Agent skill

Bio Clinical Databases Msi Detection

by GPTomics in GPTomics/bioSkills

Calls microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro, MSIsensor-ct (panel-aware), mSINGS, and MANTIS for FDA pembrolizumab MSI-H pan-tumor / Lynch syndrome /…

MITAuto-check passedResearch & Science

Install Bio Clinical Databases Msi Detection

skills CLI
$ npx skills add GPTomics/bioSkills --skill bio-clinical-databases-msi-detection -a claude-code

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

GitHub CLI
$ gh skill install GPTomics/bioSkills bio-clinical-databases-msi-detection --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/clinical-databases/msi-detection .claude/skills/bio-clinical-databases-msi-detection && 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-clinical-databases-msi-detection
GitHub stars
1.2k
Used in
2 other repos
Token cost
~5k tokens
SKILL.md length
1,805 words
Files
3
Skills in repo
559
Repo updated
First seen
Licence
MIT

At a glance

Calls microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro, MSIsensor-ct (panel-aware), mSINGS, and MANTIS for FDA pembrolizumab MSI-H pan-tumor / Lynch syndrome /…

  • Stratifying ICI eligibility (Le 2015)
  • SKILL.md covers Version Compatibility, The Regulatory and Trial…, MSI vs dMMR vs TMB-H: The… and Tool Taxonomy, plus 13 more sections
  • Runs Shell scripts from its folder; calls pip
  • Pairing MSI with TMB-H (Sha 2020 / Salem 2018)

What it does

Bio Clinical Databases Msi Detection is an agent skill from GPTomics/bioSkills. Calls microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro, MSIsensor-ct (panel-aware), mSINGS, and MANTIS for FDA pembrolizumab MSI-H pan-tumor / Lynch syndrome / dMMR ICI biomarker. Use when stratifying ICI eligibility (Le 2015), pairing MSI with TMB-H (Sha 2020 / Salem 2018), screening Lynch syndrome (universal IHC + MSI), or distinguishing MSI-H tumors from POLE-exo hypermutator with overlapping signatures.

Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `examples/msi_detection.sh` and `usage-guide.md`).

It sits in Research & Science. 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

  • Stratifying ICI eligibility (Le 2015)
  • Pairing MSI with TMB-H (Sha 2020 / Salem 2018)
  • Screening Lynch syndrome (universal IHC + MSI)
  • Distinguishing MSI-H tumors from POLE-exo hypermutator with overlapping signatures

Example prompts

  • “Use the bio-clinical-databases-msi-detection skill to call microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro…”
  • “/bio-clinical-databases-msi-detection”

Requirements

  • Python 3
  • A Bash shell

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.

    Shell commands in SKILL.md call:

    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    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 Clinical Databases Msi Detection loads about 5k tokens when it runs. Until then it costs about 121 tokens; SKILL.md has 1,805 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~121
When it runs · the whole SKILL.md, loaded when a task matches
~5k

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). 1,805 words, ~4,958 tokens.

Download SKILL.mdSave it as .claude/skills/bio-clinical-databases-msi-detection/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
bio-clinical-databases-msi-detection
description
Calls microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro, MSIsensor-ct (panel-aware), mSINGS, and MANTIS for FDA pembrolizumab MSI-H pan-tumor / Lynch syndrome / dMMR ICI biomarker. Use when stratifying ICI eligibility (Le 2015), pairing MSI with TMB-H (Sha 2020 / Salem 2018), screening Lynch syndrome (universal IHC + MSI), or distinguishing MSI-H tumors from POLE-exo hypermutator with overlapping signatures.
tool_type
cli
primary_tool
MSIsensor-pro

Version Compatibility

Reference examples tested with: MSIsensor-pro 1.2+, MSIsensor 0.6+, MANTIS 1.0.5+, samtools 1.19+, mSINGS 5.6+, pandas 2.2+, cyvcf2 0.30+. FDA pembrolizumab MSI-H / dMMR pan-tumor approval is from 2017 (Le 2015 NEJM; KEYNOTE-016/164/158); approval extended to colorectal first-line in 2020.

