Claude Configs
CLAUDE.md project files and Claude Code slash commands
Showing 4,801–4,860 of 12,601 skills · Page 81 of 211
jaechang-hits / gnomad-database
367gnomAD v4 population variant frequencies via GraphQL API. Allele counts and frequencies stratified by ancestry (AFR, AMR, EAS, NFE, SAS, FIN, ASJ, MID), gene-level constraint (pLI, LOEUF, missense z), and coverage. Identify rare or constrained variants.
jaechang-hits / gwas-database
367NHGRI-EBI GWAS Catalog REST API for SNP-trait associations from published GWAS. Query studies, associations, variants, traits, genes, summary stats. Build PRS candidates, analyze pleiotropy, fetch stats for Manhattan plots. No auth.
jaechang-hits / jaspar-database
367JASPAR 2024 TF binding profiles via REST API and pyJASPAR. Retrieve PFMs/PWMs by TF name, JASPAR ID, species, or structural class. Scan DNA for TFBS; browse by taxon (human, mouse) or TF family (bHLH, zinc finger). Use for motif enrichment input, TFBS scanning, and regulatory sequence analysis.
jaechang-hits / kegg-database
367KEGG REST API (academic only). Pathways, genes, compounds, enzymes, diseases, drugs via 7 ops (info/list/find/get/conv/link/ddi). ID conversion (NCBI/UniProt/PubChem). Use bioservices for multi-DB Python.
jaechang-hits / monarch-database
367Monarch Initiative knowledge graph REST API for disease-gene-phenotype associations and cross-species orthology. MONDO disease-to-gene/phenotype, HP phenotype profiles, cross-species comparisons. Use for rare disease gene prioritization and phenotype-based candidate ranking.
jaechang-hits / mouse-phenome-database
367Retrieve mouse phenotype data from the Jackson Laboratory Mouse Phenome Database (MPD) via its REST API. Browse 520+ projects, look up per-project measure metadata, pull strain-level means (raw or LS-mean adjusted) and per-animal values, find measures by MP/VT ontology terms, and resolve strain nome…
jaechang-hits / quickgo-database
367Query EBI QuickGO REST API for GO terms and protein annotations. Fetch term metadata by ID, search by keyword, walk ancestor/descendant hierarchies, download annotations filtered by taxon, evidence code, aspect. Use for GO resolution, ontology traversal, annotation retrieval before enrichment.
jaechang-hits / regulomedb-database
367Query RegulomeDB v2 GET REST API to score variants for regulatory function and retrieve overlapping evidence (TF binding, histone marks, DNase peaks, footprints, motifs, eQTLs, chromatin state). Scores range 1a (strongest) to 7 (none).
jaechang-hits / remap-database
367Query ReMap 2022 TF ChIP-seq peak database via REST API and BED downloads. Retrieve TF peaks overlapping a region (chr:start-end), peaks near a gene, TFs by species, peaks filtered by biotype (promoter, enhancer), and BED files for a TF-cell type pair.
jaechang-hits / ucsc-genome-browser
367Query UCSC Genome Browser REST API for DNA sequences, tracks, gene models, and conservation across 100+ assemblies. Retrieve sequence by region, list/fetch BED/bigWig tracks, chromosome sizes, RefSeq/GENCODE gene structures, PhyloP/PhastCons scores.
jaechang-hits / bedtools-genomic-intervals
367Genomic interval ops on BED/BAM/GFF/VCF. Find overlaps, merge intervals, compute coverage, extract FASTA, find nearest features. Core for ChIP-seq peak annotation, region filtering, genome arithmetic. Use tabix for indexed single-region queries; use deeptools for normalized bigWig coverage.
jaechang-hits / deeptools-ngs-analysis
367NGS CLI for ChIP/RNA/ATAC-seq. BAM→bigWig with RPGC/CPM/RPKM, sample correlation/PCA, heatmaps/profiles around features, fingerprints. For alignment use STAR/BWA; for peak calling use MACS2.
jaechang-hits / geniml
367Python library for genomic interval ML. Train/apply region2vec embeddings turning BED regions into vectors, index interval datasets for ML, search embedding space with BEDSpace, and evaluate embedding quality.
jaechang-hits / gtars
367Rust-backed Python library for fast genomic token arithmetic and BED processing. High-performance BED I/O, interval set ops (intersect, merge, complement, subtract), region tokenization against a universe, universe construction. Use for preprocessing large BED collections and ML token vocabularies.
jaechang-hits / busco-status-interpretation
367Guide to interpreting BUSCO completeness statuses: why Duplicated BUSCOs count as complete, parsing output files, computing/comparing completeness across proteomes/genomes, common counting mistakes
jaechang-hits / fastp-fastq-preprocessing
367All-in-one FASTQ QC and adapter trimming. Auto-detects Illumina adapters, filters low-quality reads, corrects paired-end overlaps, emits HTML+JSON QC in one pass. 3-10x faster than Trim Galore/Trimmomatic. First step before STAR, BWA-MEM2, or Salmon.
