Agent skill

Bio Workflows Atacseq Pipeline

by GPTomics in GPTomics/bioSkills

Orchestrates the end-to-end bulk ATAC-seq pipeline from FASTQ to differential accessibility and TF footprints, chaining Nextera-aware fastp QC, Bowtie2 alignment, chrM removal, dedup, a single Tn5…

MITAuto-check passedFrontend & Design

Install Bio Workflows Atacseq Pipeline

skills CLI
$ npx skills add GPTomics/bioSkills --skill bio-workflows-atacseq-pipeline -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install GPTomics/bioSkills bio-workflows-atacseq-pipeline --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/workflows/atacseq-pipeline .claude/skills/bio-workflows-atacseq-pipeline && rm -rf skills-src

Use ~/.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/

Facts

Skill name
bio-workflows-atacseq-pipeline
GitHub stars
1.2k
Used in
1 other repo
Token cost
~4.1k tokens
SKILL.md length
1,269 words
Files
4
Skills in repo
559
Repo updated
First seen
Licence
MIT

At a glance

Orchestrates the end-to-end bulk ATAC-seq pipeline from FASTQ to differential accessibility and TF footprints, chaining Nextera-aware fastp QC, Bowtie2 alignment, chrM removal, dedup, a single Tn5…

  • Works in 4 steps: There is NO input control -- the… → The Tn5 +4/-5 shift is applied EXACTLY… → chrM is removed BEFORE peak calling.… → …
  • Committing the reference build + blacklist once
  • SKILL.md covers Version Compatibility, The governing principle, Pipeline map and Made-once commitments, plus 9 more sections
  • Runs Shell and R scripts from its folder

What it does

Bio Workflows Atacseq Pipeline is an agent skill from GPTomics/bioSkills. Orchestrates the end-to-end bulk ATAC-seq pipeline from FASTQ to differential accessibility and TF footprints, chaining Nextera-aware fastp QC, Bowtie2 alignment, chrM removal, dedup, a single Tn5 +4/-5 shift, MACS3 peak calling, Corces fixed-width consensus, DiffBind/csaw differential accessibility, and TOBIAS footprinting. Use when committing the reference build + blacklist once, recognizing ATAC has NO input control (the shift-extend model IS the background), applying the Tn5 shift exactly once (never…

Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files (for example `examples/atacseq_workflow.sh` and `usage-guide.md`).

It sits in Frontend & Design, covering Bioinformatics, OSINT and Accessibility. 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

  • Committing the reference build + blacklist once
  • Recognizing ATAC has NO input control (the shift-extend model IS the background)
  • Applying the Tn5 shift exactly once (never combining -f BAMPE with --shift/--extsize)
  • Removing chrM before calling

Example prompts

  • “Use the bio-workflows-atacseq-pipeline skill to orchestrate the end-to-end bulk ATAC-seq pipeline from FASTQ to differential accessibility and TF…”
  • “/bio-workflows-atacseq-pipeline”

Requirements

  • A Bash shell

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. There is NO input control -- the shift-extend cut-site model IS the background. ATAC has no matched IP/input; peak significance comes from…
  2. The Tn5 +4/-5 shift is applied EXACTLY ONCE, after dedup and chrM removal. alignmentSieve --ATACshift (or one bedtools awk) applies it…
  3. chrM is removed BEFORE peak calling. Mitochondrial reads dominate ATAC libraries (often 20-50%, less with Omni-ATAC); leaving them in…
  4. Differential accessibility requires a FIXED-WIDTH consensus peakset. Variable-width MACS peaks make per-sample counts non-comparable…

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 and R), 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 Workflows Atacseq Pipeline loads about 4.1k tokens when it runs. Until then it costs about 203 tokens; SKILL.md has 1,269 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~203
When it runs · the whole SKILL.md, loaded when a task matches
~4.1k

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). 1,269 words, ~4,148 tokens.

