Agent skill

Bio Methylation Bismark Alignment

by GPTomics in GPTomics/bioSkills

Aligns bisulfite-converted (WGBS, RRBS, PBAT) and enzymatic (EM-seq) short reads to an in-silico C-T/G-A-converted reference with Bismark (Bowtie2 or HISAT2), preparing the genome index, choosing…

MITAuto-check passedResearch & Science

Install Bio Methylation Bismark Alignment

skills CLI
$ npx skills add GPTomics/bioSkills --skill bio-methylation-bismark-alignment -a claude-code

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

GitHub CLI
$ gh skill install GPTomics/bioSkills bio-methylation-bismark-alignment --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/methylation-analysis/bismark-alignment .claude/skills/bio-methylation-bismark-alignment && 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-methylation-bismark-alignment
GitHub stars
1.2k
Used in
1 other repo
Token cost
~4.8k tokens
SKILL.md length
2,113 words
Files
3
Skills in repo
559
Repo updated
First seen
Licence
MIT

At a glance

Aligns bisulfite-converted (WGBS, RRBS, PBAT) and enzymatic (EM-seq) short reads to an in-silico C-T/G-A-converted reference with Bismark (Bowtie2 or HISAT2), preparing the genome index, choosing…

  • Works in 2 steps: Conversion went to completion in BOTH… → The read mapped to the right place…
  • Aligning bisulfite
  • SKILL.md covers Version Compatibility, The Single Most Important…, Why 3-Letter Mapping Is Hard… and The Four Strands and the…, plus 12 more sections
  • Runs Shell scripts from its folder

What it does

Bio Methylation Bismark Alignment is an agent skill from GPTomics/bioSkills. Aligns bisulfite-converted (WGBS, RRBS, PBAT) and enzymatic (EM-seq) short reads to an in-silico C-T/G-A-converted reference with Bismark (Bowtie2 or HISAT2), preparing the genome index, choosing the directional vs non-directional vs PBAT strand flag, deduplicating WGBS/EM-seq (never RRBS), and bounding bisulfite conversion efficiency with unmethylated lambda and methylated pUC19 spike-ins. Covers why the library protocol (not the aligner) decides whether calls are meaningful, why incomplete conversion…

Its SKILL.md is about 4.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `examples/bismark_basic.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

  • Aligning bisulfite
  • Preparing a bisulfite genome
  • Choosing the strand flag
  • Diagnosing low mapping efficiency

Example prompts

  • “Use the bio-methylation-bismark-alignment skill to align bisulfite-converted (WGBS, RRBS, PBAT) and enzymatic (EM-seq) short reads to an in-silico…”
  • “/bio-methylation-bismark-alignment”

Requirements

  • A Bash shell

Workflow steps

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

  1. Conversion went to completion in BOTH directions. An unmethylated C that escapes deamination survives as C and is called methylated ->…
  2. The read mapped to the right place despite throwing its cytosines away. The 3-letter alphabet collapses uniqueness, so a wrong…

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 Methylation Bismark Alignment loads about 4.8k tokens when it runs. Until then it costs about 238 tokens; SKILL.md has 2,113 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~238
When it runs · the whole SKILL.md, loaded when a task matches
~4.8k

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). 2,113 words, ~4,844 tokens.

Download SKILL.mdSave it as .claude/skills/bio-methylation-bismark-alignment/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
bio-methylation-bismark-alignment
description
Aligns bisulfite-converted (WGBS, RRBS, PBAT) and enzymatic (EM-seq) short reads to an in-silico C->T/G->A-converted reference with Bismark (Bowtie2 or HISAT2), preparing the genome index, choosing the directional vs non-directional vs PBAT strand flag, deduplicating WGBS/EM-seq (never RRBS), and bounding bisulfite conversion efficiency with unmethylated lambda and methylated pUC19 spike-ins. Covers why the library protocol (not the aligner) decides whether calls are meaningful, why incomplete conversion masquerades as methylation, the 3-letter reduced-complexity mapping bias (50-70% efficiency is normal), and M-bias end-clipping. Use when aligning bisulfite or EM-seq reads, preparing a bisulfite genome, choosing the strand flag, or diagnosing low mapping efficiency. For methylation extraction see methylation-calling; for long-read MM/ML modification calling see long-read-sequencing/nanopore-methylation.
tool_type
cli
primary_tool
Bismark

Version Compatibility

Reference examples tested with: Bismark 0.24+, Bowtie2 2.5+, HISAT2 2.2+, Trim Galore 0.6.10+, samtools 1.19+.

