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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.
Passed 22 of 22 test cases with the skill, and 19 of 22 without it.
and 1 more in the full report
3 fixed19 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am running DNA read alignment for input into Picard MarkDuplicates and GATK. Split reads can cause compatibility errors in Picard if they are not marked as secondary alignments. Which flag should be passed to the aligner to ensure split/supplementary reads are marked as secondary for Picard compatibility?
| Checked | Without skill | With skill |
|---|---|---|
| Includes the -M flag in the bwa-mem2 mem invocation. | Missed | Passed |
The instructions your model reads when the skill loads.
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.
@RG read group tagsCheck before installing: The tool may already be available in the current environment (e.g., inside a
pixi/condaenv). Runcommand -v bwa-mem2first and skip the install commands below if it returns a path. When running inside a pixi project, invoke the tool viapixi run bwa-mem2rather than barebwa-mem2.
# 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
# 2.2.1
test cases passed, vs 19 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.