Skill "bio-codon-usage" from FreedomIntelligence/OpenClaw-Medical-Skills, covering copyright notice, copyright (c) 2026 md babu mia, phd, all rights reserved, this code is proprietary and confidential and provenance: authenticated by md babu mia.
Skill "bio-comparative-genomics-ancestral-reconstruction" from FreedomIntelligence/OpenClaw-Medical-Skills, covering copyright notice, copyright (c) 2026 md babu mia, phd, all rights reserved, this code is proprietary and confidential and provenance: authenticated by md babu mia.
Skill "bio-comparative-genomics-hgt-detection" from FreedomIntelligence/OpenClaw-Medical-Skills, covering copyright notice, copyright (c) 2026 md babu mia, phd, all rights reserved, this code is proprietary and confidential and provenance: authenticated by md babu mia.
Skill "bio-comparative-genomics-ortholog-inference" from FreedomIntelligence/OpenClaw-Medical-Skills, covering copyright notice, copyright (c) 2026 md babu mia, phd, all rights reserved, this code is proprietary and confidential and provenance: authenticated by md babu mia.
Skill "bio-comparative-genomics-positive-selection" from FreedomIntelligence/OpenClaw-Medical-Skills, covering copyright notice, copyright (c) 2026 md babu mia, phd, all rights reserved, this code is proprietary and confidential and provenance: authenticated by md babu mia.
Skill "bio-comparative-genomics-synteny-analysis" from FreedomIntelligence/OpenClaw-Medical-Skills, covering copyright notice, copyright (c) 2026 md babu mia, phd, all rights reserved, this code is proprietary and confidential and provenance: authenticated by md babu mia.
Read and write compressed sequence files (gzip, bzip2, BGZF) using Biopython. Use when working with .gz or .bz2 sequence files. Use BGZF for indexable compressed files.
Generate consensus FASTA sequences by applying VCF variants to a reference using bcftools consensus. Use when creating sample-specific reference sequences or reconstructing haplotypes.
Annotate CNVs with genes, pathways, and clinical significance. Use when interpreting CNV calls or identifying affected genes from copy number analysis.
Visualize copy number profiles, segments, and compare across samples. Create publication-quality plots of CNV data from CNVkit, GATK, or other callers. Use when creating genome-wide CNV plots, sample heatmaps, or chromosome-level visualizations.
Detect copy number variants from targeted/exome sequencing using CNVkit. Supports tumor-normal pairs, tumor-only, and germline CNV calling. Use when detecting CNVs from WES or targeted panel sequencing data.
Call copy number variants using GATK best practices workflow. Supports both somatic (tumor-normal) and germline CNV detection from WGS or WES data. Use when following GATK best practices or integrating CNV calling with other GATK variant pipelines.
Analyzes base editing and prime editing outcomes including editing efficiency, bystander edits, and indel frequencies. Use when quantifying CRISPR base editor results, comparing ABE vs CBE efficiency, or assessing prime editing fidelity.
Batch effect correction for CRISPR screens. Covers normalization across batches, technical replicate handling, and batch-aware analysis. Use when combining screens from multiple batches or correcting systematic technical variation.
CRISPResso2 for analyzing CRISPR gene editing outcomes. Quantifies indels, HDR efficiency, and generates comprehensive editing reports. Use when analyzing amplicon sequencing data from CRISPR editing experiments to assess editing efficiency.
Statistical methods for calling hits in CRISPR screens. Covers MAGeCK, BAGEL2, drugZ, and custom approaches for identifying essential and resistance genes. Use when identifying significant genes from screen count data after QC passes.
JACKS (Joint Analysis of CRISPR/Cas9 Knockout Screens) for modeling sgRNA efficacy and gene essentiality. Use when analyzing multiple CRISPR screens simultaneously or when accounting for variable sgRNA efficiency across experiments.
CRISPR library design for genetic screens. Covers sgRNA selection, library composition, control design, and oligo ordering. Use when designing custom sgRNA libraries for knockout, activation, or interference screens.
MAGeCK (Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout) for pooled CRISPR screen analysis. Covers count normalization, gene ranking, and pathway analysis. Use when identifying essential genes, drug targets, or resistance mechanisms from dropout or enrichment screens.
Quality control for pooled CRISPR screens. Covers library representation, read distribution, replicate correlation, and essential gene recovery. Use when assessing screen quality before hit calling or diagnosing poor screen performance.
Detects somatic mutations in circulating tumor DNA using variant callers optimized for low allele fractions with UMI-based error suppression. Reliably detects mutations at VAF above 0.5 percent using consensus-based approaches. Use when identifying tumor mutations from plasma DNA or tracking specific variants.
Skill "bio-data-visualization-circos-plots" from FreedomIntelligence/OpenClaw-Medical-Skills, covering copyright notice, copyright (c) 2026 md babu mia, phd, all rights reserved, this code is proprietary and confidential and provenance: authenticated by md babu mia.
Skill "bio-data-visualization-color-palettes" from FreedomIntelligence/OpenClaw-Medical-Skills, covering copyright notice, copyright (c) 2026 md babu mia, phd, all rights reserved, this code is proprietary and confidential and provenance: authenticated by md babu mia.
Skill "bio-data-visualization-genome-browser-tracks" from FreedomIntelligence/OpenClaw-Medical-Skills, covering copyright notice, copyright (c) 2026 md babu mia, phd, all rights reserved, this code is proprietary and confidential and provenance: authenticated by md babu mia.
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At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: