Data & Analytics · Python · By GPTomics

Validate alignment quality with insert size distribution, proper pairing rates, GC bias, strand balance, and other post-alignment metrics.

GPTomics/bioSkills

Build circular genome visualizations using circlize (R), pyCirclize (Python), or Circos (Perl CLI) with ideogram tracks, multi-data tracks (scatter, histogram, heatmap), chord/link arcs for…

GPTomics/bioSkills

Plot per-group distributions of continuous data using boxplots, violins, beeswarms, quasirandom jitter, and raincloud plots with sample-size honesty (Weissgerber 2015), KDE-bandwidth awareness, and…

GPTomics/bioSkills

Build Sankey, alluvial, river, and CONSORT-style flow diagrams to visualize cohort transitions, cell-state changes, or pipeline filtering using ggalluvial, networkD3, plotly, and consort.

GPTomics/bioSkills

Build interactive HTML/web visualizations with plotly (Python/R), bokeh (Python), and gganimate/plotly frames for animation, with awareness of current Kaleido static-export model (post-orca-EOL)…

GPTomics/bioSkills

Build publication-quality figures with matplotlib using the object-oriented Figure/Axes API, constrainedlayout, rcParams customization, TrueType (Type-42) font embedding for journal submission, and…

GPTomics/bioSkills

Compose multi-panel publication figures with patchwork, cowplot, gridExtra (R), or matplotlib GridSpec/subfigures (Python) including shared axes/legends/guides collection, panel labels in…

GPTomics/bioSkills

Visualize biological networks (PPI, gene-regulatory, co-expression, pathway) with layout algorithm choice (ForceAtlas2, Fruchterman-Reingold, Kamada-Kawai, hive plots), edge bundling…

GPTomics/bioSkills

Build OncoPrint and co-mutation matrix plots from somatic-variant cohorts using ComplexHeatmap, maftools, and comut.py with alteration-type stacking, sample ordering by mutational burden…

GPTomics/bioSkills

Build sequence logos from aligned DNA, RNA, or protein motifs using ggseqlogo (R), Logomaker (Python), or WebLogo with explicit bits vs probability encoding, background-frequency correction, custom…

GPTomics/bioSkills

Add p-value brackets, significance asterisks, and effect-size annotations to distribution plots using ggpubr, ggsignif, and statannotations with correct test selection (parametric vs non-parametric…

GPTomics/bioSkills

Build UpSet plots to visualize set intersections beyond 4 sets (where Venn fails) using ComplexUpset (modern, ggplot2-grammar) or the unmaintained UpSetR, with explicit cardinality vs degree…

GPTomics/bioSkills

Process many sequence files in batch (count, merge, split, convert, summarize) with memory-safe streaming and on-disk indexing using Biopython, pysam, or pyfastx.

GPTomics/bioSkills

Handles BED-format genomic intervals (BED3 through BED12, narrowPeak/broadPeak) and the coordinate-system substrate the whole interval category rests on, with bedtools (CLI) and…

GPTomics/bioSkills

Turns a shotgun profiler table (MetaPhlAn relative abundance, Bracken counts, HUMAnN function tables) into honest figures and defensible community statistics with phyloseq, vegan, microViz, and…

GPTomics/bioSkills

Draw and export phylogenetic trees with Bio.Phylo plus matplotlib, and route rich figures to ggtree, ETE4, or iTOL.

GPTomics/bioSkills

Computes linkage disequilibrium (r2, D', composite Rogers-Huff r2), prunes correlated variants, clumps GWAS summary statistics to lead SNPs, and defines haplotype blocks with PLINK 1.9/2.0 and…

GPTomics/bioSkills

In-memory Python population genetics with scikit-allel - GenotypeArray/HaplotypeArray/AlleleCountsArray, diversity (pi, theta, Tajima's D), SFS, FST (Weir-Cockerham, Hudson, Patterson), f3/D…

GPTomics/bioSkills

Builds and manages DIA spectral libraries as peptide query parameters (precursor m/z, a few fragment m/z plus relative intensities, normalized RT, optional CCS), covering experimental DDA…

GPTomics/bioSkills

Builds reproducible Quarto reports, presentations, and websites across R, Python, and Julia, with correct engine selection, cache-vs-freeze semantics, native cross-references, parameters, and…

GPTomics/bioSkills

Infers directed, time-delayed gene regulatory edges from BULK time-series expression using Granger causality (statsmodels VAR F-test), dynGENIE3 (tree ensembles regressing ODE-derived derivatives…

GPTomics/bioSkills

Applies ACMG/AMP 2015 framework with ClinGen SVI specifications, Tavtigian 2018/2020 Bayesian point system, Abou Tayoun 2018 PVS1 decision tree, Pejaver 2022 and Bergquist 2025 calibrated PP3/BP4…

GPTomics/bioSkills

Infers and describes population structure with PCA (plink2 --pca, smartpca/EIGENSOFT, FlashPCA2), model-based clustering (ADMIXTURE, fastSTRUCTURE), FST estimators (Weir-Cockerham vs Hudson), and…

GPTomics/bioSkills

Tests for differentially abundant proteins between conditions with limma/DEqMS empirical-Bayes moderation, proDA/msqrob2/MSstats missingness modeling, and Python Welch+BH alternatives.

GPTomics/bioSkills

End-to-end bulk time-course analysis from an expression matrix to temporal gene modules and per-cluster pathway enrichment.

GPTomics/bioSkills

Builds publication-ready tables - descriptive Table 1, regression and differential-expression result tables, and supplementary tables - with gtsummary, gt, flextable, and kableExtra (R) or…

GPTomics/bioSkills