Alphagenome Single Variant Analysis
google-deepmind/science-skills
Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API.
Fast short-read DNA aligner for WGS/WES/ChIP-seq. An agent skill from jaechang-hits/SciAgent-Skills.
$ npx skills add jaechang-hits/SciAgent-Skills --skill bwa-mem2-dna-aligner -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jaechang-hits/SciAgent-Skills bwa-mem2-dna-aligner --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner .claude/skills/bwa-mem2-dna-aligner && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "bwa-mem2-dna-aligner" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner into .claude/skills/bwa-mem2-dna-aligner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bwa-mem2-dna-aligner", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-alignerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add jaechang-hits/SciAgent-Skills --skill bwa-mem2-dna-aligner -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jaechang-hits/SciAgent-Skills bwa-mem2-dna-aligner --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner .agents/skills/bwa-mem2-dna-aligner && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "bwa-mem2-dna-aligner" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner into .agents/skills/bwa-mem2-dna-aligner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bwa-mem2-dna-aligner", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jaechang-hits/SciAgent-Skills --skill bwa-mem2-dna-aligner -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jaechang-hits/SciAgent-Skills bwa-mem2-dna-aligner --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner .cursor/skills/bwa-mem2-dna-aligner && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "bwa-mem2-dna-aligner" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner into .cursor/skills/bwa-mem2-dna-aligner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bwa-mem2-dna-aligner", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/jaechang-hits/SciAgent-Skills.git --path skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add jaechang-hits/SciAgent-Skills --skill bwa-mem2-dna-aligner -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jaechang-hits/SciAgent-Skills bwa-mem2-dna-aligner --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner .gemini/skills/bwa-mem2-dna-aligner && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "bwa-mem2-dna-aligner" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner into .gemini/skills/bwa-mem2-dna-aligner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bwa-mem2-dna-aligner", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install jaechang-hits/SciAgent-Skills bwa-mem2-dna-alignerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add jaechang-hits/SciAgent-Skills --skill bwa-mem2-dna-aligner -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner .github/skills/bwa-mem2-dna-aligner && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "bwa-mem2-dna-aligner" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner into .github/skills/bwa-mem2-dna-aligner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bwa-mem2-dna-aligner", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add jaechang-hits/SciAgent-Skills --skill bwa-mem2-dna-aligner -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jaechang-hits/SciAgent-Skills bwa-mem2-dna-aligner --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jaechang-hits/SciAgent-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner .opencode/skills/bwa-mem2-dna-aligner && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "bwa-mem2-dna-aligner" agent skill from https://github.com/jaechang-hits/SciAgent-Skills/tree/main/skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner into .opencode/skills/bwa-mem2-dna-aligner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bwa-mem2-dna-aligner", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
bwa-mem2-dna-alignerFast short-read DNA aligner for WGS/WES/ChIP-seq. An agent skill from jaechang-hits/SciAgent-Skills.
Bwa Mem2 Dna Aligner is an agent skill from jaechang-hits/SciAgent-Skills. 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.
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Bioinformatics. The repository describes itself as: 197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, single-cell, drug discovery, proteomics, and more. Powers OmicsHorizon. The licence is MIT.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 82c862c. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
wgetcondapython3From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
github.comftp.ncbi.nlm.nih.govftp.ebi.ac.ukAlso links to:
doi.orggatk.broadinstitute.orgFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Bwa Mem2 Dna Aligner loads about 3.5k tokens when it runs. Until then it costs about 72 tokens; SKILL.md has 806 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from jaechang-hits/SciAgent-Skills at commit 82c862c, republished under its MIT licence (© jaechang-hits). 806 words, ~3,487 tokens.
