This workflow takes you from raw DNA sequencing FASTQ files to a filtered set of variant calls (SNPs and indels). It covers the entire process from quality control through alignment and variant calling.
Scanned 5/31/2026
Install via CLI
openskills install tools-only/X-Skills# FASTQ to Variants - Usage Guide
## Overview
This workflow takes you from raw DNA sequencing FASTQ files to a filtered set of variant calls (SNPs and indels). It covers the entire process from quality control through alignment and variant calling.
## Prerequisites
```bash
# CLI tools
conda install -c bioconda fastp bwa-mem2 samtools bcftools
# For GATK path
conda install -c bioconda gatk4
```
## Quick Start
Tell your AI agent what you want to do:
- "Call variants from my whole genome sequencing FASTQ files"
- "Run the FASTQ to variants pipeline on my exome data"
- "I have paired-end DNA reads, help me find variants"
## Example Prompts
### Starting from FASTQ
> "I have FASTQ files for 5 samples, call variants jointly"
> "Process my WGS data from raw reads to VCF"
> "Use GATK HaplotypeCaller instead of bcftools"
### Customizing the workflow
> "Add BQSR to my variant calling pipeline"
> "Call variants only in the exome target regions"
> "Run the pipeline on a specific chromosome"
### From alignment to variants
> "I already have BAM files, just call variants"
> "My BAMs are not duplicate-marked, process and call variants"
## Input Requirements
| Input | Format | Description |
|-------|--------|-------------|
| FASTQ files | .fastq.gz | Paired-end reads (R1 and R2 per sample) |
| Reference | FASTA | Reference genome (indexed for bwa-mem2) |
| Targets (optional) | BED | For exome/targeted sequencing |
| Known sites (GATK) | VCF | dbSNP for BQSR |
## What the Workflow Does
1. **Quality Control** - Trim adapters and low-quality bases
2. **Alignment** - Map reads to reference genome
3. **BAM Processing** - Sort, mark duplicates, index
4. **Variant Calling** - Identify SNPs and indels
5. **Filtering** - Remove low-quality calls
## Choosing Between bcftools and GATK
| Use bcftools when | Use GATK when |
|-------------------|---------------|
| Speed is important | Quality is paramount |
| Germline variants | Somatic variants |
| Small cohort | Large cohort with VQSR |
| Resource-limited | Resources available |
## Tips
- **Read groups**: Always add read group information during alignment
- **Duplicates**: Mark duplicates for PCR-based libraries
- **Depth**: Check coverage before variant calling (aim for 30x WGS, 100x exome)
- **Joint calling**: Improves sensitivity, especially for rare variants
- **Filtering**: Start with default filters, adjust based on Ti/Tv ratio and known site overlap
No comments yet. Be the first to comment!