bam-to-fragment-file-conversion

bam-to-fragment-file-conversion is a skill for Claude Code, Codex from HolobiomicsLab/asb-skill-collections. It costs 72 tokens per session (1,384 once invoked), scanned A, original, Apache-2.0.

A preprocessing step that converts coordinate-sorted BAM files from single-cell ATAC-seq into compressed fragment files. Single-cell ATAC-seq measures open regions of DNA in individual cells, and the fragment file keeps coordinates, cell barcodes, and quality information together.

In plain words
What is it for?
Use it before building matrices, grouping cells into clusters, or finding open-DNA regions in SnapATAC2, when the BAM file is coordinate-sorted and contains cell barcodes.
Why use it?
Downstream SnapATAC2 analysis expects an efficient fragment-level input rather than the original alignment file. The conversion also preserves which cell produced each fragment.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it before building matrices, grouping cells into clusters, or finding open-DNA regions in SnapATAC2, when the BAM file is coordinate-sorted and contains cell barcodes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/holobiomicslab/asb-skill-collections/bam-to-fragment-file-conversion
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add HolobiomicsLab/asb-skill-collections --skill bam-to-fragment-file-conversion
Clone the repo
git clone --depth 1 https://github.com/HolobiomicsLab/asb-skill-collections

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for bam-to-fragment-file-conversion

README.md
[![agentmods](https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/bam-to-fragment-file-conversion/github.svg)](https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/bam-to-fragment-file-conversion)
Your own site
<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/bam-to-fragment-file-conversion"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/bam-to-fragment-file-conversion/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for bam-to-fragment-file-conversion

Your own site · 80×15
<a href="https://agentmods.dev/skills/holobiomicslab/asb-skill-collections/bam-to-fragment-file-conversion"><img src="https://agentmods.dev/badge/skills/holobiomicslab/asb-skill-collections/bam-to-fragment-file-conversion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,384 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.01384
Opus 5 $0.00036 $0.00692
Sonnet 5 $0.00014 $0.00277
Haiku 4.5 $0.00007 $0.00138

Measured 12d ago against content hash 04405f7d05e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

bam-to-fragment-file-conversion scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

collections/epigenomics/v1/skills/bam-to-fragment-file-conversion/SKILL.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

BAM-to-fragment-file conversion

Summary

Convert coordinate-sorted BAM files into compressed fragment files (BED.gz or .zst format) containing fragment coordinates, cell barcodes, and quality metrics. This preprocessing step is essential for downstream single-cell ATAC-seq analysis in SnapATAC2.

When to use

When you have coordinate-sorted BAM files from single-cell ATAC-seq experiments (e.g., 10X Genomics scATAC-seq) and need to generate a compressed fragment file for efficient downstream analysis. Use this step before matrix generation, clustering, or peak calling in SnapATAC2.

When NOT to use

  • Input BAM file is not coordinate-sorted; use samtools sort -c to validate or re-sort first.
  • Fragment file already exists and has been validated; re-running is redundant unless BAM has been re-aligned.
  • Working with RNA-seq or other modalities that do not generate fragment-level data (use pp.import_fragments for pre-existing fragment files instead).

Inputs

  • coordinate-sorted BAM file
  • BAM file with cell barcode information in header (for 10X or tagged BAM)

Outputs

  • compressed fragment file (BED.gz or .zst format)
  • fragment coordinates with cell barcodes and quality metrics

How to apply

Load the coordinate-sorted BAM file and invoke pp.make_fragment_file with source='10x' if the input is a 10X BAM file, or with default settings for standard BAM inputs. The function processes alignments, extracts fragment coordinates (chromosome, start, end), assigns cell barcodes from the BAM header, and computes quality metrics including duplication rate. Output is generated in compressed format (BED.gz or zst) with standard BED fields plus barcode and count columns. Validate output by confirming the file is non-empty, contains properly formatted BED columns, and that QC metrics (duplication rate, read counts per cell) are accessible for downstream QC decisions.

  • SnapATAC2 (Python/Rust framework providing pp.make_fragment_file function for BAM-to-fragment conversion with built-in quality metrics and barcode extraction) — https://github.com/scverse/SnapATAC2
  • precellar (Alternative universal preprocessing package that automates BAM-to-fragment conversion for multiple single-cell genomics platforms via alignment and fragment file generation) — https://github.com/regulatory-genomics/precellar
  • samtools (Utility for BAM file validation, sorting, and inspection before fragment file conversion)

Read the full file on GitHub · 98 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 98 lines · 72 tokens per session scan A 04405f7d05e9

Subscribe to this mod's changes

bam-to-fragment-file-conversion is a skill published in the GitHub repository HolobiomicsLab/asb-skill-collections (15 stars, last pushed yesterday), licensed Apache-2.0. It adds 72 tokens to every session and 1,384 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

medical-research-literature-reader-pro

A medical-research-native literature reading skill for users with clinical, bioinformatics, translational, and basic experimental backgrounds. Use this skill whenever a user wants to read, analyze, critique, or interpret a medical or scientific paper — whether they provide a PDF, abstract, DOI, PMID, or just a title.…

aipoch/medical-research-skills · 199 tokens

anatomy-quiz-master

Generate interactive anatomy quizzes for medical education with multiple.

aipoch/medical-research-skills · 17 tokens

decision-curve-analysis

Use when evaluating the clinical utility of a binary prediction model from a single clinical CSV file by fitting a logistic decision-curve model, plotting decision and clinical-impact curves, and exporting summary outputs. NOT for: survival calibration, ROC-only discrimination analysis, nomogram construction, or…

aipoch/medical-research-skills · 64 tokens

elastic-net-feature-selection

Use when selecting predictive genes or other molecular features from bulk expression matrices for binary case-vs-control classification with elastic net logistic regression, including coefficient path and cross-validation plots. Trigger keywords: elastic net, glmnet, feature selection, binary classification…

aipoch/medical-research-skills · 83 tokens

external-model-validation

Use when validating an existing prognostic risk signature on an external bulk expression cohort with survival outcomes, producing risk scores, Kaplan-Meier curves, risk distribution plots, heatmap, and time-dependent ROC curves. NOT for: model training, feature selection, nomogram construction, calibration analysis…

aipoch/medical-research-skills · 66 tokens

roc-diagnostic-performance

Use when evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves, exporting coefficient and AUC tables together with a ROC PDF. NOT for: survival analysis, time-to-event outcomes, multiclass classification, calibration curves, decision-curve analysis, or…

aipoch/medical-research-skills · 64 tokens