Agent skill

Bio Hi C Analysis Contact Pairs

by GPTomics in GPTomics/bioSkills

Turns Hi-C/Micro-C FASTQ into a deduplicated, filtered .pairs file with pairtools and decides whether the library worked.

MITAuto-check passedData & Analytics

Install Bio Hi C Analysis Contact Pairs

skills CLI
$ npx skills add GPTomics/bioSkills --skill bio-hi-c-analysis-contact-pairs -a claude-code

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

GitHub CLI
$ gh skill install GPTomics/bioSkills bio-hi-c-analysis-contact-pairs --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/hi-c-analysis/contact-pairs .claude/skills/bio-hi-c-analysis-contact-pairs && 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-hi-c-analysis-contact-pairs
GitHub stars
1.2k
Used in
1 other repo
Token cost
~4.7k tokens
SKILL.md length
2,031 words
Files
3
Skills in repo
559
Repo updated
First seen
Licence
MIT

At a glance

Turns Hi-C/Micro-C FASTQ into a deduplicated, filtered .pairs file with pairtools and decides whether the library worked.

  • Works in 3 steps: % long-range cis is the one-number… → The ligation junction lives INSIDE the… → Keep UU AND rescued UC; selecting only…
  • Processing Hi-C/Micro-C/Omni-C reads into pairs
  • SKILL.md covers Version Compatibility, The Single Most Important…, Aligner Taxonomy and Decision Tree by Scenario, plus 10 more sections
  • Runs Shell scripts from its folder

What it does

Bio Hi C Analysis Contact Pairs is an agent skill from GPTomics/bioSkills. Turns Hi-C/Micro-C FASTQ into a deduplicated, filtered .pairs file with pairtools and decides whether the library worked. Covers the bwa mem -SP5M / bwa-mem2 / chromap --preset hic alignment idiom (mates mapped as independent single-end reads), pairtools parse vs parse2 and the walks-policy choice (5unique pairwise vs all for Pore-C/Micro-C concatemers), pair-type classification (keep UU and rescued UC), dedup (PCR vs optical/by-tile), select by pairtype/MAPQ/distance, restriction-fragment handling (restrict…

Its SKILL.md is about 4.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `examples/fastq_to_pairs.sh` and `usage-guide.md`).

It sits in Data & Analytics, covering Forecasting and time series. 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

  • Processing Hi-C/Micro-C/Omni-C reads into pairs
  • Judging library quality
  • Handling multi-enzyme
  • Restriction-agnostic protocols

Example prompts

  • “Use the bio-hi-c-analysis-contact-pairs skill to turn Hi-C/Micro-C FASTQ into a deduplicated, filtered .pairs file with pairtools and decides…”
  • “/bio-hi-c-analysis-contact-pairs”

Requirements

  • A Bash shell

Workflow steps

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

  1. % long-range cis is the one-number quality metric; trans is the noise floor. True crosslink-ligation contacts are overwhelmingly cis and…
  2. The ligation junction lives INSIDE the read, so a local/split aligner aligning mates independently is required. A single read often…
  3. Keep UU AND rescued UC; selecting only UU silently discards every rescued ligation. A naive select pair_type=="UU" throws away the…

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 Hi C Analysis Contact Pairs loads about 4.7k tokens when it runs. Until then it costs about 264 tokens; SKILL.md has 2,031 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~264
When it runs · the whole SKILL.md, loaded when a task matches
~4.7k

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). 2,031 words, ~4,748 tokens.

Download SKILL.mdSave it as .claude/skills/bio-hi-c-analysis-contact-pairs/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
bio-hi-c-analysis-contact-pairs
description
Turns Hi-C/Micro-C FASTQ into a deduplicated, filtered .pairs file with pairtools and decides whether the library worked. Covers the bwa mem -SP5M / bwa-mem2 / chromap --preset hic alignment idiom (mates mapped as independent single-end reads), pairtools parse vs parse2 and the walks-policy choice (5unique pairwise vs all for Pore-C/Micro-C concatemers), pair-type classification (keep UU and rescued UC), dedup (PCR vs optical/by-tile), select by pair_type/MAPQ/distance, restriction-fragment handling (restrict, Arima dual-enzyme, Micro-C/DNase fragment-free), and allele-specific phasing (pairtools phase to two coolers). The library-QC decision uses % long-range cis as the one-number quality metric, trans as the noise floor, orientation balance as fragment-map-free dangling-end/self-circle QC, and % duplicates as a complexity proxy. Use when processing Hi-C/Micro-C/Omni-C reads into pairs, judging library quality, handling multi-enzyme or restriction-agnostic protocols, or generating allele-specific contacts.
tool_type
cli
primary_tool
pairtools

