Agent skill · Workflow & Productivity

bio-workflows-fastq-to-variants

End-to-end DNA sequencing workflow from FASTQ files to variant calls. Covers QC, alignment with BWA, BAM processing, and variant calling with bcftools or GATK HaplotypeCaller. Use when calling variants from raw sequencing reads.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill fastq-to-variants --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 12 KB
Bundled scripts: yes
Path: skills/bioskills/fastq-to-variants/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

## Version Compatibility Reference examples tested with: BWA-MEM2 2.2.1+, Ensembl VEP 111+, GATK 4.5+, bcftools 1.19+, fastp 0.23+, samtools 1.19+ Before using code patterns, verify installed versions match. If versions differ: - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # FASTQ to Variants Workflow **"Call variants from my whole-genome or exome FASTQ files"** → Orchestrate fastp QC, BWA-MEM2 alignment, duplicate marking, BQSR, GATK HaplotypeCaller variant calling, and VQSR/hard filtering to produce filtered VCF output. Complete pipeline from raw DNA sequencing FASTQ files to filtered variant calls. ## Workflow Overview ``` FASTQ files | v [1. QC & Trimming] -----> fastp | v [2. Alignment] ---------> bwa-mem2 | v [3. BAM Processing] ----> sort, markdup, index | v [4. Variant Calling] ---> bcftools (primary) or GATK | v [5. Filtering] ---------> Quality filters | v Filtered VCF ``` ## Primary Path: BWA + bcftools ### Step 1: Quality Control with fastp ```bash # Single sample fastp -i sample_R1.fastq.gz -I s

What's inside
Steps it walks through
  1. Version Compatibility
  2. Workflow Overview
  3. Primary Path: BWA + bcftools
  4. Step 1: Quality Control with fastp
  5. Step 2: BWA-MEM2 Alignment
  6. Step 3: BAM Processing
  7. Step 4: Variant Calling with bcftools
  8. Step 5: Variant Filtering
  9. Alternative Path: BWA + GATK HaplotypeCaller
  10. Step 4 Alternative: GATK Variant Calling (DRAGEN Mode -- Recommended)
  11. Step 4 Alternative: GATK Standard Mode (with BQSR)
  12. Step 5 Alternative: GATK Variant Filtering
  13. Parameter Recommendations
  14. Choosing a Variant Caller
Ships with 3 files
  • examples/bwa_bcftools_workflow.sh
  • examples/bwa_gatk_workflow.sh
  • usage-guide.md
Commands it runs
Single sample
fastp -i sample_R1.fastq.gz -I sample_R2.fastq.gz \
Batch processing
for sample in sample1 sample2 sample3; do
fastp -i ${sample}_R1.fastq.gz -I ${sample}_R2.fastq.gz \
done
Index reference (once)
bwa-mem2 index reference.fa
Align with read group info
bwa-mem2 mem -t 8 \
More from awesome-bio-agent-skills
All skills →
About this skill
What does the bio-workflows-fastq-to-variants skill do?

End-to-end DNA sequencing workflow from FASTQ files to variant calls. Covers QC, alignment with BWA, BAM processing, and variant calling with bcftools or GATK HaplotypeCaller. Use when calling variants from raw sequencing reads.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill fastq-to-variants --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going