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

  • Python: pip show <package> then help(module.function) to check signatures
  • CLI: <tool> --version

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. MSIsensor-pro replaces MSIsensor for tumor-only assays; MSIsensor-ct is the bTMB-equivalent for ctDNA panels.

MSI Detection; The Companion ICI Biomarker to TMB

'Detect MSI status from this somatic sequencing data' -> Profile microsatellite instability across canonical loci (Bethesda 5 panel + extended NGS-derived sites); classify MSI-H / MSS / MSI-L per Bethesda / FDA / KEYNOTE convention.

  • CLI (recommended tumor-only): msisensor-pro msi -d microsatellites.list -t tumor.bam -o msi_out -b 16
  • CLI (paired tumor-normal): msisensor msi -d microsatellites.list -n normal.bam -t tumor.bam -o msi_out
  • CLI (ctDNA / blood MSI): msisensor-ct ...
  • CLI (older WES standard): mantis -t tumor.bam -n normal.bam -b targets.bed --threads 8

The Regulatory and Trial Landscape

EventYearThresholdNotes
Le 2015 NEJM2015MSI-H + ICI in CRCThe seminal paper: pembrolizumab in MSI-H CRC ORR 40% vs 0% MSS
FDA pembrolizumab MSI-H / dMMR pan-tumor2017MSI-HFirst tissue-agnostic FDA approval (KEYNOTE-016/164/158)
FDA pembrolizumab first-line MSI-H CRC2020MSI-H + first-line CRCKEYNOTE-177
CheckMate 1422017-2018MSI-H + nivolumab/ipilimumabPan-tumor MSI-H second-line
ESMO 20242024MSI-HMaintained pan-tumor MSI-H biomarker
Universal Lynch screening--IHC + MSI on all CRC <= 70 yrNCCN / ACG / EGAPP guidelines

MSI vs dMMR vs TMB-H: The Conceptual Hierarchy

TermDefinitionMethodRelationship
dMMR (deficient MMR)Loss of MMR protein functionIHC (MLH1, MSH2, MSH6, PMS2)Causes MSI
MSI-HMicrosatellite instability highPCR-based Bethesda or NGSConsequence of dMMR
Lynch syndromeGermline MMR mutationGermline sequencingCauses ~50% of MSI-H CRC; rest are sporadic (MLH1 hyper-methylation)
TMB-H>= 10 mut/MbNGS panel / WESStatistical correlate of MSI-H
POLE-exo hypermutatorPOLE proofreading defectSequencing / signaturesHypermutator WITHOUT MMR-D; MSI-stable typically

MSI-H + TMB-H overlap (Chalmers 2017 Genome Med 9:34):

  • ~83% of MSI-H tumors are TMB-H.
  • ~16% of TMB-H solid tumors are MSI-H.
  • Sha 2020 Cancer Discov: MSI-H is the more established dMMR biomarker for ICI decisions; TMB-H not additive.

POLE-exo vs MMR-D:

  • POLE-exo (SBS10a/10b): hypermutator (100-300 mut/Mb pure); typically MSI-stable.
  • MMR-D (SBS6/15/26/44 + ID1/2): 30-50 mut/Mb typical; MSI-H.
  • POLE-exo + MMR-D (SBS14 + SBS20): ultra-hypermutator >=500 mut/Mb; MSI-H.

