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.
Detects contamination in sequencing reads - cross-species (FastQ Screen, Kraken2), vector/PhiX/adapter, rRNA, and same-species cross-sample/index-hopping and sample swaps (SNP fingerprints via…
Install Bio Read Qc Contamination Screening
$ npx skills add GPTomics/bioSkills --skill bio-read-qc-contamination-screening -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install GPTomics/bioSkills bio-read-qc-contamination-screening --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/GPTomics/bioSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/read-qc/contamination-screening .claude/skills/bio-read-qc-contamination-screening && 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 "bio-read-qc-contamination-screening" agent skill from https://github.com/GPTomics/bioSkills/tree/main/read-qc/contamination-screening into .claude/skills/bio-read-qc-contamination-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-read-qc-contamination-screening", 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/GPTomics/bioSkills/tree/main/read-qc/contamination-screeningType 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 GPTomics/bioSkills --skill bio-read-qc-contamination-screening -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install GPTomics/bioSkills bio-read-qc-contamination-screening --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/read-qc/contamination-screening .agents/skills/bio-read-qc-contamination-screening && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "bio-read-qc-contamination-screening" agent skill from https://github.com/GPTomics/bioSkills/tree/main/read-qc/contamination-screening into .agents/skills/bio-read-qc-contamination-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-read-qc-contamination-screening", 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 GPTomics/bioSkills --skill bio-read-qc-contamination-screening -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install GPTomics/bioSkills bio-read-qc-contamination-screening --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/read-qc/contamination-screening .cursor/skills/bio-read-qc-contamination-screening && 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 "bio-read-qc-contamination-screening" agent skill from https://github.com/GPTomics/bioSkills/tree/main/read-qc/contamination-screening into .cursor/skills/bio-read-qc-contamination-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-read-qc-contamination-screening", 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/GPTomics/bioSkills.git --path read-qc/contamination-screening--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 GPTomics/bioSkills --skill bio-read-qc-contamination-screening -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install GPTomics/bioSkills bio-read-qc-contamination-screening --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/read-qc/contamination-screening .gemini/skills/bio-read-qc-contamination-screening && 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 "bio-read-qc-contamination-screening" agent skill from https://github.com/GPTomics/bioSkills/tree/main/read-qc/contamination-screening into .gemini/skills/bio-read-qc-contamination-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-read-qc-contamination-screening", 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 GPTomics/bioSkills bio-read-qc-contamination-screeningInstalls 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 GPTomics/bioSkills --skill bio-read-qc-contamination-screening -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .github/skills && cp -r skills-src/read-qc/contamination-screening .github/skills/bio-read-qc-contamination-screening && 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 "bio-read-qc-contamination-screening" agent skill from https://github.com/GPTomics/bioSkills/tree/main/read-qc/contamination-screening into .github/skills/bio-read-qc-contamination-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-read-qc-contamination-screening", 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 GPTomics/bioSkills --skill bio-read-qc-contamination-screening -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install GPTomics/bioSkills bio-read-qc-contamination-screening --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/read-qc/contamination-screening .opencode/skills/bio-read-qc-contamination-screening && 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 "bio-read-qc-contamination-screening" agent skill from https://github.com/GPTomics/bioSkills/tree/main/read-qc/contamination-screening into .opencode/skills/bio-read-qc-contamination-screening/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-read-qc-contamination-screening", 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.
Facts
- Skill name
bio-read-qc-contamination-screening- GitHub stars
- 1.2k
- Used in
- 1 other repo
- Token cost
- ~3.3k tokens
- SKILL.md length
- 1,381 words
- Files
- 3
- Skills in repo
- 559
- Repo updated
- First seen
- Licence
- MIT
At a glance
Detects contamination in sequencing reads - cross-species (FastQ Screen, Kraken2), vector/PhiX/adapter, rRNA, and same-species cross-sample/index-hopping and sample swaps (SNP fingerprints via…
- Works in 3 steps: A SPECIES screen answers "what ORGANISMS… → Index hopping is the same-species… → Default to SCREEN-AND-REPORT, not filter…
- Suspecting cross-contamination
- SKILL.md covers Version Compatibility, The Single Most Important…, The Contamination Taxonomy --… and Tool Taxonomy, plus 7 more sections
- Runs Shell scripts from its folder
What it does
Bio Read Qc Contamination Screening is an agent skill from GPTomics/bioSkills. Detects contamination in sequencing reads - cross-species (FastQ Screen, Kraken2), vector/PhiX/adapter, rRNA, and same-species cross-sample/index-hopping and sample swaps (SNP fingerprints via verifyBamID2/NGSCheckMate/somalier). Use when suspecting cross-contamination, PDX host reads, microbial carry-over, or sample swaps, and to decide whether to report, filter, or align to a combined reference. For deep taxonomic profiling use metagenomics/kraken-classification.