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

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

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

The genome build and the aligner backend ARE the versions that matter. The bisulfite index is built once per genome FASTA with a specific backend (--bowtie2 vs --hisat2); the index must match the backend used at alignment time, and the FASTA build (hg38 vs T2T-CHM13) fixes every downstream coordinate. EM-seq uses the identical aligners and flags as bisulfite - only the upstream chemistry and the coverage/efficiency expectations change.

Bismark Alignment

"Align my bisulfite sequencing reads" -> Confirm the library type to pick the strand flag, trim the chemistry-specific artifacts, then map the C->T-converted reads to a C->T/G->A-converted reference - because the protocol and conversion, not the aligner, decide whether the calls mean anything.

  • CLI: bismark_genome_preparation --bowtie2 genome/ then bismark --genome genome/ -1 R1.fq.gz -2 R2.fq.gz -o out/

Scope: short-read bisulfite (WGBS/RRBS/PBAT) and enzymatic (EM-seq) alignment, the genome index, the strand/library flag, deduplication, and conversion QC. Methylation extraction from the BAM (XM tag, MethylDackel, cytosine reports) -> methylation-calling. Per-CpG/DMR statistics -> differential-cpg-testing, dmr-detection. Long-read native MM/ML modification calling -> long-read-sequencing/nanopore-methylation. Adapter trimming mechanics -> read-qc/adapter-trimming.

The Single Most Important Modern Insight -- Methylation Is Never Sequenced; the Survivors of a Deamination Assay Are

A bisulfite (or EM-seq) run never reads methylation. It reads which cytosines SURVIVED deamination, against a 3-letter genome deliberately depleted of cytosines, as a C-vs-T choice. Every methylation call is two stacked conditional bets, and both fail silently:

  1. Conversion went to completion in BOTH directions. An unmethylated C that escapes deamination survives as C and is called methylated -> false HYPER-methylation (under-conversion, the dominant fear). A genuinely methylated C deaminated anyway reads T -> false HYPO-methylation (over-conversion). Neither error is visible in the BAM or the mapping rate - only spike-in controls see them, and one control sees only one direction (lambda for under, pUC19 for over).
  2. The read mapped to the right place despite throwing its cytosines away. The 3-letter alphabet collapses uniqueness, so a wrong library-type flag (PBAT or non-directional run as directional) silently drops half to nearly all reads, and a C/T SNP masquerades as an unmethylated CpG with no alignment penalty.

Organize the work around defending these two bets - chemistry control (both directions) and library/strand correctness - not around listing bismark flags. The aligner reports a clean, sorted, indexed BAM whether conversion failed or half the reads went unmapped.

Why 3-Letter Mapping Is Hard (and Why 50-70% Is Normal)

After conversion, unmethylated Cs become Ts, so the read/genome alphabet collapses toward {A,G,T}. A normal aligner would penalize every C->T as a mismatch, so bisulfite aligners convert all Cs to T in BOTH the reads AND the reference, map in the reduced alphabet, then recover methylation by comparing the original read to the original reference. Bismark builds two converted indices (C->T for OT/CTOT, G->A for OB/CTOB) and aligns each read against both. Reduced complexity means more multi-mapping and a lower mapping efficiency (~50-70% for WGBS vs >95% for ordinary DNA) - this is expected, not a bug. The same collapse means a sample CpG->TpG variant aligns with no extra mismatch and is scored as an unmethylated CpG: methylation at a C/T-polymorphic site is a hypothesis until SNP-aware (Bis-SNP, BISCUIT).