Version Compatibility

Reference examples tested with: pairtools 1.1+, bwa 0.7.17+ (or bwa-mem2 2.2+), chromap 0.2+, samtools 1.19+, cooler 0.10+

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

  • CLI: <tool> --version then <tool> --help to confirm flags

pairtools defaults have shifted across releases (e.g. parse --max-molecule-size is 750 bp in 1.1.x; dedup --backend defaults to scipy). parse and parse2 report DIFFERENT positions by default - confirm --report-position before mixing outputs. If a command errors, introspect with pairtools <subcommand> --help and adapt rather than retrying.

Hi-C Contact Pairs

"Turn my Hi-C reads into clean contacts and tell me if the library worked" -> Align mates independently through ligation junctions, classify and deduplicate pairs to a 5'-canonical .pairs file, then read the cis/trans and orientation statistics to decide library quality before any matrix is built.

  • CLI: bwa mem -SP5M ref.fa R1.fq R2.fq | pairtools parse -c chrom.sizes | pairtools sort | pairtools dedup | pairtools stats

The Single Most Important Modern Insight -- The Read Count Is a Lie Until Pairs Are Classified; Library Quality Is Decided in pairtools, Not in the Aligner

A Hi-C library's usable signal is not "reads sequenced" - it is the uniquely-mapped, deduplicated, long-range cis contacts. Everything between FASTQ and the matrix exists to strip a specific artifact of proximity-ligation chemistry, and the diagnostic ratios from pairtools stats reveal whether the experiment succeeded before any compute is spent binning it. Three load-bearing consequences:

  1. % long-range cis is the one-number quality metric; trans is the noise floor. True crosslink-ligation contacts are overwhelmingly cis and distance-decaying. Random ligation between two unrelated molecules in solution is as likely to be trans as cis-far, so trans% is a direct readout of the spurious-ligation floor. A good in-situ human library runs cis>=1kb ~50-65%, inter-chromosomal <10%. But these numbers are genome-size dependent - a yeast or bacterial genome legitimately has higher expected trans (more inter-chromosomal volume per cis distance). Never apply a human trans threshold to a microbe.

  2. The ligation junction lives INSIDE the read, so a local/split aligner aligning mates independently is required. A single read often sequences through a ligation junction (locus A | locus B within one read). An end-to-end aligner soft-clips or mis-maps it and the contact is lost. bwa mem -SP5M aligns R1 and R2 as independent single-end reads (-SP skips mate rescue and pairing - proper-pair logic would destroy every long-range and trans contact) and marks the 5'-most chimeric segment primary (-5, the anchor for pairtools' 5' convention). The chimera fraction rises with read length, so on 150bp PE and on Micro-C long reads this is a large, real chunk of contacts.

  3. Keep UU AND rescued UC; selecting only UU silently discards every rescued ligation. A naive select pair_type=="UU" throws away the chimeric reads pairtools successfully reconstructed (UC = combined-unique) - a meaningful fraction on long reads. The 4DN standard keeps UU and UC.

Aligner Taxonomy

AlignerRoleHi-C invocationWhen
bwa mem -SP5Mreference standard; local/split alignment reconstructs in-read junctionsbwa mem -SP5M -t N ref.fa R1 R2default; best inter-contig accuracy in benchmarks
bwa-mem2drop-in faster reimplementation, identical output, same flagsbwa-mem2 mem -SP5M -t N ref.fa R1 R2when speed matters and the larger index fits RAM
chromap --preset hicultrafast integrated align + dedup + pairs (4DN .pairs out)chromap --preset hic -x idx -r ref.fa -1 R1 -2 R2 -o out.pairs~10x faster scans; trades fine walk-policy control for speed

-SP5M, letter by letter: -S skip mate rescue; -P skip pairing (no proper-pair rescue); together -SP align mates as independent single-end reads. -5 mark the 5'-most split segment primary (anchors the 5' convention). -M is legacy compatibility only (secondary flag 256 vs supplementary 2048); pairtools handles either - never agonize over -M, never drop -SP5.