Download SKILL.mdSave it as .claude/skills/bio-workflows-atacseq-pipeline/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
bio-workflows-atacseq-pipeline
description
Orchestrates the end-to-end bulk ATAC-seq pipeline from FASTQ to differential accessibility and TF footprints, chaining Nextera-aware fastp QC, Bowtie2 alignment, chrM removal, dedup, a single Tn5 +4/-5 shift, MACS3 peak calling, Corces fixed-width consensus, DiffBind/csaw differential accessibility, and TOBIAS footprinting. Use when committing the reference build + blacklist once, recognizing ATAC has NO input control (the shift-extend model IS the background), applying the Tn5 shift exactly once (never combining -f BAMPE with --shift/--extsize), removing chrM before calling, building a fixed-width consensus so per-sample counts are comparable, or choosing MACS3 vs Genrich vs HMMRATAC. Hands mechanism to the atac-seq component skills; not a re-teach of any single step.
tool_type
mixed
primary_tool
MACS3
workflow
true
depends_on
read-qc/fastp-workflow, read-alignment/bowtie2-alignment, alignment-files/duplicate-handling, atac-seq/atac-peak-calling, atac-seq/atac-qc…

Version Compatibility

Reference examples tested with: Bowtie2 2.5.3+, MACS3 3.0+, Genrich 0.6+, bedtools 2.31+, deepTools 3.5+ (alignmentSieve), fastp 0.23+, samtools 1.19+, DiffBind 3.12+, TOBIAS 0.16+

Before using code patterns, verify installed versions match. If versions differ:

  • R: packageVersion('<pkg>') then ?function_name to verify parameters
  • CLI: <tool> --version then <tool> --help to 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.

Note: macs3 callpeak -f BAMPE uses real fragment lengths and IGNORES --shift/--extsize/--nomodel; the cut-site style needs -f BAM/-f BED on Tn5-shifted reads. alignmentSieve --ATACshift applies the +4/-5 shift once. ENCODE ATAC-seq v3 and v4 QC thresholds are not interchangeable. Confirm in-tool before quoting.

ATAC-seq Pipeline

"Run ATAC-seq from FASTQ to differential accessibility and footprints" -> Chain QC/trim, alignment, chrM removal, dedup, a single Tn5 shift, peak calling, fixed-width consensus, differential accessibility, and footprinting.

  • CLI + R: fastp -> bowtie2 -> drop chrM -> markdup -> Tn5 shift (once) -> macs3 -> Corces consensus -> DiffBind/csaw -> TOBIAS

This is a workflow skill: it owns the chaining decisions and hand-offs, not the internals of any one step. Every step below cross-references the component skill that teaches its mechanism.

The governing principle

ATAC-seq differs from ChIP-seq at four seams, and each is where the analysis goes wrong.

  1. There is NO input control -- the shift-extend cut-site model IS the background. ATAC has no matched IP/input; peak significance comes from local lambda over the Tn5 insertion signal. Do not invent a "control"; commit instead to the build + ENCODE blacklist (removed before calling) as the coordinate frame.
  2. The Tn5 +4/-5 shift is applied EXACTLY ONCE, after dedup and chrM removal. alignmentSieve --ATACshift (or one bedtools awk) applies it. Applying it twice, or combining -f BAMPE with --shift/--extsize (silently ignored), misplaces every cut site. Pick ONE calling mode: cut-site (-f BAM/-f BED + --nomodel --shift -75 --extsize 150) OR fragment (-f BAMPE on shifted reads, NO --shift).
  3. chrM is removed BEFORE peak calling. Mitochondrial reads dominate ATAC libraries (often 20-50%, less with Omni-ATAC); leaving them in inflates depth and distorts FRiP and normalization.
  4. Differential accessibility requires a FIXED-WIDTH consensus peakset. Variable-width MACS peaks make per-sample counts non-comparable. Build the Corces 501 bp iterative-overlap consensus (Corces 2018) so every region is the same width before counting; DiffBind/csaw then count into uniform intervals.

Reporting corollary: ENCODE ATAC v3 and v4 define TSS-enrichment/FRiP thresholds differently -- pick one standard and state which; do not mix rows across versions.

