| name | alignment-and-mapping |
| description | Workflow for read alignment, sorting, indexing, mapping statistics, and downstream-ready alignment artifacts. |
| tool_type | mixed |
| primary_tool | samtools |
Alignment And Mapping
Version Compatibility
Reference examples assume recent stable releases of the preferred tools, especially samtools and the other tools listed below.
Before using code or command patterns, verify installed versions match the environment:
- Python:
python -c "import <module>; print(<module>.__version__)"
- CLI:
<tool> --version
- If signatures differ, inspect the installed help or API and adapt the pattern instead of retrying unchanged.
Overview
Workflow for read alignment, sorting, indexing, mapping statistics, and downstream-ready alignment artifacts.
When To Use This Skill
- use when the task is sequence alignment or alignment file preparation
- use when FASTQ files must be mapped to a genome or transcriptome
- use when BAM or CRAM files and mapping metrics are the expected outputs
Quick Route
- If the input is raw or minimally processed data, start with validation and QC before any modeling.
- If the input is already processed, skip directly to the first workflow step that matches the user goal.
- If the user asks for a biological conclusion, always produce at least one QC or confidence artifact alongside the final result.
Progressive Disclosure
- Read
references/technical_reference.md when you need deeper tool-selection rules, environment adaptation notes, or extra validation guidance.
- Keep
SKILL.md as the main execution path and load the reference file only when the task or failure mode needs the extra detail.
Default Rules
- Prefer Python-first workflows unless the task explicitly requires something else.
- Keep intermediate and final outputs separated.
- Record software versions, reference builds, and key parameters when they affect interpretation.
- Favor reproducible tables and figures over one-off interactive-only outputs.
Expected Inputs
- FASTQ files
- reference genome or transcriptome
- alignment indexes
Expected Outputs
- sorted and indexed alignments
- mapping metrics
- downstream-ready BAM or CRAM files
Preferred Tools
- bwa
- bowtie2
- hisat2
- STAR
- samtools
- pysam
Starter Pattern
bwa mem ref.fa sample_R1.fastq.gz sample_R2.fastq.gz | samtools sort -o sample.bam
samtools index sample.bam
samtools flagstat sample.bam > sample.flagstat.txt
Workflow
1. Choose the mapper
Match the aligner to DNA, RNA, read length, and splice-awareness needs.
2. Run alignment reproducibly
Capture all parameters that influence multi-mapping, splicing, and scoring.
3. Post-process alignments
Sort, index, mark or handle duplicates as appropriate, and compute mapping summaries.
4. Check mapping quality
Review alignment rate, insert sizes, and reference compatibility before downstream analysis.
5. Export standard artifacts
Save BAM or CRAM plus indexes and mapping reports.
Output Artifacts
- Recommended output layout:
results/ for final tables and serialized objects
figures/ for plots and static visual exports
qc/ for checks that justify downstream interpretation
- Minimum expected outputs for this skill:
sorted and indexed alignments
mapping metrics
downstream-ready BAM or CRAM files
Quality Review
- Confirm identifiers and metadata join correctly before modeling or summarizing.
- Generate at least one QC artifact before final biological interpretation.
- Keep raw or minimally processed inputs separate from transformed outputs.
- Confirm reference build, read-group metadata, and sort or index state before downstream analysis.
- Review mapping summaries before treating alignments as analysis-ready.
Anti-Patterns
- using a DNA aligner for splice-aware RNA tasks without justification
- forgetting sort and index steps before downstream tools
- dropping read-group or sample metadata needed later
Related Skills
Sequence And Format IO
Read QC
Database Access
Reporting And Figure Export
Optional Supplements