.claude/skills/bwa-mem2-dna-aligner/SKILL.md (or your agent's skills folder).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
# 2.2.1Settle these with the user before writing any analysis code.
decisions:
- id: D1
param: reference_bundle
kind: required
source: user
ask: "Which species and genome assembly should reads be aligned against?"
default: null
- id: D2
param: read_group
kind: required
source: user
ask: "What sample name and library identity should be stamped into each alignment?"
default: null
- id: D3
param: downstream_compatibility
kind: derived
source: upstream
ask: "Will GATK or Picard consume this BAM, requiring supplementary alignments flagged and soft-clipped?"
default: "-M -Y when a GATK/Picard step follows"
- id: D4
param: seedLength
kind: optional
source: user
ask: "Do these reads need a shorter seed than the default to map sensitively?"
default: 19
- id: D5
param: minAlignmentScore
kind: optional
source: user
ask: "How weak an alignment is still worth reporting?"
default: 30
- id: D6
param: interleavedInput
kind: derived
source: data
ask: "Are both mates held in a single interleaved FASTQ?"
default: false
skip_if: "reads supplied as separate R1/R2 files"
- id: D7
param: threads
kind: never_ask
source: data
reason: "Affects runtime only, not the alignments"
default: "min(8, available_cores)"D2 is not cosmetic. The sample name in the read group is what joint genotyping groups by; an omitted or duplicated one silently merges or splits samples downstream, long after the alignment itself looks fine.
# 1. Build genome index (~30 min, run once)
bwa-mem2 index GRCh38.fa
# 2. Align paired-end reads and sort
bwa-mem2 mem -t 16 -R "@RG\tID:sample1\tSM:sample1\tPL:ILLUMINA" \
GRCh38.fa sample1_R1.fastq.gz sample1_R2.fastq.gz \
| samtools sort -@ 8 -o sample1.sorted.bam
# 3. Index the BAM
samtools index sample1.sorted.bam
echo "Aligned reads: $(samtools view -c -F 4 sample1.sorted.bam)"Obtain the reference genome FASTA file matching the target assembly.
# Download GRCh38 primary assembly (human)
wget https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/001/405/GCA_000001405.15_GRCh38/seqs_for_alignment_pipelines.ucsc_ids/GCA_000001405.15_GRCh38_no_alt_analysis_set.fna.gz
gunzip GCA_000001405.15_GRCh38_no_alt_analysis_set.fna.gz
mv GCA_000001405.15_GRCh38_no_alt_analysis_set.fna GRCh38.fa
# Or use ENSEMBL/GENCODE
wget https://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_47/GRCh38.primary_assembly.genome.fa.gz
gunzip GRCh38.primary_assembly.genome.fa.gz
echo "Reference size: $(du -sh GRCh38.fa)"Index the reference genome — required once per genome, takes ~25-35 min for human.
# Build index (~28 GB RAM required for human genome)
bwa-mem2 index GRCh38.fa
# This creates: GRCh38.fa.0123, GRCh38.fa.amb, GRCh38.fa.ann,
# GRCh38.fa.bwt.2bit.64, GRCh38.fa.pac
echo "Index files: $(ls GRCh38.fa.* | wc -l) created"
ls -lh GRCh38.fa.*Align FASTQ reads with a read group header required for GATK compatibility.
# Align with read group (required for GATK)
# @RG fields: ID (run ID), SM (sample name), PL (platform), LB (library), PU (flowcell)
bwa-mem2 mem \
-t 16 \
-R "@RG\tID:sample1_run1\tSM:sample1\tPL:ILLUMINA\tLB:lib1\tPU:flowcell1" \
GRCh38.fa \
sample1_R1.fastq.gz \
sample1_R2.fastq.gz \
| samtools sort -@ 8 -m 2G -o sample1.sorted.bam
samtools index sample1.sorted.bam
echo "Alignment complete."
echo "Total reads: $(samtools view -c sample1.sorted.bam)"
echo "Mapped reads: $(samtools view -c -F 4 sample1.sorted.bam)"Remove or mark optical and PCR duplicates before variant calling.
# Option A: samtools markdup (fast)
samtools fixmate -m sample1.sorted.bam sample1.fixmate.bam
samtools sort -@ 8 -o sample1.fixmate.sorted.bam sample1.fixmate.bam
samtools markdup -@ 8 sample1.fixmate.sorted.bam sample1.markdup.bam
samtools index sample1.markdup.bam
echo "Duplication rate:"
samtools flagstat sample1.markdup.bam | grep "duplicate"
# Option B: Picard MarkDuplicates (GATK best practices)
picard MarkDuplicates \
INPUT=sample1.sorted.bam \
OUTPUT=sample1.markdup.bam \
METRICS_FILE=sample1.dupmetrics.txt \
REMOVE_DUPLICATES=false \
CREATE_INDEX=true
cat sample1.dupmetrics.txt | grep -A2 "ESTIMATED"Generate alignment statistics and check key quality metrics.