Pipeline map

FASTQ (paired, Nextera)
  | [1] QC & trim -----------------> fastp (Nextera adapters)   (read-qc/fastp-workflow)
  v
  | [2] Align ---------------------> bowtie2 --very-sensitive -X 2000   (read-alignment/bowtie2-alignment)
  v     ^-- commitment: build + ENCODE blacklist (NO input control)
  | [3] Drop chrM (BEFORE dedup/peaks) -> mito can be 20-50% of reads
  v
  | [4] Dedup --------------------> markdup -r   (alignment-files/duplicate-handling)
  v
  | [5] Tn5 shift ONCE ------------> alignmentSieve --ATACshift (+4/-5)
  v     ^-- pick ONE calling mode; never BAMPE + --shift
  | [6] Peak calling -------------> macs3 (cut-site -f BAM --shift/--extsize | -f BAMPE)  (atac-seq/atac-peak-calling)
  v
  | [7] Fixed-width consensus -----> Corces 501 bp iterative overlap   (atac-seq/consensus-peakset)
  v
  | [8] QC + differential + footprints -> TSS/FRiP/fragment; DiffBind/csaw; TOBIAS  (atac-seq/atac-qc, differential-accessibility, footprinting)
  v
Accessibility peaks + differential regions + TF activity

Made-once commitments

CommitmentChoiceConsequence inherited downstream
Build + blacklistOne build; ENCODE blacklist (removed before calling)ATAC has no input, so the blacklist + shift-extend model ARE the background control
Tn5 shiftApplied ONCE (--ATACshift), then ONE calling modeDouble-shift or BAMPE+--shift misplaces cut sites
chrM handlingRemoved before dedup/peaksMito reads (20-50%) inflate depth, FRiP, normalization
Differential intervalFixed-width Corces 501 bp consensusVariable-width peaks make per-sample counts non-comparable

The canonical order and why

  1. QC/trim with Nextera adapters (CTGTCTCTTATACACATCT).
  2. Align (bowtie2 --very-sensitive -X 2000) so the full nucleosome-spanning fragment distribution is captured.
  3. Remove chrM, then compute NRF/PBC, then dedup -- order-trap on both ends: markdup -r physically removes duplicates, so NRF/PBC1 computed afterwards are identically 1.0; and mito reads are over-amplified, so computing them before chrM removal measures chrM chemistry, not nuclear-library complexity. The binding constraint is PRE-DEDUP. Mito must go before peak calling regardless.
  4. Dedup (collate -> fixmate -m -> sort -> markdup -r).
  5. Tn5 shift ONCE (alignmentSieve --ATACshift).
  6. Call peaks in ONE mode -- order-trap: -f BAMPE + --shift/--extsize silently drops the flags.
  7. Build the fixed-width consensus (Corces 501 bp) -- order-trap: differential on variable-width peaks is not comparable.
  8. QC, differential (DiffBind/csaw on the consensus), footprinting (TOBIAS).

Choosing the caller and calling mode

Pipeline-level selection only; mechanism lives in the component skills.

ForkLean towardHand off to
CallerMACS3 (standard); Genrich (-j ATAC mode: handles replicates + chrM + blacklist in one pass); HMMRATAC (nucleosome-aware HMM)atac-seq/atac-peak-calling
Calling modeCut-site -f BAM/-f BED + --nomodel --shift -75 --extsize 150 (ENCODE smoothing window on shifted reads) vs fragment -f BAMPE on shifted reads (no --shift)atac-seq/atac-peak-calling
ConsensusCorces 2018 iterative-overlap fixed-width 501 bpatac-seq/consensus-peakset
DifferentialDiffBind / csaw / DESeq2 on the fixed-width count matrix; spike-in for global shiftsatac-seq/differential-accessibility

Primary path: Bowtie2 + Tn5 shift + MACS3

Goal: turn Nextera FASTQ into shifted, chrM-free peaks ready for a fixed-width consensus.