The Four Strands and the Library-Type Flag

Bisulfite PCR generates four strand species: OT (original top), OB (original bottom), CTOT (complement of OT), CTOB (complement of OB). The library protocol decides which exist, and the flag must match or reads vanish silently:

LibraryStrands sequencedBismark flagDedup?Trim Galore special-case
WGBS (directional)OT, OB(default)YESM-bias end-clip
EM-seq (directional)OT, OB(default)YESM-bias end-clip (gentler)
RRBSOT, OB(default)NO--rrbs (MspI fill-in)
PBAT / scBS-seqCTOT, CTOB--pbatusually NOaggressive 5' clip (random priming)
non-directionalall four--non_directionalYESM-bias end-clip (Trim Galore --non_directional is RRBS-only, needs --rrbs)

PBAT does bisulfite conversion FIRST then tags by random priming, so its reads originate from CTOT/CTOB - the OPPOSITE of directional. PBAT needs --pbat for strand reasons; it is unrelated to RRBS. A non-directional library run as directional silently loses ~half its reads; PBAT run as directional maps near zero.

Tool Taxonomy

ToolCitationStrategyWhen
BismarkKrueger & Andrews 2011 Bioinformatics 27:15713-letter, Bowtie2/HISAT2 backendde-facto standard; self-contained (index + align + dedup + extractor); teach this
bwa-methPedersen 2014 arXiv:1401.11293-letter, BWA-MEMlean clinical/cfDNA; handles indels/clipping; pairs with MethylDackel for calling
BISCUITZhou 2024 Nucleic Acids Res 52:e323-letter, BWA-derivedwhen SNPs / allele-specific methylation are needed alongside (joint genetic+epigenetic)
gemBSMerkel 2019 Bioinformatics 35:7373-letter, GEM3population-scale; the ENCODE WGBS pipeline mapper
abismal / methylpyde Sena Brandine & Smith 2021 NAR Genom Bioinform 3:lqab1152-letter (purine/pyrimidine)memory-constrained, large cohorts

All produce a BAM whose methylation is recovered by a SEPARATE caller (Bismark extractor, MethylDackel, or the tool's own). Alignment and calling are two steps.

Decision Tree by Scenario

ScenarioRecommendedWhy
Standard WGBS or EM-seq, mammalianBismark default (directional) + dedupOT/OB only; the common case
RRBStrim_galore --rrbs then Bismark default, NO dedupMspI fixed ends look like (but are not) PCR duplicates
PBAT / scBS-seqbismark --pbatreads come from CTOT/CTOB, not OT/OB
Non-directional librarybismark --non_directionalall four strands present; default loses half
Precious low-input (cfDNA / FFPE / single-cell)prefer EM-seq or TAPS upstreambisulfite degrades 84-96% of input; same aligners apply
Need SNPs / allele-specific methylation-> bwa-meth + Bis-SNP, or BISCUITC/T SNPs masquerade as methylation in 3-letter space
Large mammalian genome, low RAMbismark --hisat2 (index must match)HISAT2 backend is lighter than Bowtie2
Extract per-CpG methylation from the BAM-> methylation-callingthis skill stops at the deduplicated, M-bias-clipped BAM
Long-read ONT/PacBio modBAM (MM/ML tags)-> long-read-sequencing/nanopore-methylationnative modification calling, not bisulfite

Prepare the Genome Index

Goal: Build the bisulfite-converted index once per genome, with the backend that alignment will use.

Approach: Place the reference FASTA(s) in a folder, run bismark_genome_preparation with the chosen backend; it writes Bisulfite_Genome/ containing the C->T and G->A converted indices.

bash
bismark_genome_preparation --bowtie2 genome/   # or --hisat2 for large genomes, lower RAM
# genome/ holds the FASTA (e.g. hg38.fa); writes genome/Bisulfite_Genome/{CT_conversion,GA_conversion}
# The backend chosen here MUST match the bismark alignment backend below.

Trim First, with the Chemistry-Specific Flag

Goal: Remove adapters and the library-specific end artifacts before alignment so they do not become spurious methylation calls.