Tool Taxonomy

ToolPairedTumor-onlyctDNAAlgorithmFails when
MSIsensor (Niu 2014 Bioinformatics)YesNoNoBayesian + read-length distributionTumor-only data (no baseline); cohort baseline missing
MSIsensor-pro (Jia 2020 Genom Proteom Bioinform)OptionalYesNoDistribution comparison to baselineBaseline cohort not provided; panel < 50 loci
MSIsensor-ct (Han 2021 Brief Bioinform)----YescfDNA-awareTumor fraction < 3%; low ctDNA shed
MANTIS (Kautto 2017 Oncotarget)YesNoNoStep-wise differenceTumor-only; low coverage at microsatellites
mSINGS (Salipante 2014 Clin Chem)--YesNoBackground panel (unstable-loci fraction)Background panel poorly characterized for cohort

Operational consensus 2024-2026:

  • Tumor + paired normal WES: MSIsensor or MANTIS.
  • Tumor-only assay (commercial panels, often unpaired): MSIsensor-pro with reference baseline.
  • ctDNA / liquid biopsy: MSIsensor-ct.
  • Lynch screening: IHC FIRST (rules out 90%+); MSI-PCR / NGS confirmatory.

Decision Tree by Scenario

ScenarioRecommended pathWhy
Tumor + paired normal WESMSIsensor (standard)Reference paired-normal comparison
Tumor-only WES/panelMSIsensor-pro with panel baselineNo matched normal needed
ctDNA / liquid biopsyMSIsensor-ctcfDNA-aware
Lynch syndrome screeningUniversal IHC + MSI (NCCN)IHC catches 90%+; MSI for IHC-equivocal
FDA pembrolizumab eligibilityValidate per FoCR PCR + IHC + NGS concordanceCross-platform required
MSI-H + TMB-H concurrenceMSI-H is primary biomarkerSha 2020; TMB-H not additive
POLE+MMR ultra-hypermutatorSigprofiler signatures (SBS14, SBS20)Mechanism beyond MSI alone
Sporadic MSI-HConfirm MLH1 hypermethylation; rule out LynchDistinguishes sporadic vs germline
MSI-stable + TMB-HInvestigate POLE-exo signature (SBS10a/10b)POLE-exo causes hypermutator without MSI
Pan-tumor screeningMSI + IHC + TMB combinedMultiple modalities for ICI eligibility

Bethesda Panel and Modern NGS-Derived Loci

The original NCI/Bethesda reference panel (Boland 1998) used BAT-25 and BAT-26 plus three dinucleotide markers (D2S123, D5S346, D17S250); >= 2 of 5 loci unstable -> MSI-H. Modern PCR assays use the mononucleotide pentaplex (the current clinical standard), which replaced the dinucleotide markers for improved cross-population specificity:

  • BAT-25 (chr4)
  • BAT-26 (chr2)
  • NR-21 (chr14)
  • NR-24 (chr2)
  • MONO-27 (chr2)

NGS-based MSI panels use 50-1000+ microsatellite loci. MSI-H requires unstable status at >=40% of tested loci typically (varies by panel calibration).

Standard Workflow: MSIsensor-pro Tumor-Only

Goal: Compute MSI status from tumor-only WES/panel.

Approach: Generate baseline from population reference; compare patient tumor.

bash
# Generate microsatellite list from reference genome (one-time)
msisensor-pro scan -d /reference/GRCh38.fa -o microsatellites.list -p 1 -m 5

# Generate baseline from N normal control samples (one-time per panel)
msisensor-pro baseline -d microsatellites.list -i normal_samples.list -o baseline.list -b 16

# Score tumor sample. The `-i sample_id` flag is uncommon: in typical msisensor-pro
# usage the sample identifier is derived from the BAM file -- verify the flag set
# against `msisensor-pro pro --help` for the installed release.
msisensor-pro pro \
    -d microsatellites.list \
    -t tumor.bam \
    -o msi_output \
    -b 16 \
    --baseline baseline.list

# Output: msi_output_all (raw); msi_output_unstable (unstable loci); msi_output.txt (summary)
# Critical column: %_unstable. Threshold MSI-H typically >= 20-30% depending on panel.