Approach: align with a wide insert window, drop chrM, dedup, Tn5-shift once, then call in ONE mode. Full runnable script: examples/atacseq_workflow.sh; differential: examples/differential_atac.R.

bash
bowtie2 -p 8 -x bt2_index/genome -1 trimmed/${s}_R1.fq.gz -2 trimmed/${s}_R2.fq.gz \
    --very-sensitive --no-mixed --no-discordant -X 2000 2> aligned/${s}.log \
  | samtools view -@4 -bS -q 30 -f 2 - | samtools sort -@4 -o aligned/${s}.sorted.bam
samtools index aligned/${s}.sorted.bam

# Drop chrM BEFORE dedup/peaks (mito dominates ATAC), then dedup
samtools idxstats aligned/${s}.sorted.bam | cut -f1 | grep -v -e '^chrM$' -e '^MT$' \
  | xargs samtools view -b aligned/${s}.sorted.bam > aligned/${s}.noMT.bam
samtools collate -@8 -O -u aligned/${s}.noMT.bam | samtools fixmate -m -u - - \
  | samtools sort -@8 -u - | samtools markdup -r -@8 - aligned/${s}.dedup.bam
samtools index aligned/${s}.dedup.bam            # alignmentSieve needs an indexed input BAM

# Tn5 +4/-5 shift ONCE
alignmentSieve -b aligned/${s}.dedup.bam -o aligned/${s}.shifted.bam --ATACshift -p 8
samtools index aligned/${s}.shifted.bam

# Remove ENCODE blacklist regions BEFORE calling (the made-once commitment above; see the example script)
# Everything downstream (peaks, counts, footprints) consumes ${s}.filt.bam, never ${s}.shifted.bam.
# NOTE: examples/atacseq_workflow.sh names its blacklist-FILTERED output `.shifted.bam`; same reads,
# different name. Match on the step, not the suffix.
bedtools intersect -v -a aligned/${s}.shifted.bam -b "$BLACKLIST" > aligned/${s}.filt.bam
samtools index aligned/${s}.filt.bam

# Cut-site calling on the shifted, blacklist-filtered reads (ONE mode; do NOT also use -f BAMPE with these flags)
macs3 callpeak -t aligned/${s}.filt.bam -f BAM -g hs -n ${s} --outdir peaks \
    --nomodel --shift -75 --extsize 150 --keep-dup all -q 0.01

For the ENCODE 4 IDR + pseudoreplicate pipeline and the Corces 501 bp iterative-overlap consensus, see atac-seq/atac-peak-calling and atac-seq/consensus-peakset.

Show full SKILL.md (513 more words)Show less

Differential accessibility and footprinting

Goal: compare accessibility across conditions on comparable intervals, then read TF activity.

Approach: count into the fixed-width consensus with DiffBind (or csaw), then run the TOBIAS three-step (ATACorrect -> ScoreBigwig -> BINDetect) for footprints.

r
library(DiffBind)                                  # counts into the fixed-width consensus
dba <- dba(sampleSheet = samples)                  # bamReads = shifted BAMs, Peaks = per-sample narrowPeak
dba <- dba.count(dba)                              # use summits/consensus for uniform width
dba <- dba.normalize(dba); dba <- dba.contrast(dba, categories = DBA_CONDITION)
dba <- dba.analyze(dba); report <- dba.report(dba)
bash
# peaks/consensus.bed is the Corces 501 bp FIXED-WIDTH consensus from atac-seq/consensus-peakset (step 7).
# It is NOT peaks/consensus_peaks.narrowPeak, which is the variable-width pooled MACS3 call; build the
# fixed-width set first or these three commands have no input.
# TOBIAS three-step: bias-correct -> score -> detect bound motifs (differential across two conditions).
# Footprint on the BLACKLIST-FILTERED reads (${s}.filt.bam), the same reads MACS3 called peaks from --
# blacklist regions are artifact pileups, and bias-correcting over them corrupts the footprint scores.
TOBIAS ATACorrect -b aligned/${s}.filt.bam -g genome.fa -p peaks/consensus.bed --outdir foot --cores 8
TOBIAS ScoreBigwig --signal foot/${s}_corrected.bw --regions peaks/consensus.bed --output foot/${s}.bw --cores 8
TOBIAS BINDetect --motifs motifs.jaspar --signals foot/ctrl.bw foot/treat.bw --genome genome.fa \
    --peaks peaks/consensus.bed --outdir foot/bindetect --cores 8

