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Claude Skills by David-Li0406
github.com/David-Li04065,064 skills17 installs250 views
- Bio Hi C Analysis Matrix OperationsBalance, 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.Votes: 0GitHub stars: 2
- Bio Hi C Analysis Tad DetectionCall 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.Votes: 0GitHub stars: 2
- Bio Imaging Mass Cytometry Cell SegmentationCell 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.Votes: 0GitHub stars: 2
- Bio Imaging Mass Cytometry Data PreprocessingLoad and preprocess imaging mass cytometry (IMC) and MIBI data. Covers MCD/TIFF handling, hot pixel removal, and image normalization. Use when starting IMC analysis from raw MCD files or preparing images for segmentation.Votes: 0GitHub stars: 2
- Bio Imaging Mass Cytometry Interactive AnnotationInteractive cell type annotation for IMC data. Covers napari-based annotation, marker-guided labeling, training data generation, and annotation validation. Use when manually annotating cell types for training classifiers or validating automated phenotyping results.Votes: 0GitHub stars: 2
- Bio Imaging Mass Cytometry PhenotypingCell type assignment from marker expression in IMC data. Covers manual gating, clustering, and automated classification approaches. Use when assigning cell types to segmented IMC cells based on protein marker expression or when phenotyping cells in multiplexed imaging data.Votes: 0GitHub stars: 2
- Bio Imaging Mass Cytometry Quality MetricsQuality metrics for IMC data including signal-to-noise, channel correlation, tissue integrity, and acquisition QC. Use when assessing data quality before analysis or troubleshooting problematic acquisitions.Votes: 0GitHub stars: 2
- Bio Imaging Mass Cytometry Spatial AnalysisSpatial 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.Votes: 0GitHub stars: 2
- Bio Local BlastRun local BLAST searches using BLAST+ command-line tools. Use when running fast unlimited searches, building custom databases, performing large-scale analysis, or when NCBI servers are slow or unavailable.Votes: 0GitHub stars: 2
- Bio Long Read Sequencing Isoseq AnalysisAnalyze PacBio Iso-Seq data for full-length isoform discovery and quantification. Use when characterizing transcript diversity or identifying novel splice variants.Votes: 0GitHub stars: 2
- Bio Longread AlignmentAlign long reads using minimap2 for Oxford Nanopore and PacBio data. Supports various presets for different read types and applications. Use when aligning ONT or PacBio reads to a reference genome for variant calling, SV detection, or coverage analysis.Votes: 0GitHub stars: 2
- Bio Longread MedakaPolish 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.Votes: 0GitHub stars: 2
- Bio Metabolomics LipidomicsSpecialized 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.Votes: 0GitHub stars: 2
- Bio Metabolomics Metabolite AnnotationMetabolite identification from m/z and retention time. Covers database matching, MS/MS spectral matching, and confidence level assignment. Use when assigning compound identities to detected features in untargeted metabolomics.Votes: 0GitHub stars: 2
- Bio Metabolomics Msdial PreprocessingMS-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.Votes: 0GitHub stars: 2
- Bio Metabolomics Statistical AnalysisStatistical analysis for metabolomics data. Covers univariate testing, multivariate methods (PCA, PLS-DA), and biomarker discovery. Use when identifying differentially abundant metabolites or building classification models.Votes: 0GitHub stars: 2
- Bio Metabolomics Targeted AnalysisTargeted metabolomics analysis using MRM/SRM with standard curves. Covers absolute quantification, method validation, and quality assessment. Use when quantifying specific metabolites using calibration curves and internal standards.Votes: 0GitHub stars: 2
- Bio Metabolomics Xcms PreprocessingXCMS3 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.Votes: 0GitHub stars: 2
- Bio Metagenomics Strain TrackingTrack 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.Votes: 0GitHub stars: 2
- Bio Methylation Bismark AlignmentBisulfite 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.Votes: 0GitHub stars: 2
- Bio Methylation Dmr DetectionDifferentially 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.Votes: 0GitHub stars: 2
- Bio Methylation MethylkitDNA 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.Votes: 0GitHub stars: 2
- Bio Microbiome Differential AbundanceDifferential 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.Votes: 0GitHub stars: 2
- Bio Microbiome Functional PredictionPredict 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.Votes: 0GitHub stars: 2
- Bio Microbiome Qiime2 WorkflowQIIME2 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.Votes: 0GitHub stars: 2
- Bio Microbiome Taxonomy AssignmentTaxonomic classification of ASVs using reference databases like SILVA, GTDB, or UNITE. Covers naive Bayes classifiers (DADA2, IDTAXA) and exact matching approaches. Use when assigning taxonomy to ASVs after DADA2 amplicon processing.Votes: 0GitHub stars: 2
- Bio Motif SearchFind patterns, motifs, and subsequences in biological sequences using Biopython. Use when searching for transcription factor binding sites, regulatory elements, or any sequence pattern. For restriction enzyme analysis, use the restriction-analysis skill.Votes: 0GitHub stars: 2
- Bio Multi Omics Data HarmonizationPreprocessing and harmonization of multi-omics data before integration. Covers normalization, batch correction, feature alignment, and missing value handling across data types. Use when preparing multi-omics datasets for integration analysis.Votes: 0GitHub stars: 2