Paired Tumor-Normal MSIsensor

bash
msisensor msi \
    -d microsatellites.list \
    -n normal.bam \
    -t tumor.bam \
    -o msi_paired_out \
    -b 16

# Output: %_unstable in paired comparison
# MSI-H threshold: >= 20% by FoCR guidance; varies 10-30% across studies

MANTIS Step-wise Difference

bash
mantis.py \
    -t tumor.bam \
    -n normal.bam \
    -b microsatellite_targets.bed \
    --threads 8 \
    -o mantis_output

# Output: mantis_output.kmer_counts (raw), mantis_output (status)
# Threshold MSI-H: stepwise difference > 0.4 (default)

MSI-H Classification Logic

python
import pandas as pd


def classify_msi(unstable_percentage, panel_calibrated_cutoff=20.0):
    '''Classify MSI status from percentage of unstable loci.

    Bethesda PCR: >=2 of 5 unstable -> MSI-H (40% loci)
    NGS: panel-specific cutoffs typically 10-30%
    Concordance: MSI-PCR + IHC + NGS should agree (FoCR)
    '''
    if unstable_percentage >= panel_calibrated_cutoff:
        return 'MSI-H'
    elif unstable_percentage >= panel_calibrated_cutoff / 2:
        return 'MSI-L (intermediate; treat as MSS clinically per FDA)'
    else:
        return 'MSS'


def msi_lynch_workflow(msi_status, ihc_results, mlh1_methylation_status, germline_test):
    '''Standard Lynch syndrome workflow.

    Args:
        msi_status: 'MSI-H' / 'MSS' / 'MSI-L'
        ihc_results: dict {MLH1: 'retained' or 'loss', MSH2, MSH6, PMS2}
        mlh1_methylation_status: 'methylated' (sporadic) / 'unmethylated' (Lynch suspect)
        germline_test: 'positive' / 'negative' / 'not_performed'
    '''
    if msi_status != 'MSI-H':
        return 'No further Lynch screening indicated'

    ihc_loss = [gene for gene, status in ihc_results.items() if status == 'loss']
    if not ihc_loss:
        return 'MSI-H with retained IHC; consider Lynch with germline testing'

    if 'MLH1' in ihc_loss:
        if mlh1_methylation_status == 'methylated':
            return 'Sporadic MSI-H (MLH1 hypermethylation); not Lynch'
        elif mlh1_methylation_status == 'unmethylated':
            return 'Lynch suspect (MLH1 loss without methylation); proceed with germline testing'
        else:
            return 'MLH1 loss; perform methylation test'

    return f'MSH2/6/PMS2 loss ({", ".join(ihc_loss)}); strong Lynch suspect; germline testing'


def msi_tmb_ici_decision(msi_status, tmb_value, tumor_type=None, dmmr_ihc=None):
    '''Integrated ICI eligibility from MSI + TMB.

    Sha 2020: MSI-H is primary biomarker; TMB-H not additive.
    McGrail 2021: TMB-H NOT endorsed for breast/prostate/glioma alone.
    '''
    msi_high = msi_status == 'MSI-H'
    dmmr_positive = dmmr_ihc == 'positive'
    tmb_h = tmb_value >= 10

    if msi_high or dmmr_positive:
        return ('ICI eligible: MSI-H or dMMR (FDA pembrolizumab 2017 pan-tumor; KEYNOTE-016/164/158); '
                'TMB-H is not additive (Sha 2020).')
    if tmb_h and tumor_type and tumor_type.lower() in ('breast', 'prostate', 'glioma'):
        return ('TMB-H but tumor type excluded by ESMO 2024 / McGrail 2021. '
                'Consider tumor-type-specific cutoff.')
    if tmb_h:
        return 'TMB-H pan-tumor (FDA pembrolizumab 2020); ICI eligible.'
    return 'MSS + TMB-low. Standard chemo per tumor type.'

Per-Operation Failure Modes

1. Tumor-only with paired-normal tool

  • Trigger: Run MSIsensor on tumor-only BAM.
  • Mechanism: MSIsensor requires paired normal for baseline comparison.
  • Symptom: Tool errors or produces unstable noisy result.
  • Fix: Use MSIsensor-pro for tumor-only; or use mSINGS background-panel approach.