QC checkpoints between steps

AfterGateInterpretation
AlignmentMapping >80%, mito <20% (Omni-ATAC lower)High mito = suboptimal lysis; drop before calling
PRE-dedupNRF >0.8, PBC1 >0.8Low complexity = over-amplification/low input; compute before dedup
PeaksFRiP >0.2, TSS enrichment >5 (v3)Low TSS/FRiP = over/under-digestion or degraded chromatin (atac-seq/atac-qc)
Fragment sizeNFR <100 bp, mono ~200 bp, di ~400 bp periodicityLoss of nucleosome periodicity = over-digestion (Tn5:DNA too high)
ConsensusFixed-width (501 bp) built before countingVariable-width peaks make counts non-comparable

Common Errors

SymptomCauseFix
Depth/FRiP dominated by one contig; few real peakschrM not removed before callingDrop chrM/MT before dedup and peak calling
Cut sites offset / footprints smearedTn5 shift applied twice, or -f BAMPE used with --shift/--extsizeShift ONCE; pick ONE calling mode (cut-site -f BAM OR fragment -f BAMPE)
Differential counts not comparable across samplesCounted into variable-width MACS peaksBuild the Corces 501 bp fixed-width consensus first
Looked for an input/IgG track and found noneATAC has no input controlUse the blacklist + shift-extend model as background; do not fabricate a control
QC numbers disagree with a referenceMixed ENCODE v3 and v4 thresholdsPick one ENCODE version and report which

Pipeline map (hand-offs)

  • read-qc/fastp-workflow - Nextera adapter trimming
  • read-alignment/bowtie2-alignment - the aligner, wide insert window
  • alignment-files/duplicate-handling - collate/fixmate/sort/markdup order
  • atac-seq/atac-peak-calling - MACS3/Genrich/HMMRATAC, ENCODE 4 IDR, calling modes
  • atac-seq/atac-qc - TSS enrichment, FRiP, NRF/PBC, fragment periodicity
  • atac-seq/consensus-peakset - Corces 2018 iterative-overlap fixed-width consensus
  • atac-seq/differential-accessibility - DiffBind/csaw/DESeq2 on the consensus
  • atac-seq/footprinting - TOBIAS three-step and per-TF failure modes
  • atac-seq/nucleosome-positioning - V-plot, NucleoATAC, +1 nucleosome

The complete runnable scripts are in this skill's examples/ (atacseq_workflow.sh, differential_atac.R).

  • database-access/sra-data - Pull ATAC-seq FASTQ from SRA / ENA
  • database-access/geo-data - Resolve GEO accessions for ATAC datasets
  • read-qc/fastp-workflow - Nextera adapter trimming and quality filtering
  • read-alignment/bowtie2-alignment - Standard ATAC-seq aligner
  • alignment-files/duplicate-handling - MarkDuplicates pre-peak-calling
  • atac-seq/atac-peak-calling - MACS3 / Genrich / HMMRATAC details, ENCODE 4 IDR
  • atac-seq/atac-qc - TSS enrichment, FRiP, NRF/PBC1/PBC2 details
  • atac-seq/consensus-peakset - Corces 2018 iterative-overlap fixed-width consensus
  • atac-seq/differential-accessibility - DiffBind / csaw / DESeq2; spike-in normalization
  • atac-seq/footprinting - TOBIAS three-step; per-TF failure modes
  • atac-seq/motif-deviation - chromVAR for motif accessibility variability
  • atac-seq/nucleosome-positioning - V-plot, NucleoATAC, +1 nucleosome
  • atac-seq/single-cell-atac - For scATAC instead of bulk
  • atac-seq/co-accessibility - Cicero cis-regulatory inference
  • atac-seq/enhancer-gene-linking - ABC, ENCODE-rE2G enhancer-gene mapping
  • atac-seq/deep-learning-atac - chromBPNet variant-effect prediction
  • atac-seq/allele-specific-accessibility - WASP + caQTL mapping
  • chip-seq/peak-annotation - Annotate ATAC peaks to genes

References

  • Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ (2013) Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nature Methods 10:1213-1218. DOI 10.1038/nmeth.2688. (original ATAC-seq.)
  • Corces MR, Trevino AE, Hamilton EG, et al (2017) An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nature Methods 14:959-962. DOI 10.1038/nmeth.4396. (Omni-ATAC.)
  • Corces MR, Granja JM, Shams S, et al (2018) The chromatin accessibility landscape of primary human cancers. Science 362:eaav1898. DOI 10.1126/science.aav1898. (fixed-width iterative-overlap consensus peakset.)
  • Bentsen M, Goymann P, Schultheis H, et al (2020) ATAC-seq footprinting unravels kinetics of transcription factor binding during zygotic genome activation. Nature Communications 11:4267. DOI 10.1038/s41467-020-18035-1. (TOBIAS.)