Approach: Run Trim Galore (Cutadapt wrapper). Add --rrbs for RRBS (clips the MspI end-repair fill-in), --non_directional for non-directional, or extra 5' clipping for PBAT. Bismark itself does not trim. Mechanics live in read-qc/adapter-trimming.

bash
trim_galore --paired R1.fq.gz R2.fq.gz                 # WGBS / EM-seq (auto-detect adapter, -q 20)
trim_galore --rrbs --paired R1.fq.gz R2.fq.gz          # RRBS: extra 2 bp off 3' R1 (+ 5' R2) = MspI fill-in
trim_galore --clip_r2 6 --paired R1.fq.gz R2.fq.gz     # PBAT/scBS: random-priming bias at 5' (amount from M-bias)

Align

bash
bismark --genome genome/ -1 R1_val_1.fq.gz -2 R2_val_2.fq.gz \
    --bowtie2 \         # must match the index backend; --hisat2 if prepared that way
    --parallel 4 \      # instances PER direction; total threads scale up several-fold per instance
    -o out/             # writes *_bismark_bt2_pe.bam + *_PE_report.txt (mapping efficiency, %meth per context)
# Add --pbat for PBAT/scBS, or --non_directional for non-directional libraries (NOT both).

Deduplicate (WGBS/EM-seq Only)

Goal: Remove PCR duplicates from random-fragmentation libraries, while leaving RRBS untouched.

Approach: deduplicate_bismark removes reads sharing mapping coordinate + strand. Run it on the by-name (unsorted) Bismark BAM, before extraction. For RRBS, SKIP it: every fragment starts at an MspI cut site, so identical coordinates are biologically distinct molecules, not PCR copies (apparent duplication ~90-95% is real data).

bash
deduplicate_bismark --paired --bam out/sample_R1_bismark_bt2_pe.bam   # WGBS/EM-seq ONLY
# RRBS: do NOT run this. UMI-tagged RRBS can dedup by UMI+coordinate; optical dups can still be removed.
samtools sort out/sample_R1_bismark_bt2_pe.deduplicated.bam -o out/sample.sorted.bam   # IGV/downstream
samtools index out/sample.sorted.bam

Conversion QC: Both Directions, and the Spike-In Is an Optimistic Floor

Goal: Bound both conversion error directions before believing any methylation level.

Approach: Spike unmethylated lambda phage (measures under-conversion -> false hyper) AND CpG-methylated pUC19 (measures over-conversion -> false hypo). Align each spike-in genome separately and read off context methylation. With no spike-in, sample CHH methylation is a weak fallback (somatic tissue only; confounded in ESCs/neurons/plants).

bash
bismark_genome_preparation --bowtie2 lambda/   # lambda: residual %meth = non-conversion rate (target <=1%)
bismark --genome lambda/ -1 R1.fq.gz -2 R2.fq.gz -o lambda_qc/
# pUC19 (CpG-methylated): fraction of CpGs called UNmethylated = over-conversion (expect ~96-98% methylated)

Spike-ins are naked, fully accessible DNA that denature completely, so their conversion is an OPTIMISTIC upper bound. Real genomic conversion is region-dependent: GC-rich CpG islands and structured regions denature less, under-convert more, and inflate apparent methylation exactly where the biology is. Treat the spike-in number as a floor; a rising per-GC-bin CHH rate flags local under-conversion.

Per-Method Failure Modes

Show full SKILL.md (856 more words)Show less
PBAT or non-directional run with the default flag

Trigger: running PBAT/scBS or a non-directional library without --pbat/--non_directional. Mechanism: PBAT reads come from CTOT/CTOB and non-directional from all four strands, but the default tries only OT/OB. Symptom: near-zero (PBAT) or ~halved (non-directional) mapping efficiency on a clean-looking run. Fix: confirm the kit/protocol directionality, pass the matching flag; never reach for -N 1 first.

Incomplete conversion read as methylation

Trigger: no conversion control, or only a lambda (under-conversion) control. Mechanism: an unmethylated C surviving deamination is indistinguishable from real 5mC. Symptom: globally elevated methylation, worst in GC-rich CpG islands. Fix: report BOTH a lambda non-conversion rate (<=1%) and a pUC19 over-conversion rate; add per-GC CHH as an internal check.

RRBS deduplicated by coordinate

Trigger: running deduplicate_bismark on RRBS. Mechanism: MspI cuts give every fragment a fixed start, so distinct molecules share coordinates. Symptom: ~90-95% of reads discarded, coverage decimated. Fix: skip coordinate dedup for RRBS; use UMIs if dedup is required.