2. Panel size too small

  • Trigger: 30-locus panel called MSI-H based on 20% threshold (= 6 unstable loci).
  • Mechanism: Small panel + stochastic unstable rates produce high false-positive rates.
  • Symptom: False-positive MSI-H in WES-comparable panels with < 50 microsatellite loci.
  • Fix: Validate panel calibration with reference cohort; use panel-specific cutoff; minimum 50 informative loci.

3. IHC vs MSI discordance not investigated

  • Trigger: IHC retains all four MMR proteins; MSI-H by sequencing.
  • Mechanism: IHC may miss subtle loss; MSI may include MSH6-only subtype (more variable); rare germline POLE+MMR ultra-hypermutators show MSI.
  • Symptom: Apparent discordance; classification ambiguous.
  • Fix: Cross-check with germline MMR sequencing; check for POLE-exo on Sigprofiler.

4. MSI-H + Lynch syndrome confusion

  • Trigger: Report MSI-H tumor as "Lynch syndrome".
  • Mechanism: ~50% of MSI-H CRC is sporadic (MLH1 hypermethylation, not germline Lynch).
  • Symptom: Incorrect family counseling; wrong screening.
  • Fix: Apply IHC + MLH1 methylation + germline testing workflow.

5. POLE-exo hypermutator labeled MSI

  • Trigger: Tumor with 200 mut/Mb POLE-exo signature labeled MSI-H.
  • Mechanism: Pure POLE-exo causes hypermutator WITHOUT MSI (different repair mechanism); apparent MSI-H call may be a false positive in high-mutation context.
  • Symptom: Misclassification; ICI eligibility still positive but for different mechanism.
  • Fix: Run Sigprofiler signatures (SBS10a/10b vs SBS6/15/26/44); confirm POLE-exo via SBS10 contribution.

6. ctDNA MSI without sufficient tumor fraction

  • Trigger: Run MSIsensor-ct on cfDNA with <1% tumor fraction.
  • Mechanism: Low ctDNA fraction produces noise-dominated unstable locus counts.
  • Symptom: False-negative or unstable MSI call.
  • Fix: Estimate tumor fraction first (ichorCNA); require >= 3% for reliable cfDNA MSI.

7. Universal screening missed

  • Trigger: CRC patient < 70 yr without IHC / MSI.
  • Mechanism: NCCN / ACG universal Lynch screening required; without it, Lynch syndrome undiagnosed.
  • Symptom: Family loses screening benefit.
  • Fix: Universal IHC + MSI on all CRC < 70; institute reflex testing.

8. MSI-L treated as actionable

  • Trigger: Report MSI-L (intermediate) as ICI-eligible.
  • Mechanism: FDA approval specifies MSI-H; MSI-L = MSS clinically.
  • Symptom: ICI given on insufficient indication; reimbursement issues.
  • Fix: Apply MSI-H threshold strictly per FDA; MSI-L = MSS.
Show full SKILL.md (699 more words)Show less

Reconciliation: When Sources Disagree

PatternLikely causeAction
PCR Bethesda MSI-H vs NGS MSSBethesda panel uses 5 loci only; less sensitiveTrust NGS with >=50 informative loci
NGS MSI-H vs IHC retainedSubtle MMR loss; MSH6-only subtype; or POLE-exoConfirm with germline + POLE-exo signature analysis
Paired-normal MSI-H + tumor-only MSSSample swap or low tumor purity in tumor-onlyRe-validate; check purity (>=20% required)
MSIsensor-pro vs MSIsensor (paired)Different baseline thresholdsApply panel-specific calibration
MSI-H suspected but tools differBorderline mutational burdenUse signature analysis (SBS6/15/26/44) as orthogonal evidence
ctDNA MSI vs tissue MSITumor fraction lowTrust tissue; estimate ctDNA fraction