jaechang-hits / deseq2-differential-expression
367Bulk RNA-seq DE with R/Bioconductor DESeq2. Negative binomial GLM, empirical Bayes shrinkage, Wald/LRT tests, multi-factor designs, Salmon tximeta import, apeglm LFC shrinkage, MA/volcano/heatmap viz. R gold standard. Use pydeseq2-differential-expression for Python; use edgeR for TMM normalization.
jaechang-hits / featurecounts-rna-counting
367Counts RNA-seq reads overlapping GTF gene features. Takes sorted STAR BAMs plus GTF; outputs a per-gene tab-delimited matrix across samples. Handles strandedness (0/1/2), paired-end, multi-sample batch counting in one command, and outputs assignment statistics.
jaechang-hits / gseapy-gene-enrichment
367GSEA and over-representation analysis (ORA) for RNA-seq and proteomics. Wraps Enrichr for ORA against MSigDB, KEGG, GO, and 200+ databases; runs preranked GSEA on ranked DE gene lists. Outputs enrichment tables and running-score plots. Use after DESeq2 or edgeR for pathway-level interpretation.
jaechang-hits / pydeseq2-differential-expression
367Bulk RNA-seq DE with PyDESeq2: load counts, normalize, fit negative binomial models, Wald test (BH-FDR), LFC shrinkage, volcano/MA plots. Use for two-group comparisons, multi-factor designs with batch correction, multiple contrasts.
jaechang-hits / salmon-rna-quantification
367Ultra-fast RNA-seq transcript/gene quantification via quasi-mapping (no BAM). Builds a k-mer index from transcriptome FASTA, quantifies in minutes. Outputs TPM/count tables (quant.sf) with optional GC- and sequence-bias correction. Integrates with tximeta/tximport for DESeq2/edgeR.
jaechang-hits / anndata-data-structure
367Annotated matrices for single-cell genomics. Stores X with obs/var metadata, layers, embeddings (obsm/varm), graphs (obsp/varp), uns. Use for .h5ad/.zarr I/O, concatenation, scverse integration. For analysis use scanpy; for probabilistic models use scvi-tools.
jaechang-hits / celltypist-cell-annotation
367Automated scRNA-seq cell type annotation via pre-trained logistic regression. 45+ models: immune, gut, lung, brain, fetal, cancer microenvironments. Input normalized AnnData; outputs per-cell labels, majority-vote cluster labels, confidence scores.
jaechang-hits / cellxgene-census
367Query CELLxGENE Census (61M+ cells). Search by cell type/tissue/disease/organism; get AnnData, stream out-of-core, train PyTorch models. For your own data use scanpy; for annotated data use anndata.
jaechang-hits / harmony-batch-correction
367Harmony batch correction for scRNA-seq and other omics. Removes batch effects from PCA embeddings while preserving biology. Run after PCA, before UMAP. Scales to millions of cells. Python (harmonypy, scanpy) and R (Seurat).
jaechang-hits / popv-cell-annotation
367Consensus cell type annotation: runs 10+ algorithms (KNN-Harmony/BBKNN/Scanorama/scVI, CellTypist, ONCLASS, Random Forest, SCANVI, SVM, XGBoost) on a labeled reference and transfers labels via majority voting. Outputs per-method labels, consensus, agreement score
jaechang-hits / scanpy-scrna-seq
367scRNA-seq with Scanpy: QC, normalization, HVG selection, PCA, neighborhood graph, UMAP/t-SNE, Leiden clustering, markers, cell annotation, trajectory inference. Standard scRNA-seq exploration.
AlpacaLabsLLC / learn
361Guided, hands-on course teaching architects how to use Codex or Claude Code — six short modules, each built around an exercise on a bundled sandbox project (a fictional Brooklyn art museum expansion). Resumable across sessions via PROGRESS.md
AlpacaLabsLLC / product-enrich
361Enrich FF&E schedule rows with categories, colors, materials, and style tags. Use to tag, categorize, or fill those missing fields; not to research new products.
kazukinagata / e-tax
360This skill should be used when the user wants to file their tax return electronically via the 確定申告書等作成コーナー (NTA Tax Return Preparation Corner) using Claude in Chrome, Antigravity Browser Sub-Agent, or Playwright CLI (fallback). It guides the browser-based input of calculated tax data.
kazukinagata / income-tax
360This skill should be used when the user needs to calculate their income tax (所得税), compute deductions, or import withholding slips. Trigger phrases include: "所得税を計算", "確定申告書を作成", "控除を計算", "源泉徴収票を取り込む", "所得税額", "納付額を計算", "還付額を計算", "第一表", "第二表", "申告書B", "所得控除", "税額控除".
athola / night-market-collective-memory
338Search and record project memory (Discussions, journal, ADRs). Use before re-investigating anything. Do not use for settled battles; see failure-archaeology.
athola / night-market-completion-integrity-campaign
338Bind loop 'done' to unfakeable gates. Use to harden egregore/herald loops or promote completion_integrity. Not for QA gates; use night-market-validation-and-qa.
