Topic: openclaw
3,425 skills in this topic.
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bio-variant-calling-filtering-best-practices
Comprehensive variant filtering including GATK VQSR, hard filters, bcftools expressions, and quality metric interpretation for SNPs and indels. Use when filtering variants using GATK best practices.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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agent-browser
Browse the web for any task — research topics, read articles, interact with web apps, fill forms, take screenshots, extract data, and test web pages. Use whenever a browser would be useful, not just when the user explicitly asks.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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hmdb-database
Access Human Metabolome Database (220K+ metabolites). Search by name/ID/structure, retrieve chemical properties, biomarker data, NMR/MS spectra, pathways, for metabolomics and identification.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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tooluniverse-crispr-screen-analysis
Comprehensive CRISPR screen analysis for functional genomics. Analyze pooled or arrayed CRISPR screens (knockout, activation, interference) to identify essential genes, synthetic lethal interactions, and drug targets. Perform sgRNA count processing, gene-level scoring (MAGeCK, BAGEL), quality control, pathway enrichment, and drug target prioritization. Use for CRISPR screen analysis, gene essentiality studies, synthetic lethality detection, functional genomics, drug target validation, or identifying genetic vulnerabilities.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-workflows-tcr-pipeline
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-clinical-databases-somatic-signatures
Extract and analyze mutational signatures from somatic variants using SigProfiler or MutationalPatterns to characterize mutagenic processes. Use when identifying DNA damage mechanisms or etiology in cancer genomes.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-primer-design-qpcr-primers
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-single-cell-metabolite-communication
Analyze metabolite-mediated cell-cell communication using MeboCost for metabolic signaling inference between cell types. Predict metabolite secretion and sensing patterns from scRNA-seq data. Use when studying metabolic crosstalk between cell populations or metabolite-receptor interactions.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-metabolomics-xcms-preprocessing
XCMS3 workflow for LC-MS/MS metabolomics preprocessing. Covers peak detection, retention time alignment, correspondence (grouping), and gap filling. Use when processing raw LC-MS data into a feature table for untargeted metabolomics.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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exosome-ev-analysis-agent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-entrez-search
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-population-genetics-linkage-disequilibrium
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-comparative-genomics-hgt-detection
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-expression-matrix-gene-id-mapping
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-genome-assembly-assembly-polishing
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-workflows-metagenomics-pipeline
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-single-cell-doublet-detection
Detect and remove doublets (multiple cells captured in one droplet) from single-cell RNA-seq data. Uses Scrublet (Python), DoubletFinder (R), and scDblFinder (R). Essential QC step before clustering to avoid artificial cell populations. Use when identifying and removing doublets from scRNA-seq data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-chipseq-differential-binding
Differential binding analysis using DiffBind. Compare ChIP-seq peaks between conditions with statistical rigor. Requires replicate samples. Outputs differentially bound regions with fold changes and p-values. Use when comparing ChIP-seq binding between conditions.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-atac-seq-atac-qc
Quality control metrics for ATAC-seq data including fragment size distribution, TSS enrichment, FRiP, and library complexity. Use when assessing ATAC-seq library quality before or after peak calling to identify problematic samples.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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biomni-general-agent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-spatial-transcriptomics-spatial-statistics
Compute spatial statistics for spatial transcriptomics data using Squidpy. Calculate Moran's I, Geary's C, spatial autocorrelation, co-occurrence analysis, and neighborhood enrichment. Use when computing spatial autocorrelation or co-occurrence statistics.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-data-visualization-heatmaps-clustering
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-genome-engineering-base-editing-design
Design guides for cytosine and adenine base editing using editing window optimization and BE-Hive outcome prediction. Select optimal positions for C-to-T or A-to-G conversions without double-strand breaks. Use when designing base editor experiments for precise nucleotide changes.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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cellular-senescence-agent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009