GitHub
tessa
TESSA (TCR and Expression Joint Clustering) is a Bayesian model that integrates T-cell receptor (TCR) sequence profiling with transcriptomes of T cells. It maps the functional landscape of the TCR repertoire by...
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seuratpreparing
Load, prepare, and apply quality control (QC) to single-cell RNA-seq data using Seurat. Performs data loading, QC filtering, normalization, and multi-sample integration. This is a core preprocessing process tha...
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GitHub
screploading
Load single-cell TCR-seq or scBCR-seq data from various formats into a scRepertoire-compatible object. This process reads VDJ (variable, diversity, joining) receptor contig data from multiple single-cell sequen...
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GitHub
torbcellselection
Separates T and non-T cells or B and non-B cells from a mixed cell population. Uses either clonotype percentage from VDJ data, indicator gene expression (CD3 markers for T cells, CD19/CD20 for B cells), custom...
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GitHub
seuratclustering
Performs unsupervised clustering on single-cell RNA-seq data using Seurat. This process finds nearest neighbors, computes UMAP for visualization, and applies Louvain/Leiden algorithms to identify cell clusters....
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GitHub
metabolicexpimputation
Imputes missing/dropout values in scRNA-seq expression data to improve metabolic pathway analysis. This process handles sparsity common in single-cell RNA sequencing data by filling in zero values using advance...
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GitHub
celltypeannotation
Annotates cell clusters with biological cell type labels using multiple methods: direct assignment, ScType, scCATCH, hitype, or CellTypist. This process is essential for interpreting clustering results by assig...
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GitHub
scrnametaboliclandscape
Comprehensive metabolic landscape analysis pipeline for scRNA-seq data. This is an all-in-one process group performing complete metabolic pathway analysis including expression imputation, feature selection, pat...
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GitHub
seuratclusteringofallcells
Performs coarse clustering on ALL cells (including T cells, B cells, and non-T/B cells) before cell type selection. This process identifies broad cell populations to enable subsequent T/B cell selection via `TO...
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GitHub
clustermarkersofallcells
Finds marker genes for clusters of ALL cells before T/B cell selection. This process identifies differentially expressed genes across unsupervised clusters to help identify broad cell types (T cells, B cells, M...
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GitHub
clustermarkers
Finds differentially expressed genes (markers) for clusters of T/B cells using Seurat's FindMarkers function. Performs statistical testing between clusters, identifies cluster-defining genes, and automatically...
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GitHub
pseudobulkdeg
Performs pseudo-bulk differential gene expression analysis using DESeq2 or edgeR. Aggregates single-cell counts to sample-level pseudo-bulk data, then identifies differentially expressed genes between condition...
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GitHub
metabolicpathwayheterogeneity
Analyzes metabolic pathway heterogeneity within cell populations by calculating normalized enrichment scores (NES) for each pathway across different groups. Quantifies metabolic diversity and identifies pathway...
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GitHub
cellcellcommunication
Infer ligand-receptor interactions and cell-cell communication networks from single-cell RNA-seq data using the LIANA+ framework. Identifies potential signaling events between cell types based on gene expressio...
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GitHub
vitest-best-practices
Comprehensive vitest testing patterns covering test structure, AAA pattern, parameterized tests, assertions, mocking, test doubles, error handling, async testing, and performance optimization. Use when writing,...
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GitHub
smoke-tests
Run smoke tests on a deployed environment to ensure basic functionality.
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GitHub
reasoning-causal
Execute evidence-based decision-making through 6-stage causal flow. Use for known processes, operational execution, and decisions with clear cause-effect chains.
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GitHub
goal-tracker
Track goal progress, derive state from execution, identify gaps, trigger actions. Use for goal status checks, progress reviews, and operational goal management.
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GitHub
goal-setter
Transform objectives into structured goals with plans. Use when user declares intent ("I want to...", "Goal is to...", "Achieve X by Y"). Decomposes into subgoals, milestones, success criteria.
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GitHub
healthkit-sync
iOS HealthKit data sync CLI commands and patterns. Use when working with healthsync CLI, fetching Apple Health data (steps, heart rate, sleep, workouts), pairing iOS devices over local network, or understanding...
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GitHub
agent-browser
Browser automation using Vercel's agent-browser CLI. Use when you need to interact with web pages, fill forms, take screenshots, extract data, or test web applications. Uses ref-based element selection from acc...
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GitHub
create-new-routes
Learn how to create a new route in The Lab.
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GitHub
visualize-any-data
Learn how to visualize data in a sustainable, accurate, and theme aware way.
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GitHub
create-new-component
Create a new React component following Lab's architecture patterns. Determines component scope (core vs. page-scoped), generates proper structure with TypeScript types, creates Storybook stories for core compon...
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