athola / project-brainstorming
338Guides project ideation via Socratic questioning to produce a validated brief. Use before specification when requirements are unclear.
athola / project-execution
338Executes implementation plans with progress tracking, checkpoint validation, and quality gates. Use after planning is complete and tasks are ready to implement.
datadrivenconstruction / as-built-documentation
333Automate as-built documentation and digital handover for construction. Compile project records, generate O&M manuals, create asset databases, and ensure complete project closeout.
datadrivenconstruction / bim-visual-programming-automation
333Automate BIM workflows using visual programming and Python. Create parametric schedules, export data, batch modify elements, and integrate with external data sources.
datadrivenconstruction / capacity-planning
333Plan organizational capacity for construction projects. Forecast resource needs, identify capacity gaps, and support strategic planning for project pursuit and staffing.
datadrivenconstruction / change-order-analysis
333Analyze and predict construction change orders using ML. Classify change order types, predict costs and schedule impacts, identify patterns, and optimize approval workflows.
datadrivenconstruction / clash-detection-analysis
333Detect and analyze geometric clashes between BIM elements. Identify hard clashes, soft clashes, and workflow conflicts using spatial analysis and rule-based detection.
datadrivenconstruction / contractor-matching-ai
333AI-powered contractor matching and selection for construction projects. Analyze contractor capabilities, past performance, certifications, and project requirements to recommend optimal matches.
datadrivenconstruction / defect-detection-ai
333AI-powered construction defect detection using computer vision. Identify cracks, spalling, corrosion, and other defects in concrete, steel, and building components from images and video.
datadrivenconstruction / digital-twin-sync
333Synchronize construction digital twins with real-time data. Connect BIM models with IoT sensors, progress updates, and field data for live project visualization and monitoring.
datadrivenconstruction / document-classification-nlp
333Automatically classify and extract information from construction documents using NLP. Categorize RFIs, submittals, change orders, specifications, and contracts.
datadrivenconstruction / drone-site-survey
333Process drone survey data for construction sites. Generate orthomosaics, DEMs, point clouds, calculate volumes, track progress, and integrate with BIM models for comparison.
datadrivenconstruction / energy-simulation
333Building energy simulation and analysis for construction. Calculate heating/cooling loads, evaluate envelope performance, optimize HVAC sizing, and ensure energy code compliance.
datadrivenconstruction / enterprise-risk-aggregator
333Aggregate and analyze risks across construction project portfolio. Identify correlated risks, systemic exposures, and portfolio-level risk mitigation strategies.
datadrivenconstruction / environmental-monitoring
333Monitor environmental conditions on construction sites. Track air quality, noise levels, vibration, dust, and weather to ensure compliance and worker safety.
datadrivenconstruction / equipment-telematics
333Integrate and analyze telematics data from heavy construction equipment. Track location, utilization, fuel consumption, maintenance needs, and operator behavior.
datadrivenconstruction / ifc-data-extraction
333Extract structured data from IFC (Industry Foundation Classes) files using IfcOpenShell. Parse BIM models, extract quantities, properties, spatial relationships, and export to various formats.
datadrivenconstruction / labor-productivity-analytics
333Analyze construction labor productivity using data analytics. Track worker performance, identify inefficiencies, predict resource needs, and optimize crew allocation for maximum efficiency.
datadrivenconstruction / material-tracking-iot
333IoT-based material tracking for construction sites. Monitor material delivery, storage conditions, usage, and inventory with sensors, RFID, GPS, and real-time dashboards.
datadrivenconstruction / open-construction-estimate
333Access and utilize open construction pricing databases. Match BIM elements to standardized work items, calculate costs using public unit price databases with 55,000+ work items.
datadrivenconstruction / permit-tracking-automation
333Automate construction permit tracking and management. Monitor application status, track renewal deadlines, manage document requirements, and integrate with municipal systems.
datadrivenconstruction / portfolio-dashboard
333Multi-project portfolio analytics dashboard. Aggregate KPIs across projects, track portfolio health, compare performance, and support executive decision-making.
datadrivenconstruction / prefab-optimization
333Optimize prefabrication and modular construction workflows. Plan module sequencing, factory scheduling, transportation logistics, and on-site assembly for maximum efficiency.
datadrivenconstruction / resource-pool-optimizer
333Optimize shared resource pools across multiple construction projects. Balance resource allocation, minimize conflicts, and maximize utilization across the portfolio.
datadrivenconstruction / risk-assessment-ml
333Apply machine learning for construction project risk assessment. Predict schedule delays, cost overruns, and safety incidents using historical data and project characteristics.
datadrivenconstruction / safety-compliance-checker
333Automated safety compliance verification for construction sites. Check PPE usage, zone access, working at heights regulations, and generate compliance reports using rule-based and ML approaches.
datadrivenconstruction / sensor-data-aggregator
333Aggregate and analyze IoT sensor data from construction sites. Collect data from multiple sensor types, detect anomalies, and trigger alerts for safety and quality monitoring.