Decision Tree by Scenario

ScenarioRecommendedWhy
Standard in-situ/Omni-C, FASTQ -> matrixbwa mem -SP5M -> parse (5unique) -> sort -> dedup -> statsthe 4DN/distiller default; restriction-agnostic
Fastest scan, control not criticalchromap --preset hicintegrated align+dedup+pairs ~10x faster
Multi-way contacts (Pore-C, MC-3C, Micro-C walks)parse --walks-policy all or parse2 --expand5unique COLLAPSES concatemers to pairwise silently
Micro-C / DNase Hi-CNO fragment map; do NOT apply a 1kb min-distance cutsub-1kb (nucleosome ladder) is signal, not artifact
Arima / Hi-C 3.0 dual-enzyme, fragment-levelfragment file must encode BOTH motifs (restrict -f)a single-enzyme digest file is silently wrong
Repeat-heavy genome / stringent loop anchorsraise parse --min-mapq 30reclassifies borderline reads M, drops repeat false anchors
Allele-specific / diploid foldingdiploid ref + -XA suboptimal hits -> pairtools phase -> two coolersneeds the suboptimal-score gap to resolve haplotypes
Decide whether to sequence deepercomplexity curve from dup model / preseq lc_extrapa bare dup% without depth is meaningless
Build the matrix from clean pairs-> hic-data-io (cooler cload pairs)binning happens after classification/dedup
Annotate boundary/anchor coordinates-> genome-intervals/bed-file-basicspairs are 1-based, half-open conventions differ

Align: Mates as Independent Single-End Reads

bash
bwa index ref.fa                                            # or bwa-mem2 index ref.fa
bwa mem -SP5M -t 16 ref.fa R1.fq.gz R2.fq.gz | \            # -SP: independent SE; -5: 5' segment primary
    samtools view -b -@ 8 - > aligned.bam
# chromap fast path (integrated align + dedup + 4DN pairs, no separate pairtools needed):
# chromap -i -r ref.fa -o idx && \
# chromap --preset hic -x idx -r ref.fa -1 R1.fq.gz -2 R2.fq.gz -o sample.pairs

Parse, Sort, Dedup, Select: the pairtools Core

bash
# Parse alignments into a 5'-canonical .pairs. min-mapq 1 (default) is permissive: only MAPQ-0 is "multi".
pairtools parse -c chrom.sizes --walks-policy 5unique --min-mapq 1 \
    --add-columns mapq --drop-sam aligned.bam | \
pairtools sort --nproc 8 | \                                # block-sort; flips to upper-triangular (5'-canonical)
pairtools dedup --max-mismatch 3 --mark-dups \              # within 3bp on both sides = duplicate; tag DD
    --output-stats sample.dedup.stats | \
pairtools select '(pair_type=="UU") or (pair_type=="UC")' \ # keep both-unique AND rescued chimeric
    -o sample.valid.pairs.gz

Dedup MUST run on a flipped, 5'-canonical file (sort does the flip); on a non-canonical file dedup under-collapses and dup% reads falsely low. --max-molecule-size (750 bp in 1.1.x) governs single-ligation chimera rescue; --max-inter-align-gap (20 bp) sets when a coverage gap becomes a null alignment.