# Full alignment statistics
samtools flagstat sample1.markdup.bam > sample1.flagstat.txt
cat sample1.flagstat.txt
# Coverage statistics
samtools coverage sample1.markdup.bam | head -30
# Parse key metrics with Python
python3 - << 'EOF'
from pathlib import Path
flagstat = Path("sample1.flagstat.txt").read_text()
for line in flagstat.splitlines():
if any(kw in line for kw in ["total", "mapped", "properly paired", "duplicate"]):
print(line)
EOFPipe BWA-MEM2 output directly into GATK HaplotypeCaller.
#!/bin/bash
# Complete WGS alignment → variant calling pipeline
GENOME="GRCh38.fa"
SAMPLE="sample1"
R1="data/${SAMPLE}_R1.fastq.gz"
R2="data/${SAMPLE}_R2.fastq.gz"
THREADS=16
OUTDIR="results/${SAMPLE}"
mkdir -p "$OUTDIR"
# Step 1: Align + sort
bwa-mem2 mem -t $THREADS \
-R "@RG\tID:${SAMPLE}\tSM:${SAMPLE}\tPL:ILLUMINA\tLB:lib1\tPU:run1" \
$GENOME $R1 $R2 \
| samtools sort -@ 8 -o $OUTDIR/${SAMPLE}.sorted.bam
samtools index $OUTDIR/${SAMPLE}.sorted.bam
# Step 2: Mark duplicates
samtools fixmate -m $OUTDIR/${SAMPLE}.sorted.bam - \
| samtools sort -@ 8 \
| samtools markdup -@ 8 - $OUTDIR/${SAMPLE}.markdup.bam
samtools index $OUTDIR/${SAMPLE}.markdup.bam
# Step 3: GATK variant calling
gatk HaplotypeCaller \
-R $GENOME \
-I $OUTDIR/${SAMPLE}.markdup.bam \
-O $OUTDIR/${SAMPLE}.g.vcf.gz \
-ERC GVCF \
--native-pair-hmm-threads 4
echo "Pipeline complete: $OUTDIR/${SAMPLE}.g.vcf.gz"| Parameter | Default | Range/Options | Effect |
|---|---|---|---|
-t | 1 | 1–64 | CPU threads; use 8–16 for production runs |
-R | — | @RG\tID:...\tSM:... | Read group string; required for GATK compatibility |
-k | 19 | 10–28 | Minimum seed length; lower = more sensitive for shorter reads |
-w | 100 | 50–500 | Band width for Smith-Waterman alignment |
-M | off | flag | Mark split/supplementary reads as secondary (BWA-MEM style); needed for Picard compatibility |
-a | off | flag | Output all alignments for single-end reads (for seeding; increases file size) |
-p | off | flag | Treat input as interleaved paired-end FASTQ |
-c | 500 | 100–10000 | Skip alignment for MEM count > threshold (reduces multi-mapper noise) |
-T | 30 | 20–60 | Minimum alignment score threshold; lower = report more low-quality alignments |
-Y | off | flag | Use soft clipping for supplementary alignments (recommended for GATK) |
#!/bin/bash
# Align all samples in parallel using GNU parallel or sequential loop
GENOME="GRCh38.fa"
SAMPLES=(ctrl_1 ctrl_2 treat_1 treat_2)
THREADS=12
for sample in "${SAMPLES[@]}"; do
echo "=== Aligning $sample ==="
bwa-mem2 mem -t $THREADS \
-R "@RG\tID:${sample}\tSM:${sample}\tPL:ILLUMINA\tLB:lib1\tPU:run1" \
$GENOME \
data/${sample}_R1.fastq.gz \
data/${sample}_R2.fastq.gz \
| samtools sort -@ 4 -m 2G -o results/${sample}.sorted.bam
samtools index results/${sample}.sorted.bam
MAPPED=$(samtools view -c -F 4 results/${sample}.sorted.bam)
TOTAL=$(samtools view -c results/${sample}.sorted.bam)
echo "$sample: $MAPPED / $TOTAL reads mapped"
doneimport subprocess
import pandas as pd
from pathlib import Path
samples = ["ctrl_1", "ctrl_2", "treat_1", "treat_2"]
metrics = []
for sample in samples:
bam = f"results/{sample}.sorted.bam"
result = subprocess.run(
["samtools", "flagstat", bam], capture_output=True, text=True
)
stats = {}
for line in result.stdout.splitlines():
if "total" in line:
stats["total"] = int(line.split()[0])
elif "mapped" in line and "%" in line:
stats["mapped"] = int(line.split()[0])
stats["pct_mapped"] = float(line.split("(")[1].split("%")[0])
elif "properly paired" in line:
stats["properly_paired"] = int(line.split()[0])
stats["sample"] = sample
metrics.append(stats)
df = pd.DataFrame(metrics).set_index("sample")
print(df[["total", "mapped", "pct_mapped", "properly_paired"]])
df.to_csv("alignment_metrics.tsv", sep="\t")| Output | Format | Description |
|---|---|---|
*.sorted.bam | BAM | Coordinate-sorted aligned reads; index with samtools index |
*.sorted.bam.bai | BAI | BAM index; required for random access by GATK and IGV |
*.flagstat.txt | Text | Alignment summary: total/mapped/paired/duplicate counts and percentages |
*.markdup.bam | BAM | Duplicate-marked BAM; use as input to GATK HaplotypeCaller |
*.dupmetrics.txt | Text | Picard duplication metrics with estimated library size |
| Problem | Cause | Solution |
|---|---|---|
| Low mapping rate (< 85%) | Genome mismatch, contamination, or low quality reads | Verify genome assembly matches sample; run FastQC; trim adapters with Trim Galore |
@RG header missing error in GATK | -R flag not specified during alignment | Re-align with -R "@RG\tID:...\tSM:...\tPL:ILLUMINA" |
| Out of memory during indexing | Insufficient RAM for genome index | BWA-MEM2 requires ~28 GB for human; use classic bwa with less RAM if needed |
| Unbalanced paired-end counts | Interleaved FASTQ or file mismatch | Add -p for interleaved; verify R1/R2 read counts with zcat r1.fq.gz | wc -l |
[E::bwa_idx_load_from_disk] error | Index files missing or wrong prefix | Re-run bwa-mem2 index genome.fa; ensure all .0123, .bwt.2bit.64 files exist |
| Slow alignment speed | Low thread count or slow I/O | Use -t 16 or more; store data on SSD; pipe directly to samtools sort |
| Supplementary alignments causing issues | Split reads in downstream tools | Add -M flag to mark split reads as secondary (Picard compatibility) |
| GATK base quality score recalibration fails | Missing known variant VCF | Download dbSNP VCF for your genome assembly from NCBI or GATK resource bundle |
© jaechang-hits, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner of jaechang-hits/SciAgent-Skills.
Open the folder on GitHubat commit 82c862c
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in jaechang-hits/SciAgent-Skills, which our catalogue first saw on October 7, 2026.
Bwa Mem2 Dna Aligner next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Bwa Mem2 Dna Aligner this skilljaechang-hits/SciAgent-Skills | 374 | 1 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Alphagenome Single Variant Analysisgoogle-deepmind/science-skills | 3.2k | 2 repos | ~3k | Automated safety check: Notes | Apache-2.0 | |
| 13C Metabolic Flux AnalysisK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Clinvar Databasegoogle-deepmind/science-skills | 3.2k | 2 repos | ~3.9k | Automated safety check: Notes | Apache-2.0 | |
| Metabolic Study Planneraiming-lab/AutoResearchClaw | 15k | — | ~1.9k | Automated safety check: Pass | MIT | |
| Dbsnp Databasegoogle-deepmind/science-skills | 3.2k | 2 repos | ~3.4k | Automated safety check: Notes | Apache-2.0 |
google-deepmind/science-skills
Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API.
K-Dense-AI/scientific-agent-skills
Estimates reaction fluxes inside cells from steady-state carbon-13 labeling data with a bundled mfapy-based solver, and reports which fluxes the data pin down.
google-deepmind/science-skills
A skill your agent uses when needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding "hard positive" benchmark controls…
aiming-lab/AutoResearchClaw
Turns a broad metabolic modelling topic into a concrete, paper-shaped plan with organism, model, perturbations, metrics and figures before any FBA code is written.
google-deepmind/science-skills
A skill your agent uses when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database.
aiming-lab/AutoResearchClaw
Runs a metabolic flux analysis from model loading to phenotype prediction and figures by handing work to four sub-agents in sequence.
jaechang-hits/SciAgent-Skills
NEB-IRC activation energy pipeline for reaction barriers using GFN2-xTB and pysisyphus.
jaechang-hits/SciAgent-Skills
3Dmol.js WebGL molecular visualization emitted as self-contained HTML.
jaechang-hits/SciAgent-Skills
Constraint-based (COBRA) analysis of genome-scale metabolic models: FBA, FVA, knockouts, flux sampling, production envelopes, gapfilling, media optimization.
jaechang-hits/SciAgent-Skills
Read, write, and edit ChemDraw CDX/CDXML files with RDKit's rdkit.Chem.rdChemDraw plus direct XML editing, always paired with a rendered PNG.
jaechang-hits/SciAgent-Skills
Programmatic PubMed access via NCBI E-utilities REST API. An agent skill from jaechang-hits/SciAgent-Skills.
jaechang-hits/SciAgent-Skills
Scaffold a new SciAgent-Skills entry. An agent skill from jaechang-hits/SciAgent-Skills.
Categories
Fast short-read DNA aligner for WGS/WES/ChIP-seq. An agent skill from jaechang-hits/SciAgent-Skills. Bwa Mem2 Dna Aligner is an agent skill from jaechang-hits/SciAgent-Skills. Fast short-read DNA aligner for WGS/WES/ChIP-seq.
Bwa Mem2 Dna Aligner fits situations like: tasks that involve Bioinformatics.
Run `npx skills add jaechang-hits/SciAgent-Skills --skill bwa-mem2-dna-aligner -a claude-code`. Or copy the skill folder (skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner in jaechang-hits/SciAgent-Skills) into .claude/skills/bwa-mem2-dna-aligner in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jaechang-hits/SciAgent-Skills --skill bwa-mem2-dna-aligner -a codex`. Or copy the skill folder (skills/genomics-bioinformatics/alignment/bwa-mem2-dna-aligner in jaechang-hits/SciAgent-Skills) into .agents/skills/bwa-mem2-dna-aligner in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jaechang-hits/SciAgent-Skills --skill bwa-mem2-dna-aligner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bwa-mem2-dna-aligner, .gemini/skills/bwa-mem2-dna-aligner, .github/skills/bwa-mem2-dna-aligner and .opencode/skills/bwa-mem2-dna-aligner in your project.
Going by SKILL.md and its folder, Bwa Mem2 Dna Aligner needs the command-line tools its instructions call (wget, conda and python3). Our summary lists: Python 3.
SKILL.md names 5 domains. In commands or code: github.com, ftp.ncbi.nlm.nih.gov and ftp.ebi.ac.uk; the agent is likely to contact these when it follows the instructions. As links in the text: doi.org and gatk.broadinstitute.org. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Bwa Mem2 Dna Aligner is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Bwa Mem2 Dna Aligner: Alphagenome Single Variant Analysis (google-deepmind/science-skills, 3.2k stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars), Clinvar Database (google-deepmind/science-skills, 3.2k stars) and Metabolic Study Planner (aiming-lab/AutoResearchClaw, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
jaechang-hits (a GitHub user) maintains it in jaechang-hits/SciAgent-Skills, which has 374 GitHub stars. The repository holds 169 skills in this directory. The repository was last updated on September 29, 2026.
Source: jaechang-hits/SciAgent-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.