into a unified long-format table.

MultiQC parses each tool independently. This package adds a semantic mapping layer so that equivalent metrics (e.g. "total reads" from samtools and RSeQC) resolve to a single canonical concept.

Install

uv add multiqc-mapper          # inside an existing uv project
uv tool install multiqc-mapper # as a standalone CLI tool

Quickstart

# 1. Auto-discover all metrics from a MultiQC output directory
multiqc-mapper discover ./multiqc_data -o concepts.yaml

# 2. Edit concepts.yaml — merge equivalent cross-tool metrics under one key

# 3. Validate the mapping is complete
multiqc-mapper validate ./multiqc_data concepts.yaml

# 4. Resolve to a unified long-format table
multiqc-mapper resolve ./multiqc_data concepts.yaml -o unified.tsv

Python API

from multiqc_mapper import ConceptRegistry, resolve

registry = ConceptRegistry.from_yaml("concepts.yaml")
df = resolve("./multiqc_data", registry)

# One row per (sample, concept, tool)
df[df["concept"] == "total_reads"]
#    sample     concept     tool              metric  val_raw unit
# ERR188383 total_reads samtools raw_total_sequences  98732.0 reads
# ERR188383 total_reads    rseqc       total_records 100826.0 reads

Output schema

column	description
sample	Sample name
concept	Canonical concept key from concepts.yaml
tool	Tool that reported this observation
anchor	MultiQC anchor (plot/table id)
section_key	MultiQC section key
metric	Original MultiQC metric key
val_raw	Raw numeric value
val_fmt	Formatted display string from MultiQC
unit	Unit from concept definition
title	Human-readable metric title
description	Metric description

concepts.yaml format

The mapping file is the single source of truth. Only anchor and metric under each source are used for resolution; all other fields are documentation.

version: "1.0"

concepts:
  total_reads:
    title: "Total reads"
    description: "Total reads in the BAM file"
    unit: reads
    category: alignment
    shared_key: read_count     # MultiQC shared_key (unit hint)
    notes: "samtools counts raw sequences; RSeQC counts BAM records"
    sources:
      - anchor: samtools-stats-dp
        metric: raw_total_sequences
        tool: samtools           # documentation only
        title: "Total sequences"
      - anchor: rseqc_bam_stat
        metric: total_records
        tool: rseqc
        title: "Total records"

To extend for a new tool: add a sources: entry to the relevant concept. To add a new concept: add a new top-level key under concepts:.

CLI reference

multiqc-mapper discover <multiqc_data_dir> [-o concepts.yaml]
multiqc-mapper resolve  <multiqc_data_dir> <concepts.yaml> [-o out.tsv] [--format tsv|csv|parquet] [--drop-unresolved]
multiqc-mapper validate <multiqc_data_dir> <concepts.yaml>
multiqc-mapper list-metrics <multiqc_data_dir> [--shared-key]

Requirements

• Python ≥ 3.9
• MultiQC ≥ 1.25 (parquet output required)