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `examples/screen_samples.sh` and `usage-guide.md`).
It sits in Research & Science, covering Bioinformatics. The repository describes itself as: a set of SKILLS.md for doing bioinformatics with agents like claude code. The licence is MIT.
When your agent uses it
- Suspecting cross-contamination
- Microbial carry-over
- To decide whether to report
- Align to a combined reference
Example prompts
- “Use the bio-read-qc-contamination-screening skill to detect contamination in sequencing reads - cross-species (FastQ Screen, Kraken2)…”
- “/bio-read-qc-contamination-screening”
Requirements
- A Bash shell
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- A SPECIES screen answers "what ORGANISMS are here?"; a SNP FINGERPRINT answers "WHOSE DNA is this, and is it a mixture?" -- and these are…
- Index hopping is the same-species contamination that lives inside one run, and unique dual indexing (UDI) is the only clean fix. On…
- Default to SCREEN-AND-REPORT, not filter -- removing reads biases composition. A species screen is a QC gate; if a contaminant is low…
What it can do on your machine
Read from SKILL.md and the folder at commit d91ed3d. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
Ships script files (Shell), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Bio Read Qc Contamination Screening loads about 3.3k tokens when it runs. Until then it costs about 126 tokens; SKILL.md has 1,381 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.
Safety
Auto-check passed
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.
SKILL.md
The full file from GPTomics/bioSkills at commit d91ed3d, republished under its MIT licence (© GPTomics). 1,381 words, ~3,332 tokens.
Download SKILL.mdSave it as
.claude/skills/bio-read-qc-contamination-screening/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- bio-read-qc-contamination-screening
- description
- Detects contamination in sequencing reads - cross-species (FastQ Screen, Kraken2), vector/PhiX/adapter, rRNA, and same-species cross-sample/index-hopping and sample swaps (SNP fingerprints via verifyBamID2/NGSCheckMate/somalier). Use when suspecting cross-contamination, PDX host reads, microbial carry-over, or sample swaps, and to decide whether to report, filter, or align to a combined reference. For deep taxonomic profiling use metagenomics/kraken-classification.
- tool_type
- cli
- primary_tool
- fastq_screen
Version Compatibility
Reference examples tested with: FastQ Screen 0.15+, Bowtie2 2.5+, Kraken2 2.1+, BBTools 39.0+, MultiQC 1.21+
Before using code patterns, verify installed versions match. If versions differ:
- CLI:
<tool> --versionthen<tool> --helpto 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.
Contamination Screening -- a species screen cannot see a same-species swap
Screen reads against a genome panel (FastQ Screen / Kraken2) for foreign ORGANISMS, and against SNP fingerprints for foreign or wrong INDIVIDUALS.
"Check my reads for contamination" -> Map a subsample against multiple references and/or fingerprint sample identity to find foreign DNA and mislabels.
- CLI:
fastq_screen --conf fastq_screen.conf sample.fastq.gz(cross-species) - CLI:
verifyBamID2 --SVDPrefix resource --BamFile sample.bam(same-species contamination)
Scope: this skill OWNS contamination detection and the report-vs-filter decision. Deep taxonomic profiling/abundance -> metagenomics/kraken-classification, metagenomics/metaphlan-profiling. rRNA depletion as an RNA prep metric -> read-qc/rnaseq-qc. OUT OF SCOPE: adapter removal (read-qc/adapter-trimming).