- Bio Multi Omics Mixomics AnalysisSupervised and unsupervised multi-omics integration with mixOmics. Includes sPLS for pairwise integration and DIABLO for multi-block discriminant analysis. Use when performing supervised multi-omics integration or identifying features that discriminate between groups.Votes: 0GitHub stars: 2
- Bio Multi Omics Mofa IntegrationMulti-Omics Factor Analysis (MOFA2) for unsupervised integration of multiple data modalities. Identifies shared and view-specific sources of variation. Use when integrating RNA-seq, proteomics, methylation, or other omics to discover latent factors driving biological variation across modalities.Votes: 0GitHub stars: 2
- Bio Multi Omics Similarity NetworkSimilarity Network Fusion (SNF) for patient stratification using multi-omics data. Integrates multiple data types into a unified patient similarity network. Use when performing patient stratification or integrating multi-omics data into unified similarity networks.Votes: 0GitHub stars: 2
- Bio Paired End FastqHandle paired-end FASTQ files (R1/R2) using Biopython. Use when working with Illumina paired reads, synchronizing pairs, interleaving/deinterleaving, or filtering paired data.Votes: 0GitHub stars: 2
- Bio Pdb Geometric AnalysisPerform geometric calculations on protein structures using Biopython Bio.PDB. Use when measuring distances, angles, and dihedrals, superimposing structures, calculating RMSD, or computing solvent accessible surface area (SASA).Votes: 0GitHub stars: 2
- Bio Pdb Structure IoParse and write protein structure files using Biopython Bio.PDB. Use when reading PDB, mmCIF, and MMTF files, downloading structures from RCSB PDB, or writing structures to various formats.Votes: 0GitHub stars: 2
- Bio Pdb Structure ModificationModify protein structures using Biopython Bio.PDB. Use when transforming coordinates, removing atoms or residues, adding new entities, modifying B-factors and occupancies, or building structures programmatically.Votes: 0GitHub stars: 2
- Bio Pdb Structure NavigationNavigate protein structure hierarchy using Biopython Bio.PDB SMCRA model. Use when accessing models, chains, residues, and atoms, iterating over structure levels, or extracting sequences from PDB files.Votes: 0GitHub stars: 2
- Bio Phylo Distance CalculationsCompute evolutionary distances and build phylogenetic trees using Biopython Bio.Phylo.TreeConstruction. Use when creating distance matrices from alignments, building NJ/UPGMA trees, or generating bootstrap consensus trees.Votes: 0GitHub stars: 2
- Bio Phylo Modern Tree InferenceBuild maximum likelihood phylogenetic trees using IQ-TREE2 and RAxML-ng. Use when inferring publication-quality trees with model selection, ultrafast bootstrap, or partitioned analyses from sequence alignments.Votes: 0GitHub stars: 2
- Bio Phylo Tree IoRead, write, and convert phylogenetic tree files using Biopython Bio.Phylo. Use when parsing Newick, Nexus, PhyloXML, or NeXML tree formats, converting between formats, or handling multiple trees.Votes: 0GitHub stars: 2
- Bio Phylo Tree ManipulationModify phylogenetic tree structure using Biopython Bio.Phylo. Use when rooting trees with outgroups or midpoint, pruning taxa, collapsing clades, ladderizing branches, or extracting subtrees.Votes: 0GitHub stars: 2
- Bio Phylo Tree VisualizationDraw and export phylogenetic trees using Biopython Bio.Phylo with matplotlib. Use when creating publication-quality tree figures, customizing colors and labels, or exporting to image formats.Votes: 0GitHub stars: 2
- Bio Pileup GenerationGenerate pileup data for variant calling using samtools mpileup and pysam. Use when preparing data for variant calling, analyzing per-position read data, or calculating allele frequencies.Votes: 0GitHub stars: 2
- Bio Population Genetics Plink BasicsPLINK file formats, format conversion, and quality control filtering for population genetics. Convert between VCF, BED/BIM/FAM, and PED/MAP formats, apply MAF, genotyping rate, and HWE filters using PLINK 1.9 and 2.0. Use when working with PLINK format files or running QC.Votes: 0GitHub stars: 2
- Bio Population Genetics Scikit Allel AnalysisPython population genetics with scikit-allel. Read VCF files, compute allele frequencies, calculate diversity statistics, perform PCA, and run selection scans using GenotypeArray and HaplotypeArray data structures. Use when analyzing population genetics in Python.Votes: 0GitHub stars: 2
- Bio Primer Design Primer BasicsDesign PCR primers for a target sequence using primer3-py. Specify target regions, product size, melting temperature, and other constraints. Returns ranked primer pairs with quality metrics. Use when designing standard PCR primers.Votes: 0GitHub stars: 2
- Bio Primer Design Primer ValidationValidate PCR primers for specificity, dimers, hairpins, and secondary structures using primer3-py thermodynamic calculations. Check self-complementarity, heterodimer formation, and 3' stability. Use when validating primer specificity and properties.Votes: 0GitHub stars: 2
- Bio Primer Design Qpcr PrimersDesign qPCR primers and TaqMan/molecular beacon probes using primer3-py. Configure probe Tm, primer-probe spacing, and hydrolysis probe constraints for real-time PCR assays. Use when designing qPCR primers and probes.Votes: 0GitHub stars: 2
- Bio Proteomics Data ImportLoad 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.Votes: 0GitHub stars: 2
- Bio Proteomics Dia AnalysisData-independent acquisition (DIA) proteomics analysis with DIA-NN and other tools. Use when analyzing DIA mass spectrometry data with library-free or library-based workflows for deep proteome profiling.Votes: 0GitHub stars: 2
- Bio Proteomics Differential AbundanceStatistical 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.Votes: 0GitHub stars: 2