Quantitative Thresholds and Conventions

ThresholdConventionSource
Bethesda MSI-H>= 2/5 unstableBoland 1998
NGS MSI-H cutoff10-30% unstable loci (panel-specific)Various
MANTIS MSI-H thresholdStep-wise difference > 0.4Kautto 2017
MSIsensor MSI-H threshold>= 20% by FoCRFriends of Cancer Research
Minimum informative loci>= 50 NGS lociPanel-design convention
ctDNA tumor fraction minimum>= 3% for reliable cfDNA MSI (depth-dependent operational floor; MSIsensor-ct reports 0.05% LOD only at >= 3000x)Operational convention
Tumor purity minimum>= 20%Standard
FDA approvalMSI-H or dMMR pan-tumor (2017)KEYNOTE-016/164/158
First-line MSI-H CRCKEYNOTE-177 (2020)--
MSI-H -> TMB-H rate~83%Chalmers 2017
TMB-H -> MSI-H rate~16%Chalmers 2017
Sporadic MSI-H mechanism~50% MLH1 hypermethylationVarious
Universal screening cutoffCRC <= 70 yrNCCN / ACG

Common Errors

SymptomCauseSolution
MSI-H + IHC retained discordanceSubtle loss; MSH6-only; or rare hypermutatorCross-check germline + signatures
Borderline MSI callPanel too smallUse >= 50 informative loci
Tumor-only MSI low confidenceBackground subtraction neededUse MSIsensor-pro with cohort baseline
MSI-H + TMB-H reported additiveTautology per Sha 2020MSI-H is primary; TMB-H not additive
POLE-exo labeled MMR-DDifferent mechanism; mutation count differsRun Sigprofiler; SBS10a/10b is POLE-exo
Sporadic MSI-H mis-labeled LynchNeed MLH1 methylation testConfirm MLH1 methylation + germline

Anticipated Reviewer Pushback

PushbackStandard response
"MSI-H + TMB-H both reported additive"Sha 2020 Cancer Discov: MSI-H is the primary biomarker; TMB-H is statistical correlate. We report MSI-H first; TMB-H reported but noted not additive.
"Why MSIsensor-pro instead of MSIsensor?"MSIsensor requires paired normal; MSIsensor-pro handles tumor-only via cohort baseline. Most commercial panels are tumor-only.
"MSI-PCR vs NGS discordant"Bethesda 5-locus panel is less sensitive; we use NGS >=50 informative loci for confirmation.
"Universal Lynch screening?"NCCN / ACG recommend reflex IHC + MSI on all CRC <= 70 yr; we implemented universal screening protocol.
"POLE-exo hypermutator with MSI-H?"Sigprofiler signature analysis distinguishes: SBS10a/10b = POLE-exo (typically MSI-stable); SBS6/15/26/44 = MMR-D. POLE+MMR concurrent produces ultra-hypermutator.
"MSI-L?"FDA approval specifies MSI-H; MSI-L = clinically MSS; we apply MSI-H threshold strictly.
"ctDNA MSI viability?"MSIsensor-ct works if tumor fraction >= 3%; we estimate via ichorCNA; below threshold falls back to tissue.