The Single Most Important Modern Insight
A SPECIES screen answers "what ORGANISMS are here?"; a SNP FINGERPRINT answers "WHOSE DNA is this, and is it a mixture?" -- and these are orthogonal. A species screen is structurally BLIND to same-species cross-sample contamination and sample swaps: a human-A + human-B mixture, or a mislabeled human file, produces a perfectly clean single-species profile. Most pipelines run only a species screen and declare the data clean. Any human or single-species-cohort pipeline needs BOTH a taxonomic screen AND a SNP-fingerprint identity/contamination check (verifyBamID2, NGSCheckMate, somalier, conpair).
Index hopping is the same-species contamination that lives inside one run, and unique dual indexing (UDI) is the only clean fix. On patterned flowcells (HiSeq X/4000, NovaSeq) ExAmp chemistry lets a free index adapter tag a fragment from another sample, spreading ~0.1-2% of reads into incorrect samples. Irrelevant for germline common variants, CATASTROPHIC for low-VAF work (ctDNA, single-cell, somatic) where hopped reads look like phantom low-frequency variants. Combinatorial indexing cannot detect it; UDI (a unique i7 AND i5 per sample) lets the demultiplexer drop impossible index pairs. UDI is effectively mandatory for ctDNA/plasma, single-cell, and low-input somatic.
Default to SCREEN-AND-REPORT, not filter -- removing reads biases composition. A species screen is a QC gate; if a contaminant is low, aligning to the correct reference simply will not place the foreign reads. Filter only a specific, named contaminant (PhiX before assembly, adapters before alignment) with a precise k-mer remover (BBDuk
ref=phix), never "remove anything that hits the screen" (that also discards conserved rRNA/mito reads that belong to the sample). For PDX, align to a COMBINED human+mouse reference and keep human-assigned reads, OR use a dedicated post-alignment classifier (XenofilteR benchmarks above Xenome for variant false-positive rate); both beat hard pre-filtering on one genome, which mis-assigns conserved-region reads.
Deeper trap: reference-genome contamination corrupts the screen itself. A "human" hit can be bacterial sequence mis-deposited inside the human assembly (Conterminator found >2M contaminated GenBank entries). No --confidence setting fixes a wrong database; trust a deconned/curated DB and treat surprising single-source hits as DB artifacts until ruled out.
The Contamination Taxonomy -- five classes, five fixes
| Class | What it is | Detect with | Fix |
|---|---|---|---|
| Cross-species | Mouse in human PDX; bacteria in culture | FastQ Screen, Kraken2/Bracken, sourmash, Xenome/XenofilteR | Combined-reference alignment; k-mer bin (report, do not blindly remove) |
| Cross-sample / index hopping | Same-species reads on the wrong sample (INVISIBLE to species screens) | verifyBamID2, NGSCheckMate, somalier, conpair | UDI at prep; drop impossible index pairs at demux |
| Vector / PhiX / adapter | Spike-in, cloning vector, linkers | UniVec/VecScreen; FastQ Screen adapter DB; BBDuk ref=phix/ref=adapters | k-mer trim/filter; upstream library QC |
| rRNA over-representation | Library-prep failure, not contamination | SortMeRNA, ribodetector | Re-prep / better depletion; filter only to recover depth |
| Cell-line: mycoplasma / misID | Mollicutes infection; HeLa cross-contamination | Kraken2 for Mollicutes; STR profiling for line identity | Clear culture or discard; STR-authenticate |
A pipeline that runs FastQ Screen and stops has checked exactly one of five boxes.
