Agent skill

bwa-mem2-dna-aligner

Fast short-read DNA aligner for WGS/WES/ChIP-seq. 2× faster BWA-MEM successor; outputs SAM/BAM with read group headers for GATK. Primary plus supplementary records for chimeric reads. Use STAR for RNA-seq splice-aware alignment; Bowtie2 is a comparable alternative.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill bwa-mem2-dna-aligner --agent claude-code

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

Facts
Files in the skill folder: 1
SKILL.md size: 12 KB
Bundled scripts: none
Path: skills/sciagent/bwa-mem2-dna-aligner/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

# BWA-MEM2 — DNA Short-Read Aligner ## Overview BWA-MEM2 aligns short DNA reads (Illumina, 50–250 bp) to a reference genome using the BWT-FM index. It is the standard aligner for whole-genome sequencing (WGS), whole-exome sequencing (WES), ChIP-seq, and ATAC-seq DNA alignment. BWA-MEM2 is 2× faster than the original BWA-MEM while producing identical results. It outputs SAM format with proper read group (`@RG`) headers required by GATK HaplotypeCaller and Picard tools. For paired-end reads, it marks proper pairs and resolves chimeric/split reads into supplementary alignments. ## When to Use - Aligning WGS or WES Illumina reads to a reference genome for variant calling (SNP, indel, SV) - ChIP-seq or ATAC-seq DNA alignment to produce BAM files for peak calling with MACS3 - Producing GATK-compatible BAM files with `@RG` read group tags - Aligning reads ≥ 50 bp; for shorter reads (< 50 bp), BWA-backtrack may be more appropriate - Re-aligning legacy FASTQ files to an updated reference genome assembly - Use **STAR** instead for RNA-seq reads that span splice junctions - Use **Bowtie2** as an alternative for local alignment or when index size must be minimized ## Prerequisites - **Software

What's inside
Steps it walks through
  1. Overview
  2. When to Use
  3. Prerequisites
  4. Quick Start
  5. Workflow
  6. Step 1: Download Reference Genome
  7. Step 2: Build BWA-MEM2 Index
  8. Step 3: Align Paired-End Reads
  9. Step 4: Mark PCR Duplicates
  10. Step 5: Assess Alignment Quality
  11. Step 6: Complete WGS/WES Pipeline → Variant Calling
  12. Key Parameters
  13. Common Recipes
  14. Recipe 1: Batch Align Multiple Samples
Commands it runs
Install with conda (recommended)
conda install -c bioconda bwa-mem2 samtools
Or download pre-compiled binary
wget https://github.com/bwa-mem2/bwa-mem2/releases/download/v2.2.1/bwa-mem2-2.2.1_x64-linux.tar.bz2
tar -jxf bwa-mem2-2.2.1_x64-linux.tar.bz2
export PATH="$PWD/bwa-mem2-2.2.1_x64-linux:$PATH"
Verify
bwa-mem2 version
bwa-mem2 index GRCh38.fa
bwa-mem2 mem -t 16 -R "@RG\tID:sample1\tSM:sample1\tPL:ILLUMINA" \
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About this skill
What does the bwa-mem2-dna-aligner skill do?

Fast short-read DNA aligner for WGS/WES/ChIP-seq. 2× faster BWA-MEM successor; outputs SAM/BAM with read group headers for GATK. Primary plus supplementary records for chimeric reads. Use STAR for RNA-seq splice-aware alignment; Bowtie2 is a comparable alternative.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill bwa-mem2-dna-aligner --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.

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