Polish assemblies and call variants from Oxford Nanopore data using medaka. Uses neural networks trained on specific basecaller versions. Use when improving ONT-only assemblies or calling variants from Nanopore data without short-read polishing.
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FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Track bacterial strains using MASH, sourmash, fastANI, and inStrain. Compare genomes, detect contamination, and monitor strain-level variation. Use when needing sub-species resolution for outbreak tracking, transmission analysis, or within-host strain dynamics.
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FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Call topologically associating domains (TADs) from Hi-C data using insulation score, HiCExplorer, and other methods. Identify domain boundaries and hierarchical domain structure. Use when calling TADs from Hi-C insulation scores.
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FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Visualize metagenomic profiles using R (phyloseq, microbiome) and Python (matplotlib, seaborn). Create stacked bar plots, heatmaps, PCA plots, and diversity analyses. Use when creating publication-quality figures from MetaPhlAn, Bracken, or other taxonomic profiling output.
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FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Quality control for long-read sequencing data using NanoPlot, NanoStat, and chopper. Generate QC reports, filter reads by length and quality, and visualize read characteristics. Use when assessing ONT or PacBio run quality or filtering reads before assembly or alignment.
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FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Analyzes isoform switching events and functional consequences using IsoformSwitchAnalyzeR. Predicts protein domain changes, NMD sensitivity, ORF alterations, and coding potential shifts between conditions. Use when investigating how splicing changes affect protein function.
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FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Amplicon sequence variant (ASV) inference from 16S rRNA or ITS amplicon sequencing using DADA2. Covers quality filtering, error learning, denoising, and chimera removal. Use when processing demultiplexed amplicon FASTQ files to generate an ASV table for downstream analysis.
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FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Differential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of microbiome data.
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FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Profile functional potential of metagenomes using HUMAnN3 and similar tools. Use when obtaining pathway abundances, gene family counts, or functional annotations from metagenomic data.
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FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Specialized lipidomics analysis for lipid identification, quantification, and pathway interpretation. Covers LC-MS lipidomics with LipidSearch, MS-DIAL, and LipidMaps annotation. Use when analyzing lipid classes, chain composition, or lipid-specific pathways.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Analyzes cfDNA methylation patterns for cancer detection using cfMeDIP-seq or bisulfite sequencing with MethylDackel. Identifies cancer-specific methylation signatures and performs tissue-of-origin deconvolution. Use when using methylation biomarkers for early cancer detection or minimal residual disease.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
MS-DIAL-based metabolomics preprocessing as alternative to XCMS. Covers peak detection, alignment, annotation, and export for downstream analysis. Use when processing MS-DIAL output files for R/Python analysis or when preferring GUI-based preprocessing.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identifying contiguous genomic regions with methylation differences between experimental conditions or cell types.
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FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Deep learning-based variant calling from long reads using Clair3 for SNPs and small indels. Use when calling germline variants from ONT or PacBio alignments, particularly when high accuracy is needed for clinical or research applications.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Predict TCR-epitope specificity using ERGO-II and deep learning models for T-cell receptor antigen recognition. Match TCRs to their cognate epitopes or predict TCR targets. Use when analyzing TCR repertoire specificity or identifying antigen-reactive T-cells.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Bisulfite sequencing read alignment using Bismark with bowtie2/hisat2. Handles genome preparation and produces BAM files with methylation information. Use when aligning WGBS, RRBS, or other bisulfite-converted sequencing reads to a reference genome.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Tracks ctDNA dynamics over time for treatment response monitoring using serial liquid biopsy samples. Analyzes tumor fraction trends, mutation clearance kinetics, and defines molecular response criteria. Use when monitoring patients during therapy or detecting molecular relapse before clinical progression.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
DNA methylation analysis with methylKit in R. Import Bismark coverage files, filter by coverage, normalize samples, and perform statistical comparisons. Use when analyzing single-base methylation patterns, comparing samples, or preparing data for DMR detection.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Balance, normalize, and transform Hi-C contact matrices using cooler and cooltools. Apply iterative correction (ICE), compute expected values, and generate observed/expected matrices. Use when normalizing or transforming Hi-C matrices.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Score and prioritize neoantigens and epitopes for immunogenicity using multi-factor models combining MHC binding, processing, expression, and sequence features. Rank candidates for vaccine design. Use when prioritizing epitopes for vaccine development or identifying the most immunogenic neoantigens.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Predict metagenome functional content from 16S rRNA marker gene data using PICRUSt2. Infer KEGG, MetaCyc, and EC abundances from ASV tables. Use when functional profiling is needed from 16S data without shotgun metagenomics sequencing.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Cell segmentation from multiplexed tissue images. Covers deep learning (Cellpose, Mesmer) and classical approaches for nuclear and whole-cell segmentation. Use when extracting single-cell data from IMC or MIBI images after preprocessing.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Calls DNA methylation from Oxford Nanopore sequencing data using signal-level analysis. Use when detecting 5mC or 6mA modifications directly from nanopore reads without bisulfite conversion.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026
Compare Hi-C contact matrices between conditions to identify differential chromatin interactions. Compute log2 fold changes, statistical significance, and visualize differential contact maps. Use when comparing Hi-C contacts between conditions.
The English summary is being prepared. Showing the original description.
FreedomIntelligence/OpenClaw-Medical-Skills☆ 3.1KUpdated Jul 21, 2026