Skill UI

Automates time series decomposition work in data analytics by guiding through patterns and best practices, generating production-ready code/configuration, and validating outputs for SQL, visualization, and BI workflows.

Automated help for data analytics visualization best practices, offering step-by-step guidance, industry patterns, production-ready code, and validation for dashboards and reports.

deepTools is a Python command-line suite for NGS workflows, converting BAM files into normalized coverage, running QC (fingerprint, correlation, PCA), comparing samples, and rendering heatmaps or profiles for ChIP-seq, RNA-seq, and ATAC-seq analyses.

A toolkit for phylogenetic tree manipulation, event detection, NCBI taxonomy integration, and publication-quality visualization, streamlining phylogenomics workflows and gene family analysis.

Automates detection and deep exploratory analysis across 200+ scientific data formats, assessing quality, extracting metadata, and recommending visualizations while generating markdown reports that guide downstream workflows and highlight structure and distributions.

End-to-end Neuropixels recording analysis covering SpikeGLX/OpenEphys/NWB loading, preprocessing, motion correction, Kilosort4 sorting, quality metrics, Allen/IBL curation, and AI-assisted visualization for extracellular electrophysiology.

QuTiP is a Python toolbox for simulating open and closed quantum systems, offering solvers for master equations, trajectory methods, visualization, and analysis tailored to quantum research, education, and exploratory physics studies.

Scanpy is a scalable Python toolkit for single-cell RNA-seq analyses, covering QC, normalization, dimensionality reduction, clustering, marker discovery, annotation, and publication-ready visualization across h5ad/10X/CSV datasets.

Transforms data into publication-ready figures with multi-panel layouts, precise annotations, colorblind-friendly palettes, and journal formatting using matplotlib, seaborn, and plotly plus export helpers for PDF/EPS/TIFF.

Seaborn is a powerful Python library for creating publication-quality statistical graphics. It is designed for dataset-oriented plotting, making it ideal for exploratory data analysis, multivariate analysis, and visualizing complex relationships, distributions, and comparisons with minimal code. It builds upon Matplotlib, offering high-level interfaces for functions like scatterplots, heatmaps, and pair plots.

Use UMAP for fast nonlinear manifold reduction to produce embeddings that keep local and global structure, making it ideal for visualization, clustering preprocessing, supervised/parametric workflows, or high-dimensional feature engineering.

A comprehensive toolkit for reconstructing and analyzing the evolutionary history of biological sequences (genes, proteins, genomes). The standard workflow includes multiple sequence alignment using MAFFT, robust maximum likelihood tree inference with IQ-TREE 2 and FastTree, and advanced visualization/manipulation using ETE3. This skill is essential for studies in viral phylodynamics, microbial genomics, protein family evolution, and molecular clock dating.