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Topic: clawhub

924 skills in this topic.

bio-genome-intervals-proximity-operations
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-hi-c-analysis-matrix-operations 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.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-imaging-mass-cytometry-cell-segmentation 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.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-imaging-mass-cytometry-spatial-analysis Spatial analysis of cell neighborhoods and interactions in IMC data. Covers neighbor graphs, spatial statistics, and interaction testing. Use when analyzing spatial relationships between cell types, testing for neighborhood enrichment, or identifying cell-cell interaction patterns in imaging mass cytometry data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-liquid-biopsy-pipeline
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-long-read-sequencing-isoseq-analysis Analyze PacBio Iso-Seq data for full-length isoform discovery and quantification. Use when characterizing transcript diversity or identifying novel splice variants.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-longread-medaka 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.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-longread-qc 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.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-metabolomics-msdial-preprocessing 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.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-metabolomics-pathway-mapping Map metabolites to biological pathways using KEGG, Reactome, and MetaboAnalyst. Perform pathway enrichment and topology analysis. Use when interpreting metabolomics results in the context of biochemical pathways.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-metagenomics-strain-tracking 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.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-methylation-based-detection 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.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-motif-search
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-paired-end-fastq Handle paired-end FASTQ files (R1/R2) using Biopython. Use when working with Illumina paired reads, synchronizing pairs, interleaving/deinterleaving, or filtering paired data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-phasing-imputation-genotype-imputation
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-population-genetics-selection-statistics
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-proteomics-differential-abundance Statistical testing for differentially abundant proteins between conditions. Covers limma and MSstats workflows with multiple testing correction. Use when identifying proteins with significant abundance changes between experimental groups.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-proteomics-proteomics-qc Quality control and assessment for proteomics data. Use when evaluating proteomics data quality before downstream analysis. Covers sample metrics, missing value patterns, replicate correlation, batch effects, and intensity distributions.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-proteomics-quantification Protein quantification from mass spectrometry data including label-free (LFQ, intensity-based), isobaric labeling (TMT, iTRAQ), and metabolic labeling (SILAC) approaches. Use when extracting protein abundances from MS data for differential analysis.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-read-alignment-bwa-alignment
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-reporting-automated-qc-reports
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-restriction-enzyme-selection
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-restriction-sites
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-ribo-seq-riboseq-preprocessing Preprocess ribosome profiling data including adapter trimming, size selection, rRNA removal, and alignment. Use when preparing Ribo-seq reads for downstream analysis of translation.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009