Tool Taxonomy
| Tool | Mechanism | When |
|---|---|---|
| FastQ Screen | Map a subsample to a genome panel; classify hit categories | Cross-species QC gate; the workhorse screen |
| Kraken2 + Bracken | Exact-k-mer minimizer LCA classification; Bracken re-estimates abundance | Read-level taxonomy; many possible contaminants |
| BBSplit / BBDuk | k-mer binning / named-contaminant k-mer removal | Decontamination of a NAMED contaminant (PhiX, adapters) |
| Xenome / XenofilteR | Classify reads human vs mouse (k-mer / dual-alignment) | PDX host-graft disambiguation |
| sourmash | MinHash/FracMinHash containment sketches | Fast low-memory "what is in here?" screen |
| verifyBamID2 | Per-sample within-species contamination from population SNP AFs | Same-species contamination level (FREEMIX) |
| NGSCheckMate / somalier | SNP-fingerprint identity / relatedness | Sample swaps, tumor-normal pairing, longitudinal identity |
| conpair | Tumor-normal concordance + independent contamination | Matched T/N pairs |
Decision Tree by Scenario
| Question | Use | Why |
|---|---|---|
| Is a foreign ORGANISM present? | FastQ Screen or Kraken2 | Maps reads to species references |
| Is this the right INDIVIDUAL / one person? | NGSCheckMate / somalier | SNP fingerprint, species-screen-blind |
| What is the contamination LEVEL (human)? | verifyBamID2 (FREEMIX) | Estimates mixture fraction from SNP AFs |
| Tumor-normal pair: matched and clean? | conpair | Concordance + per-sample contamination |
| PDX host vs graft | Combined reference or a benchmarked classifier | XenofilteR > Xenome for SNV FP rate; both beat hard pre-filtering |
| Remove a NAMED contaminant | BBDuk ref=... | Precise k-mer removal, not "hits the screen" |
| Strip HUMAN reads before public deposition (non-human library) | hostile / NCBI sra-human-scrubber (HRRT) | Deposition compliance, not a QC gate; a masked T2T reference avoids stripping conserved microbial regions |
Default when uncertain: FastQ Screen as the QC gate for organisms, PLUS a SNP-fingerprint check (somalier/NGSCheckMate) for any human cohort.
Show full SKILL.md (508 more words)Show less
FastQ Screen
Maps a SUBSAMPLE (--subset, default 100000) with bowtie2 reporting >1 alignment, then classifies each read across the panel. Read the bar chart, not just "% mapped": contamination concentrates in One_hit_one_genome of an UNEXPECTED genome; homology (rRNA, mito, conserved loci) spreads into the *_multiple_genomes categories; high Hit_no_genomes means adapter dimer, a missing reference, or a novel organism (a diagnostic, not a verdict).
# Config: aligner binary + DATABASE lines (bowtie2 index prefixes)
cat > fastq_screen.conf <<'EOF'
BOWTIE2 /usr/local/bin/bowtie2
THREADS 8
DATABASE Human /refs/GRCh38_bt2/GRCh38
DATABASE Mouse /refs/GRCm39_bt2/GRCm39
DATABASE Ecoli /refs/Ecoli_bt2/Ecoli
DATABASE PhiX /refs/phix_bt2/phix
DATABASE rRNA /refs/rRNA_bt2/rRNA
EOF
fastq_screen --conf fastq_screen.conf --threads 8 --outdir screen/ *.fastq.gz
multiqc screen/ # MultiQC parses *_screen.txt across samples
# Tag every read with a per-genome status, then extract a subset by pattern
fastq_screen --conf fastq_screen.conf --tag --filter 10000 sample.fastq.gz # maps only to genome 1
fastq_screen --conf fastq_screen.conf --nohits sample.fastq.gz # reads hitting nothing--filter digits (one per genome, config order): 0=no map, 1=unique, 2=multi, 3=maps, 4=pass 0 or 1, 5=pass 0 or 2, -=ignore. --subset 0 screens the whole file; --bisulfite uses Bismark.
Kraken2 + Bracken (read-level taxonomy)
Default --confidence 0.0 over-reports a long tail of spurious low-abundance species (a few shared k-mers suffice); raise to 0.05-0.1 and keep --minimum-hit-groups 2 (or 3 for custom DBs). Kraken2 gives CLASSIFICATION; Bracken redistributes higher-rank reads to species for ABUNDANCE.