References

  • Le DT et al. 2015. PD-1 blockade in tumors with mismatch-repair deficiency. NEJM 372:2509. (The seminal paper)
  • Marabelle A et al. 2020. Efficacy of pembrolizumab in patients with noncolorectal high MSI/dMMR cancer. J Clin Oncol 38:1.
  • Niu B et al. 2014. MSIsensor: microsatellite instability detection using paired tumor-normal sequence data. Bioinformatics 30:1015.
  • Jia P et al. 2020. MSIsensor-pro: fast, accurate, and matched-normal-sample-free detection of microsatellite instability. Genomics Proteomics Bioinformatics 18:65.
  • Han X et al. 2021. MSIsensor-ct: microsatellite instability detection using cfDNA sequencing data. Brief Bioinform 22:bbaa402.
  • Kautto EA et al. 2017. Performance evaluation for rapid detection of pan-cancer microsatellite instability with MANTIS. Oncotarget 8:7452.
  • Salipante SJ et al. 2014. Microsatellite instability detection by NGS. Clin Chem 60:1192.
  • Boland CR et al. 1998. National Cancer Institute workshop on microsatellite instability for cancer detection and familial predisposition. Cancer Res 58:5248.
  • Salem ME et al. 2018. Landscape of tumor mutation load, mismatch repair deficiency, and PD-L1 expression in a large patient cohort of gastrointestinal cancers. Mol Cancer Res 16:805.
  • Chalmers ZR et al. 2017. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med 9:34.
  • Sha D et al. 2020. Tumor mutational burden as a predictive biomarker in solid tumors. Cancer Discov 10:1808.
  • Vanderwalde A et al. 2018. Microsatellite instability status determined by next-generation sequencing and compared with PD-L1 and tumor mutational burden in 11,348 patients. Cancer Med 7:746.
  • clinical-databases/tumor-mutational-burden - TMB as related ICI biomarker
  • clinical-databases/somatic-signatures - SBS6/15/26/44 MMR-D signatures + SBS10a/10b POLE-exo
  • clinical-databases/clinvar-lookup - Lynch syndrome variant pathogenicity (MLH1, MSH2, MSH6, PMS2)
  • clinical-databases/variant-prioritization - Germline MMR variant prioritization for Lynch
  • variant-calling/clinical-interpretation - Clinical reporting

© 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 clinical-databases/msi-detection of GPTomics/bioSkills.

  • SKILL.md
  • examples/msi_detection.sh
  • usage-guide.md

Open the folder on GitHubat commit d91ed3d

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in GPTomics/bioSkills, which our catalogue first saw on October 7, 2026.

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Questions about Bio Clinical Databases Msi Detection

What does Bio Clinical Databases Msi Detection do?

Calls microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro, MSIsensor-ct (panel-aware), mSINGS, and MANTIS for FDA pembrolizumab MSI-H pan-tumor / Lynch syndrome /…. Bio Clinical Databases Msi Detection is an agent skill from GPTomics/bioSkills. Calls microsatellite instability from WES/WGS/targeted-panel with MSIsensor, MSIsensor-pro, MSIsensor-ct (panel-aware), mSINGS, and MANTIS for FDA pembrolizumab MSI-H pan-tumor / Lynch syndrome / dMMR ICI biomarker.

When should I use Bio Clinical Databases Msi Detection?

Bio Clinical Databases Msi Detection fits situations like: stratifying ICI eligibility (Le 2015); pairing MSI with TMB-H (Sha 2020 / Salem 2018); screening Lynch syndrome (universal IHC + MSI); distinguishing MSI-H tumors from POLE-exo hypermutator with overlapping signatures.

How do I install Bio Clinical Databases Msi Detection in Claude Code?

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

How do I install Bio Clinical Databases Msi Detection in Codex?

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

Can I use Bio Clinical Databases Msi Detection 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-clinical-databases-msi-detection -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-clinical-databases-msi-detection, .gemini/skills/bio-clinical-databases-msi-detection, .github/skills/bio-clinical-databases-msi-detection and .opencode/skills/bio-clinical-databases-msi-detection in your project.

What does Bio Clinical Databases Msi Detection need to run?

Going by SKILL.md and its folder, Bio Clinical Databases Msi Detection needs a shell for the scripts in its folder and the command-line tools its instructions call (pip). Our summary lists: Python 3; A Bash shell.

Does Bio Clinical Databases Msi Detection access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Bio Clinical Databases Msi Detection 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 Clinical Databases Msi Detection use?

Bio Clinical Databases Msi Detection 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 Clinical Databases Msi Detection use?

About 5k tokens (SKILL.md is roughly 20k 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 Clinical Databases Msi Detection?

Skills that share tags, products or a category with Bio Clinical Databases Msi Detection: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 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 Clinical Databases Msi Detection?

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.