MspI fill-in not trimmed

Trigger: RRBS aligned without trim_galore --rrbs. Mechanism: end-repair fills MspI overhangs with unmethylated dCTP, creating artificial cytosines at fragment ends. Symptom: artificial hypomethylation clustered at MspI sites. Fix: trim_galore --rrbs; Bismark aligns RRBS fine but does NOT fix this trimming artifact.

M-bias not clipped before calling

Trigger: calling methylation off raw read ends. Mechanism: end-repair fills 5' overhangs with unmethylated dCTP, worst at the start of R2. Symptom: an M-bias plot (methylation vs read position) shows a dip/spike at the ends instead of a flat line. Fix: read the M-bias plot, clip the affected ends; extraction --ignore/--clip mechanics live in methylation-calling.

Index/backend mismatch

Trigger: index prepared with --bowtie2, alignment run with --hisat2 (or vice versa). Mechanism: the two backends use incompatible converted indices. Symptom: Bismark errors or fails to find the index. Fix: prepare and align with the same backend.

Quantitative Thresholds

ThresholdSourceRationale
Lambda non-conversion <=1%manufacturer spec; field standardresidual apparent methylation on unmethylated spike-in = false-positive floor (EM-seq v2 ~<=0.5%)
pUC19 ~96-98% methylatedmanufacturer specbounds over-conversion -> false hypo; lambda alone cannot see this direction
WGBS mapping efficiency ~50-70%Krueger & Andrews 2011; 3-letter complexityreduced alphabet costs uniqueness; below this, diagnose (library flag > trimming > reference > biology)
EM-seq mapping efficiency typically higherVaisvila 2021no chemical fragmentation -> flatter coverage; WGBS expectations are too pessimistic
Bisulfite degrades 84-96% of inputGrunau 2001 Nucleic Acids Res 29:e65only ~4-16% of molecules survive intact; the reason low-input fails and EM-seq/TAPS exist
-N = 0 (seed mismatches)Bismark manualdefault; -N 1 raises sensitivity AND mis-mapping - last resort, not the low-mapping fix
--rrbs clips 2 bpTrim Galore guidethe MspI end-repair fill-in length; confirm on the installed version

Common Errors

Error / symptomCauseSolution
Near-zero mapping efficiencyPBAT run as directionaladd --pbat
~Half the reads unmappednon-directional run as directionaladd --non_directional
RRBS loses ~90% of readsdeduplicated by coordinateskip deduplicate_bismark for RRBS
Globally high methylationincomplete conversion (no/one-sided control)lambda + pUC19 spike-ins; check per-GC CHH
Artificial hypomethylation at MspI sites--rrbs trimming omittedtrim_galore --rrbs
FastQC per-base content / GC FAILexpected for converted libraries (C depleted)not a defect; do not "fix" a healthy bisulfite library
0% sites at C/T variantsC/T SNP read as unmethylated CpGSNP-aware calling (Bis-SNP/BISCUIT) or mask known C/T SNPs
Bismark cannot find the indexbackend mismatch with genome prepre-prep or align with the matching --bowtie2/--hisat2
Output named "5mC"standard BS and EM-seq report 5mC+5hmC summedlabel the sum; oxBS/TAB pairing is needed to separate (see methylation-calling)