Library QC: the Decision This Skill Owns

pairtools stats is the canonical readout. Read it as a funnel, not a single number.

bash
pairtools stats --bytile-dups -o sample.stats.tsv sample.valid.pairs.gz
# Key fields: frac_dups; frac_cis; cis_1kb+/cis_20kb+; trans; pair_types; dist_freq orientation FF/FR/RF/RR.
  • % long-range cis (cis>=1kb, often cis>=20kb) = signal quality. trans = noise floor (genome-size dependent).
  • Orientation vs distance = fragment-map-free dangling-end/self-circle QC. Above ~1kb the four orientations FF/FR/RF/RR each converge to ~25% (random, the positive QC signal). A short-range FR (inward) spike = dangling ends / undigested / self-ligation; a short-range RF (outward) spike = self-circles / religation. The distance where orientations equalize is the minimum reliable contact distance - derive the min-distance cut from this plot, do not hardcode 1kb (Micro-C structure lives below 1kb).
  • % duplicates = complexity proxy, but --bytile-dups separates OPTICAL dups (patterned NovaSeq flowcells, same tile, adjacent coordinates) from PCR dups. Only the PCR fraction reflects library complexity; reading total dup% as over-amplification wrongly condemns a good library. A bare dup% without the depth it was measured at is meaningless - use the complexity/yield curve (preseq lc_extrap) to decide whether deeper sequencing buys uniques or duplicates.

Apply the QC-derived distance cut without a fragment map:

bash
pairtools select '(chrom1!=chrom2) or (abs(pos2-pos1) > 1000)' \   # keep trans + cis beyond the orientation-equalization distance
    -o sample.filtered.pairs.gz sample.valid.pairs.gz

Restriction Fragments: Opt-In, Not Default

Modern pipelines SKIP fragment filtering on purpose - the distance cut + dedup + UU/UC filter + balancing absorb the residual, and a digest file is one genome-specific place to mis-specify the enzyme. pairtools restrict -f frags.bed is opt-in for: sub-kb / restriction-fragment-resolution maps, capture-Hi-C / 4C-style fragment analysis, and bench QC where the dangling-end fraction is the digestion-efficiency readout.

bash
cooler digest --out frags.bed chrom.sizes ref.fa DpnII     # single-enzyme: DpnII ^GATC
pairtools restrict -f frags.bed -o restricted.pairs.gz parsed.pairs.gz

Arima dual-enzyme has FOUR junction motifs (GATCGATC, GANTGATC, GANTANTC, GATCANTC); a single-enzyme (DpnII-only) digest file silently mis-assigns fragments. Micro-C / DNase Hi-C have NO fragment map (MNase/DNase cut sequence-nonspecifically) - any tool requiring a restriction file cannot process them, which is exactly why the restriction-agnostic pairtools path became the field default.

Allele-Specific Contacts: pairtools phase -> Two Coolers

Goal: Resolve each contact to maternal vs paternal haplotype for allele-specific 3D folding.

Approach: Align to a diploid reference reporting suboptimal hits, so each read carries its best alignment on both homologs; pairtools phase reads the gap between the two best alignment scores to tag each side resolved-hap1 / resolved-hap2 / non-resolved / multi-mapper - the score gap is what separates a genuinely uninformative read from an actual repeat.

bash
bcftools consensus -H 1 -f ref.fa phased.vcf.gz > hap1.fa   # build a diploid (two-homolog) reference
bcftools consensus -H 2 -f ref.fa phased.vcf.gz > hap2.fa
bwa mem -SP5M ref_diploid.fa R1.fq R2.fq | \                # report suboptimal hits so both homologs are kept
pairtools parse -c chrom.sizes --add-columns XB,AS,XS | \
pairtools phase --phase-suffixes _hap1 _hap2 --tag-mode XB | \
pairtools sort | pairtools dedup -o phased.pairs.gz
# Then split into hap1/hap2/trans pairs and cload each into a SEPARATE cooler.

Per-Method Failure Modes

Aligned Hi-C as a normal PE library

Trigger: plain bwa mem without -SP, or proper-pair logic. Mechanism: mate rescue forces the shotgun insert model on mates from different loci. Symptom: trans% collapses, compartments vanish, sparse map. Fix: bwa mem -SP5M, mates aligned independently.

Show full SKILL.md (797 more words)Show less
Dropped -5

Trigger: copying a pre-2016 -SP command lacking -5. Mechanism: the 5'-most chimeric segment is not primary, so pairtools picks an inconsistent anchor. Symptom: degraded flip/dedup, smeared loops. Fix: always -SP5M (or -SP5).

walks-policy 5unique on a multi-way protocol

Trigger: Pore-C/MC-3C/Micro-C walks parsed with the default. Mechanism: 5unique reports only the two 5'-most alignments, collapsing concatemers to pairwise. Symptom: "we found few multi-contacts." Fix: --walks-policy all or parse2 --expand.