kraken2 --db /db/k2_standard --threads 8 --confidence 0.1 --paired \
--report sample.kreport --use-names R1.fq.gz R2.fq.gz > sample.kraken
bracken -d /db/k2_standard -i sample.kreport -o sample.bracken -r 150 -l SSame-species: SNP fingerprints and index hopping
# verifyBamID2: FREEMIX = contamination fraction (action threshold ~0.02);
# FREEMIX~0 with CHIPMIX~1 indicates a SWAP, not contamination.
# --SVDPrefix points to the panel resource that ships with verifyBamID2 (resource/1000g.phase3...).
verifyBamID2 --SVDPrefix /res/1000g.phase3.100k.b38.vcf.gz.dat --BamFile sample.bam --Reference ref.fa
# somalier: extract genome sketches, then relate to find swaps / identity across a cohort.
# --sites = somalier's released sites.<build>.vcf.gz (github releases), not a custom panel.
somalier extract -d sites/ --sites sites.hg38.vcf.gz -f ref.fa sample.bam
somalier relate sites/*.somalier # off-diagonal identity flags swaps
# conpair (tumor-normal): concordance + independent per-sample contaminationIndex hopping is mitigated at demultiplexing with UDI (drop impossible i7,i5 pairs); residual contamination is then quantified by the SNP-fingerprint tools above.
Common Errors
| Symptom | Cause | Solution |
|---|---|---|
| "Single species, data is clean" but a swap is suspected | Species screen is blind to same-species swaps | Run somalier / NGSCheckMate on SNP fingerprints |
| Phantom low-VAF variants in ctDNA/single-cell | Index hopping on patterned flowcell | Use UDI; quantify residual with verifyBamID2/conpair |
| Kraken2 reports dozens of trace species | Default confidence 0.0 over-reports | Raise --confidence to 0.05-0.1; raise hit-groups |
| A "human" Kraken hit on a microbial isolate | Reference/DB contamination | Use a deconned DB; treat as artifact until confirmed |
| Filtering "contaminant" reads skews composition | Removed conserved rRNA/mito too | Remove a NAMED contaminant with BBDuk, not "hits the screen" |
| PDX human counts look biased | Hard pre-filtering of ambiguous reads | Align to combined human+mouse reference instead |
References
Wingett SW, Andrews S. 2018. FastQ Screen: a tool for multi-genome mapping and quality control. F1000Research 7:1338. Wood DE, Lu J, Langmead B. 2019. Improved metagenomic analysis with Kraken 2. Genome Biology 20:257. Lu J, Breitwieser FP, Thielen P, Salzberg SL. 2017. Bracken: estimating species abundance in metagenomics data. PeerJ Computer Science 3:e104. Steinegger M, Salzberg SL. 2020. Terminating contamination: large-scale search identifies more than 2,000,000 contaminated entries in GenBank. Genome Biology 21:115. Conway T, Wazny J, Bromage A, et al. 2012. Xenome - a tool for classifying reads from xenograft samples. Bioinformatics 28(12):i172-i178. Costello M, Fleharty M, Abreu J, et al. 2018. Characterization and remediation of sample index swaps by non-redundant dual indexing. BMC Genomics 19:332. Zhang F, Flickinger M, Taliun SAG, et al. 2020. Ancestry-agnostic estimation of DNA sample contamination from sequence reads. Genome Research 30(2):185-194. Lee S, Lee S, Ouellette S, Park WY, Lee EA, Park PJ. 2017. NGSCheckMate: software for validating sample identity in next-generation sequencing studies within and across data types. Nucleic Acids Research 45(11):e103. Pedersen BS, Bhetariya PJ, Brown J, et al. 2020. Somalier: rapid relatedness estimation for cancer and germline studies using efficient genome sketches. Genome Medicine 12:62.
Related Skills
read-qc/quality-reports - Bimodal GC and overrepresented sequences flag contamination read-qc/adapter-trimming - Remove adapter contamination read-qc/rnaseq-qc - rRNA fraction as a prep-efficiency metric metagenomics/kraken-classification - Deeper taxonomic classification and profiling variant-calling/joint-calling - Where SNP-fingerprint sample swaps do the most damage
© GPTomics, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files in read-qc/contamination-screening of GPTomics/bioSkills.
