Web & Frontend

fridrichmethod Bundle

Build a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative overlap removal, fixed-width re-centering, and majority-rule overlap. Use when generating a stable peak coordinate system for downstream differential accessibility, ML feature engineering, cross-sample comparison, or fixed-width peak counts; covers Corces 2018 iterative overlap (501 bp), DiffBind summit re-centering, and ENCODE consistency rules.

fridrichmethod Bundle

Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.

fridrichmethod Bundle

Calls significant loops from protein-directed and targeted 3C assays (HiChIP, PLAC-seq, Capture Hi-C/PCHi-C, ChIA-PET) where the contact background is peak-anchored and coverage-biased, so generic Hi-C loop callers (cooltools dots, Juicer HiCCUPS) use the wrong null. Covers FitHiChIP (config-driven coverage+distance-decay spline regression, peak-to-peak vs peak-to-all foreground, loose vs stringent background, coverage vs ICE bias), MAPS (positive Poisson regression on bias factors for PLAC-seq/HiChIP), hichipper (restriction-site-distance bias model + library QC), CHiCAGO (Delaporte two-component Brownian+technical background for asymmetric bait x other-end Capture Hi-C), the with/without separate-ChIP anchor decision, and differential loops via diffloop. Use when calling loops from HiChIP/PLAC-seq/Capture Hi-C, choosing FitHiChIP/MAPS/CHiCAGO, picking peak-to-all vs peak-to-peak, setting the loop FDR, supplying ChIP peaks as anchors, QCing a HiChIP library, or comparing loops between conditions.

fridrichmethod Bundle

Orchestrates the end-to-end bulk short-read alternative-splicing pipeline from FASTQ to differential splicing, chaining fastp QC, cohort-consistent STAR 2-pass alignment (one shared junction DB), junction QC, event-level differential splicing (rMATS-turbo + leafcutter, optional MAJIQ V3), parallel isoform-level DTU (Salmon -> tximport dtuScaledTPM -> DRIMSeq/DEXSeq -> stageR), and sashimi visualization. Use when committing the annotation GTF and a shared 2-pass junction database for the whole cohort, keeping the analysis at splice-aware resolution (never collapsing to gene), choosing event-level vs isoform-level DTU and reconciling them, applying the stageR two-stage gene->transcript FDR, or off-ramping to splice-variant / outlier / long-read / single-cell splicing. Hands mechanism to the alternative-splicing component skills; not a re-teach of any single step.

fridrichmethod Bundle

Sequence-based deep learning for ATAC-seq using chromBPNet, BPNet, scBasset, or Enformer. Use when correcting Tn5 bias with neural networks beyond k-mer models, predicting per-base accessibility profiles, scoring in silico variant effects at GWAS or rare-variant SNPs, discovering motifs via DeepLIFT/TF-MoDISco from a trained model, or generating cell-type-specific accessibility predictions for unobserved cell states.

intense-visions Bundle

XState React Integration

intense-visions Bundle

Angular Component Pattern

intense-visions Bundle

Astro Content Collections

intense-visions Bundle

Astro Integration Pattern

intense-visions Bundle

React Memoization Pattern

intense-visions Bundle

Vue Renderless Components

intense-visions Bundle

Screen Reader Testing

intense-visions Bundle

Astro Islands Architecture

intense-visions Bundle

Color Accessibility

intense-visions Bundle

React Render Props Pattern

intense-visions Bundle

Test Accessibility Testing

intense-visions Bundle

React Progressive Hydration

intense-visions Bundle

Svelte Performance Patterns

intense-visions Bundle

Next.js Deployment Optimization

intense-visions Bundle

Svelte Component Composition

intense-visions Bundle

tRPC React Query Integration

intense-visions Bundle

Svelte Transitions and Animations

intense-visions Bundle

React Container/Presentational Pattern

intense-visions Bundle

React State Management Pattern

intense-visions Bundle

Next.js Parallel and Intercepting Routes

intense-visions Bundle

Astro Multi-Framework

intense-visions Bundle

Astro Routing Pattern

intense-visions Bundle

CSS Animation Pattern

intense-visions Bundle

Custom Styled Components

intense-visions Bundle

Responsive Design with Tailwind

intense-visions Bundle

Next.js Error Boundaries

intense-visions Bundle

Next.js Testing Patterns

intense-visions Bundle

React Context Pattern

intense-visions Bundle

React Islands Pattern

intense-visions Bundle

React Context Pattern

intense-visions Bundle

Svelte Adapter Config