Mixing parse and parse2 outputs

Trigger: combining a parse2 (.pairs, default outer/junction-anchored) file with a parse (5'-anchored) file. Mechanism: the two report positions by different conventions. Symptom: coordinates shift by the alignment length; dedup under-collapses; loops smear. Fix: one parser/convention per project; prefer plain parse if walks are not needed.

Selecting only UU

Trigger: select pair_type=="UU". Mechanism: discards rescued chimeric (UC) pairs. Symptom: lower valid-pair yield, especially on long reads. Fix: keep (pair_type=="UU") or (pair_type=="UC").

Dedup on a non-canonical file

Trigger: dedup run before sort/flip, or on mixed parse/parse2 positions. Mechanism: duplicates are not in canonical coordinates. Symptom: dup% reads falsely low - library looks better than it is. Fix: sort (flips to 5'-canonical) before dedup.

Optical dups read as PCR dups

Trigger: total dup% on a patterned flowcell taken as library complexity. Mechanism: optical (same-tile) dups inflate apparent PCR rate. Symptom: a good library condemned as over-amplified. Fix: --bytile-dups / --output-bytile-stats; judge complexity on the PCR fraction only.

Fixed 1kb cut on Micro-C

Trigger: applying Hi-C's >1kb min-distance cut to Micro-C. Mechanism: Micro-C's nucleosome-ladder signal lives below 1kb. Symptom: the structure Micro-C exists to capture is erased. Fix: derive the cut from the orientation-vs-distance plot per library.

Quantitative Thresholds

ThresholdSourceRationale
cis>=1kb ~50-65% of nodup pairs (good in-situ human)Dovetail/Arima QC guidance (~approx)long-range cis is the signal; library- and genome-size dependent
inter-chromosomal (trans) <10% (clean), 20-30% acceptablein-situ Hi-C practicetrans is the spurious-ligation floor; NEVER apply to small genomes
FF/FR/RF/RR -> ~25% each above ~1kbrandom strand combination at true contactsconvergence is the fragment-map-free positive QC signal
parse --min-mapq 1 default, raise to 30 for stringencypairtools default1 drops only MAPQ-0; 30 removes repeat-driven false anchors
dedup --max-mismatch 3 bppairtools defaulttolerates mapping wobble; 0 over-splits, larger over-collapses complexity
parse --max-molecule-size 750 bp (1.1.x)pairtools defaultbound on single-ligation chimera rescue; revisit for unusual size selection
min-distance cut ~1kb (Hi-C), derive from orientation plotorientation-equalization distancethe cut is protocol-specific; Micro-C signal is sub-1kb

Common Errors

Error / symptomCauseSolution
trans% high, no compartmentsaligned without -SP (proper-pair logic)re-align bwa mem -SP5M
Few multi-way contacts on Pore-C/Micro-Cdefault --walks-policy 5unique collapsed walks--walks-policy all / parse2 --expand
Loops smeared, dedup under-collapsesmixed parse/parse2 position conventionsone parser per project; sort before dedup
Valid-pair yield lower than expectedselect kept only UUkeep UU and UC
dup% suspiciously lowdedup ran before sort/flipsort to 5'-canonical first
dup% high on NovaSeq, complexity looks badoptical dups counted as PCR--bytile-dups; judge on PCR fraction
Micro-C structure disappears after filteringfixed 1kb min-distance cutderive cut from orientation-vs-distance
Fragment assignment wrong on Arima datasingle-enzyme digest fileencode all four Arima junction motifs
phase resolves nothingaligned to a haploid referencediploid ref + suboptimal (-XA) alignments

