Bioinformatics & Genomics

Gene expression analysis, GWAS results, and clustering visualizations.

Specialized Visualizations

Volcano Plot

bioinfokit

matplotlib

A scatter plot used to identify changes in large datasets (like RNA-seq), plotting statistical significance (-log10 p-value) against magnitude of change (log2 fold change).

Prompt

"Generate a proper example differential gene expression dataset and create a volcano plot using bioinfokit. Highlight genes with a p-value < 0.05 and fold change > 2 in red. Label the top 5 most significant genes."

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Manhattan Plot

pandas-genomics

qqman

matplotlib

A scatter plot used in Genome-Wide Association Studies (GWAS) to display significant SNPs (Single Nucleotide Polymorphisms) across chromosomes.

Prompt

"Generate a proper example GWAS dataset and create a Manhattan plot displaying the results using matplotlib. Color points by 'Chromosome' and add a horizontal dashed line at the genome-wide significance threshold."

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Clustered Heatmap

seaborn

scanpy

A heatmap that reorders rows and columns based on hierarchical clustering to reveal patterns in gene expression.

Prompt

"Generate a proper example gene expression dataset for 50 highly variable genes across 10 patient samples and create a hierarchically clustered heatmap using seaborn. Use the 'viridis' colormap and normalize the data by row (Z-score)."

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