© 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 3 other files in workflows/atacseq-pipeline of GPTomics/bioSkills.

  • SKILL.md
  • examples/atacseq_workflow.sh
  • examples/differential_atac.R
  • 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

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Questions about Bio Workflows Atacseq Pipeline

What does Bio Workflows Atacseq Pipeline do?

Orchestrates the end-to-end bulk ATAC-seq pipeline from FASTQ to differential accessibility and TF footprints, chaining Nextera-aware fastp QC, Bowtie2 alignment, chrM removal, dedup, a single Tn5…. Bio Workflows Atacseq Pipeline is an agent skill from GPTomics/bioSkills. Orchestrates the end-to-end bulk ATAC-seq pipeline from FASTQ to differential accessibility and TF footprints, chaining Nextera-aware fastp QC, Bowtie2 alignment, chrM removal, dedup, a single Tn5 +4/-5 shift, MACS3 peak calling, Corces fixed-width consensus, DiffBind/csaw differential accessibility, and TOBIAS footprinting.

When should I use Bio Workflows Atacseq Pipeline?

Bio Workflows Atacseq Pipeline fits situations like: committing the reference build + blacklist once; recognizing ATAC has NO input control (the shift-extend model IS the background); applying the Tn5 shift exactly once (never combining -f BAMPE with --shift/--extsize); removing chrM before calling.

How do I install Bio Workflows Atacseq Pipeline in Claude Code?

Run `npx skills add GPTomics/bioSkills --skill bio-workflows-atacseq-pipeline -a claude-code`. Or copy the skill folder (workflows/atacseq-pipeline in GPTomics/bioSkills) into .claude/skills/bio-workflows-atacseq-pipeline in your project. Claude Code loads it when a task matches its description.

How do I install Bio Workflows Atacseq Pipeline in Codex?

Run `npx skills add GPTomics/bioSkills --skill bio-workflows-atacseq-pipeline -a codex`. Or copy the skill folder (workflows/atacseq-pipeline in GPTomics/bioSkills) into .agents/skills/bio-workflows-atacseq-pipeline in your project. Codex loads it when a task matches its description.

Can I use Bio Workflows Atacseq Pipeline 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-workflows-atacseq-pipeline -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-workflows-atacseq-pipeline, .gemini/skills/bio-workflows-atacseq-pipeline, .github/skills/bio-workflows-atacseq-pipeline and .opencode/skills/bio-workflows-atacseq-pipeline in your project.

What does Bio Workflows Atacseq Pipeline need to run?

Going by SKILL.md and its folder, Bio Workflows Atacseq Pipeline needs a shell and R for the scripts in its folder. Our summary lists: A Bash shell.

Does Bio Workflows Atacseq Pipeline 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 Workflows Atacseq Pipeline 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 Workflows Atacseq Pipeline use?

Bio Workflows Atacseq Pipeline 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 Workflows Atacseq Pipeline use?

About 4.1k tokens (SKILL.md is roughly 17k 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 Workflows Atacseq Pipeline?

Skills that share tags, products or a category with Bio Workflows Atacseq Pipeline: Bio Atac Seq Differential Accessibility (FreedomIntelligence/OpenClaw-Medical-Skills, 3.1k stars), Best Practices (tech-leads-club/agent-skills, 7k stars), Salesforce Component Standards (github/awesome-copilot, 40k stars) and Hot3d (wu-yc/LabClaw, 1.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bio Workflows Atacseq Pipeline?

GPTomics (a GitHub organization) maintains it in GPTomics/bioSkills, which has 1,217 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.