- SKILL.md
- examples/screen_samples.sh
- usage-guide.md
Open the folder on GitHubat commit d91ed3d
Used in 1 other repository
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 GPTomics/bioSkills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Bio Read Qc Contamination Screening 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 |
|---|---|---|---|---|---|---|
| Bio Read Qc Contamination Screening this skillGPTomics/bioSkills | 1.2k | 1 repos | ~3.3k | 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 |
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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.
Dbsnp Database
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.
MFA Pipeline Orchestrator
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.
More from GPTomics/bioSkills
All 559 skills in this repoBio Alignment Io
GPTomics/bioSkills
Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO.
bioSkills Installer
GPTomics/bioSkills
Installs the bioSkills collection of 425 bioinformatics skills in one step, or only chosen categories, so sequencing, RNA-seq, single-cell and variant tasks get specialized help.
Bio Write Sequences
GPTomics/bioSkills
Write biological sequences to files (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO.
Amplicon Primer Clipping
GPTomics/bioSkills
Soft- or hard-clips PCR primer footprints from aligned amplicon BAMs so primer bases stop masquerading as confirmed reference sequence.
Alignment Filtering with samtools and pysam
GPTomics/bioSkills
Filters BAM alignments by FLAG bits, mapping quality and regions with samtools view or pysam, with recipes for common keep and drop cases.
Bio Alignment Indexing
GPTomics/bioSkills
Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam.
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Questions about Bio Read Qc Contamination Screening
What does Bio Read Qc Contamination Screening do?
Detects contamination in sequencing reads - cross-species (FastQ Screen, Kraken2), vector/PhiX/adapter, rRNA, and same-species cross-sample/index-hopping and sample swaps (SNP fingerprints via…. Bio Read Qc Contamination Screening is an agent skill from GPTomics/bioSkills. Detects contamination in sequencing reads - cross-species (FastQ Screen, Kraken2), vector/PhiX/adapter, rRNA, and same-species cross-sample/index-hopping and sample swaps (SNP fingerprints via verifyBamID2/NGSCheckMate/somalier).
When should I use Bio Read Qc Contamination Screening?
Bio Read Qc Contamination Screening fits situations like: suspecting cross-contamination; microbial carry-over; to decide whether to report; align to a combined reference.
How do I install Bio Read Qc Contamination Screening in Claude Code?
Run `npx skills add GPTomics/bioSkills --skill bio-read-qc-contamination-screening -a claude-code`. Or copy the skill folder (read-qc/contamination-screening in GPTomics/bioSkills) into .claude/skills/bio-read-qc-contamination-screening in your project. Claude Code loads it when a task matches its description.
How do I install Bio Read Qc Contamination Screening in Codex?
Run `npx skills add GPTomics/bioSkills --skill bio-read-qc-contamination-screening -a codex`. Or copy the skill folder (read-qc/contamination-screening in GPTomics/bioSkills) into .agents/skills/bio-read-qc-contamination-screening in your project. Codex loads it when a task matches its description.
Can I use Bio Read Qc Contamination Screening in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add GPTomics/bioSkills --skill bio-read-qc-contamination-screening -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bio-read-qc-contamination-screening, .gemini/skills/bio-read-qc-contamination-screening, .github/skills/bio-read-qc-contamination-screening and .opencode/skills/bio-read-qc-contamination-screening in your project.
What does Bio Read Qc Contamination Screening need to run?
Going by SKILL.md and its folder, Bio Read Qc Contamination Screening needs a shell for the scripts in its folder. Our summary lists: A Bash shell.
Does Bio Read Qc Contamination Screening access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Bio Read Qc Contamination Screening safe to install?
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.
What licence does Bio Read Qc Contamination Screening use?
Bio Read Qc Contamination Screening is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Bio Read Qc Contamination Screening use?
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Bio Read Qc Contamination Screening?
Skills that share tags, products or a category with Bio Read Qc Contamination Screening: 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.
Who maintains Bio Read Qc Contamination Screening?
GPTomics (a GitHub organization) maintains it in GPTomics/bioSkills, which has 1,218 GitHub stars. The repository holds 559 skills in this directory. The repository was last updated on August 15, 2026.
Source: GPTomics/bioSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.