References

  • Krueger F, Andrews SR. 2011. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 27:1571-1572.
  • Vaisvila R, Ponnaluri VKC, Sun Z, et al. 2021. Enzymatic methyl sequencing detects DNA methylation at single-base resolution from picograms of DNA. Genome Res 31:1280-1289.
  • Meissner A, Gnirke A, Bell GW, et al. 2005. Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res 33:5868-5877.
  • Miura F, Enomoto Y, Dairiki R, Ito T. 2012. Amplification-free whole-genome bisulfite sequencing by post-bisulfite adaptor tagging. Nucleic Acids Res 40:e136.
  • Hansen KD, Langmead B, Irizarry RA. 2012. BSmooth: from whole genome bisulfite sequencing reads to differentially methylated regions. Genome Biol 13:R83.
  • Grunau C, Clark SJ, Rosenthal A. 2001. Bisulfite genomic sequencing: systematic investigation of critical experimental parameters. Nucleic Acids Res 29:e65.
  • Pedersen BS, Eyring K, De S, Yang IV, Schwartz DA. 2014. Fast and accurate alignment of long bisulfite-seq reads. arXiv:1401.1129.
  • Zhou W, Johnson BK, Morrison J, et al. 2024. BISCUIT: an efficient, standards-compliant tool suite for simultaneous genetic and epigenetic inference in bulk and single-cell studies. Nucleic Acids Res 52:e32.
  • Merkel A, Fernandez-Callejo M, Casals E, et al. 2019. gemBS: high throughput processing for DNA methylation data from bisulfite sequencing. Bioinformatics 35:737-742.
  • de Sena Brandine G, Smith AD. 2021. Fast and memory-efficient mapping of short bisulfite sequencing reads using a two-letter alphabet. NAR Genom Bioinform 3:lqab115.
  • methylation-calling - Extract per-CpG methylation from the aligned BAM
  • methylkit-analysis - Downstream import, filtering, normalization
  • read-qc/adapter-trimming - Trim Galore before Bismark (RRBS/PBAT handling)
  • read-qc/quality-reports - FastQC (expect per-base C-depletion FAIL on converted libraries)
  • alignment-files/sam-bam-basics - BAM manipulation after alignment
  • sequence-io/read-sequences - FASTQ handling before alignment
  • long-read-sequencing/nanopore-methylation - Native long-read MM/ML modification calling (out of scope here)
  • workflows/methylation-pipeline - End-to-end bisulfite pipeline

© 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 methylation-analysis/bismark-alignment of GPTomics/bioSkills.

  • SKILL.md
  • examples/bismark_basic.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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    Soft- or hard-clips PCR primer footprints from aligned amplicon BAMs so primer bases stop masquerading as confirmed reference sequence.

    1.2k GitHub starsUsed in 2 repos~2.2k tokens
    Auto-check passed
  • Filters BAM alignments by FLAG bits, mapping quality and regions with samtools view or pysam, with recipes for common keep and drop cases.

    1.2k GitHub starsUsed in 2 repos~3.6k tokens
    Auto-check passed
  • Bio Alignment Indexing

    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
    Auto-check passed

Questions about Bio Methylation Bismark Alignment

What does Bio Methylation Bismark Alignment do?

Aligns bisulfite-converted (WGBS, RRBS, PBAT) and enzymatic (EM-seq) short reads to an in-silico C-T/G-A-converted reference with Bismark (Bowtie2 or HISAT2), preparing the genome index, choosing…. Bio Methylation Bismark Alignment is an agent skill from GPTomics/bioSkills. Aligns bisulfite-converted (WGBS, RRBS, PBAT) and enzymatic (EM-seq) short reads to an in-silico C-T/G-A-converted reference with Bismark (Bowtie2 or HISAT2), preparing the genome index, choosing the directional vs non-directional vs PBAT strand flag, deduplicating WGBS/EM-seq (never RRBS), and bounding bisulfite conversion efficiency with unmethylated lambda and methylated pUC19 spike-ins.

When should I use Bio Methylation Bismark Alignment?

Bio Methylation Bismark Alignment fits situations like: aligning bisulfite; preparing a bisulfite genome; choosing the strand flag; diagnosing low mapping efficiency.

How do I install Bio Methylation Bismark Alignment in Claude Code?

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

How do I install Bio Methylation Bismark Alignment in Codex?

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

Can I use Bio Methylation Bismark Alignment 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-methylation-bismark-alignment -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-methylation-bismark-alignment, .gemini/skills/bio-methylation-bismark-alignment, .github/skills/bio-methylation-bismark-alignment and .opencode/skills/bio-methylation-bismark-alignment in your project.

What does Bio Methylation Bismark Alignment need to run?

Going by SKILL.md and its folder, Bio Methylation Bismark Alignment needs a shell for the scripts in its folder. Our summary lists: A Bash shell.

Does Bio Methylation Bismark Alignment 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 Methylation Bismark Alignment 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 Methylation Bismark Alignment use?

Bio Methylation Bismark Alignment 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 Methylation Bismark Alignment use?

About 4.8k 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 Methylation Bismark Alignment?

Skills that share tags, products or a category with Bio Methylation Bismark Alignment: 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 Methylation Bismark Alignment?

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.