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Topic: skills

17,247 skills in this topic.

bio-spatial-transcriptomics-spatial-visualization Visualize spatial transcriptomics data using Squidpy and Scanpy. Create tissue plots with gene expression, clusters, and annotations overlaid on histology images. Use when visualizing spatial expression patterns.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-de-visualization Visualize differential expression results using DESeq2/edgeR built-in functions. Covers plotMA, plotDispEsts, plotCounts, plotBCV, sample distance heatmaps, and p-value histograms. Use when visualizing differential expression results.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-experimental-design-sample-size
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-sequence-statistics Calculate sequence statistics (N50, length distribution, GC content, summary reports) using Biopython. Use when analyzing sequence datasets, generating QC reports, or comparing assemblies.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-microbiome-qiime2-workflow QIIME2 command-line workflow for 16S/ITS amplicon analysis. Alternative to DADA2/phyloseq R workflow with built-in provenance tracking. Use when preferring CLI over R, needing reproducible provenance, or working within QIIME2 ecosystem.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-reporting-rmarkdown-reports
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-batch-processing Process multiple sequence files in batch using Biopython. Use when working with many files, merging/splitting sequences, or automating file operations across directories.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-data-visualization-multipanel-figures
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
anndata This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-atac-seq-differential-accessibility Find differentially accessible chromatin regions between conditions using DiffBind or DESeq2. Use when comparing chromatin accessibility between treatment groups, cell types, or developmental stages in ATAC-seq experiments.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-reference-operations
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-pathway-gsea Gene Set Enrichment Analysis using clusterProfiler gseGO and gseKEGG. Use when analyzing ranked gene lists to find coordinated expression changes in gene sets without arbitrary significance cutoffs. Detects subtle but coordinated expression changes.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-rna-quantification-tximport-workflow
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-data-visualization-specialized-omics-plots
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-format-conversion Convert between sequence file formats (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO. Use when changing file formats or preparing data for different tools.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-rna-quantification-featurecounts-counting
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-small-rna-seq-mirdeep2-analysis
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-clinical-databases-gnomad-frequencies Query gnomAD for population allele frequencies to assess variant rarity. Use when filtering variants by population frequency for rare disease analysis or determining if a variant is common in the general population.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-hi-c-analysis-compartment-analysis Detect A/B compartments from Hi-C data using cooltools and eigenvector decomposition. Identify active (A) and inactive (B) chromatin compartments from contact matrices. Use when identifying A/B compartments from Hi-C data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-single-cell-cell-communication Infer cell-cell communication networks from scRNA-seq data using CellChat, NicheNet, and LIANA for ligand-receptor interaction analysis. Use when inferring ligand-receptor interactions between cell types.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-read-alignment-bowtie2-alignment
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-splicing-qc Assesses RNA-seq data quality for splicing analysis including junction saturation curves, splice site strength scoring, and junction coverage metrics using RSeQC. Use when evaluating data suitability for splicing analysis or troubleshooting low event detection.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-chipseq-peak-annotation Annotate ChIP-seq peaks to genomic features and genes using ChIPseeker. Assign peaks to promoters, exons, introns, and intergenic regions. Find nearest genes and calculate distance to TSS. Generate annotation plots and statistics. Use when annotating ChIP-seq peaks to genomic features.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-proteomics-data-import Load and parse mass spectrometry data formats including mzML, mzXML, and quantification tool outputs like MaxQuant proteinGroups.txt. Use when starting a proteomics analysis with raw or processed MS data. Handles contaminant filtering and missing value assessment.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009