Microbiome Diversity Reporter
Interpret Alpha and Beta diversity metrics from 16S rRNA sequencing results.
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Interpret Alpha and Beta diversity metrics from 16S rRNA sequencing results.
Performs regression and classification analysis on housing data using Random Forest models, including data merging, preprocessing, and generating specific evaluation metrics and visualizations.
Differential gene expression analysis for bulk RNA-seq count matrices using a DESeq2-like workflow in Python; use when you need Wald tests, FDR correction, and optional LFC shrinkage for condition/batch/covariate designs.
Quality control and assessment for proteomics data. Use when evaluating proteomics data quality before downstream analysis. Covers sample metrics, missing value patterns, replicate correlation, batch effects, and intensity distributions.
Create publication-quality visualizations of immune repertoire data including circos plots, clone tracking, diversity plots, and network graphs. Use when generating figures for repertoire comparisons, clonal dynamics, or V(D)J gene usage.
Build publication-quality figures with matplotlib using the object-oriented Figure/Axes API, constrained_layout, rcParams customization, TrueType (Type-42) font embedding for journal submission, and CVD-safe palettes. Covers seaborn integration, common chart types, axis formatting, and the small ...
Analyze data with `pseudotime-trajectory-viz` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
Kaplan-Meier survival analysis tool for clinical and biological research. Generates publication-ready survival curves with statistical tests.
Build clustered heatmaps for expression matrices and other features-by-samples data with rigorous distance/linkage/scaling choices, robust color mapping, optimal leaf ordering, and ComplexHeatmap/pheatmap/seaborn rendering. Covers the ward.D vs ward.D2 trap, the row-vs-column scaling decision, mu...
End-to-end genome-scale metabolic modeling from genome sequence to flux predictions. Covers automated reconstruction with CarveMe, model validation with memote, FBA/FVA analysis, and gene essentiality prediction. Use when building metabolic models or predicting metabolic phenotypes from genomic d...
Quality control and exploration of RNA-seq count matrices before differential expression. Check for outliers, batch effects, and sample relationships. Use when assessing count matrix quality before DE analysis.
Guide for annotating statistical significance (p-value asterisks) on comparison plots. Covers standard notation (ns, *, **, ***, ****), matplotlib bracket+asterisk implementation, and use with seaborn box/violin/bar plots. Use when preparing publication-ready figures with significance markers.
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