References

  • Open2C, Abdennur N, Fudenberg G, Flyamer IM, Galitsyna AA, Goloborodko A, Imakaev M, Venev SV. 2024. Pairtools: from sequencing data to chromosome contacts. PLoS Comput Biol 20(5):e1012164.
  • Li H. 2013. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv:1303.3997.
  • Zhang H, Song L, Wang X, et al. 2021. Fast alignment and preprocessing of chromatin profiles with Chromap. Nat Commun 12:6566.
  • Durand NC, Shamim MS, Machol I, et al. 2016. Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Syst 3:95-98.
  • Servant N, Varoquaux N, Lajoie BR, et al. 2015. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol 16:259.
  • Akgol Oksuz B, Yang L, Abraham S, et al. 2021. Systematic evaluation of chromosome conformation capture assays. Nat Methods 18:1046-1055.
  • Krietenstein N, Abraham S, Venev SV, et al. 2020. Ultrastructural details of mammalian chromosome architecture (Micro-C). Mol Cell 78:554-565.
  • Ramani V, Cusanovich DA, Hause RJ, et al. 2016. Mapping 3D genome architecture through in situ DNase Hi-C. Nat Protoc 11:2104-2121.
  • Abdennur N, Mirny LA. 2020. Cooler: scalable storage for Hi-C data and other genomically labeled arrays. Bioinformatics 36:311-316.
  • Daley T, Smith AD. 2013. Predicting the molecular complexity of sequencing libraries (preseq). Nat Methods 10:325-327.
  • hic-data-io - Bins the deduplicated valid pairs into a .cool/.mcool matrix
  • matrix-operations - Balancing and O/E that the binned pairs feed into
  • hic-visualization - Render contact maps from the resulting cooler
  • read-alignment/bwa-alignment - Aligner upstream; this skill adds the Hi-C -SP5M idiom
  • alignment-files/duplicate-handling - General duplicate-marking context for the pairtools dedup step
  • genome-intervals/bed-file-basics - Coordinate/digest BED handling for restriction fragments and anchors
  • genome-assembly/scaffolding - Same Hi-C reads used to order contigs into chromosomes

© 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 hi-c-analysis/contact-pairs of GPTomics/bioSkills.

  • SKILL.md
  • examples/fastq_to_pairs.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

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    GPTomics/bioSkills

    Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam.

    1.2k GitHub starsUsed in 2 repos~2.4k tokens
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Questions about Bio Hi C Analysis Contact Pairs

What does Bio Hi C Analysis Contact Pairs do?

Turns Hi-C/Micro-C FASTQ into a deduplicated, filtered .pairs file with pairtools and decides whether the library worked. Bio Hi C Analysis Contact Pairs is an agent skill from GPTomics/bioSkills.pairs file with pairtools and decides whether the library worked.

When should I use Bio Hi C Analysis Contact Pairs?

Bio Hi C Analysis Contact Pairs fits situations like: processing Hi-C/Micro-C/Omni-C reads into pairs; judging library quality; handling multi-enzyme; restriction-agnostic protocols.

How do I install Bio Hi C Analysis Contact Pairs in Claude Code?

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

How do I install Bio Hi C Analysis Contact Pairs in Codex?

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

Can I use Bio Hi C Analysis Contact Pairs 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-hi-c-analysis-contact-pairs -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-hi-c-analysis-contact-pairs, .gemini/skills/bio-hi-c-analysis-contact-pairs, .github/skills/bio-hi-c-analysis-contact-pairs and .opencode/skills/bio-hi-c-analysis-contact-pairs in your project.

What does Bio Hi C Analysis Contact Pairs need to run?

Going by SKILL.md and its folder, Bio Hi C Analysis Contact Pairs needs a shell for the scripts in its folder. Our summary lists: A Bash shell.

Does Bio Hi C Analysis Contact Pairs 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 Hi C Analysis Contact Pairs 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 Hi C Analysis Contact Pairs use?

Bio Hi C Analysis Contact Pairs 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 Hi C Analysis Contact Pairs use?

About 4.7k tokens (SKILL.md is roughly 19k 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 Hi C Analysis Contact Pairs?

Skills that share tags, products or a category with Bio Hi C Analysis Contact Pairs: TimesFM Forecasting (google-research/timesfm, 34k stars), Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars), Timesfm Forecasting (zLanqing/codex-claude-academic-skills, 4.7k stars) and Find Hypertable Candidates (timescale/pg-aiguide, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bio Hi C Analysis Contact Pairs?

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.