Claude Skills by FridrichMethod

Precision Oncology

Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strategies, or building backtesting infrastructure.

Generate alignment statistics using samtools flagstat, stats, depth, coverage, and mosdepth. Use when assessing alignment quality, calculating coverage, or generating QC reports.

Analyzes base-editing screens for variant function. Covers library design (Hanna 2021 ClinVar-scale CBE screen benchmarked on BRCA1/2, Cuella-Martin 2021 DDR saturation), CBE vs ABE chemistry choice (BE3/BE4 vs ABE7.10/ABE8.20/ABE8e), editing-window math (positions 4-8 from PAM-distal end; 4-7 for ABE7.10), bystander-edit quantification and the variant-call ambiguity it creates, sgRNA-efficiency filtering before hit calling, indel byproduct interpretation, the substitution-vs-indel diagnostic...

Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequencing run, Cas9 lot, FBS lot), PCA + variance-decomposition diagnostic to decide if correction is needed, when correction harms biology by over-correcting condition into batch, limma removeBatchEffect fo...

Master Bash Automated Testing System (Bats) for comprehensive shell script testing. Use when writing tests for shell scripts, CI/CD pipelines, or requiring test-driven development of shell utilities.

Bayesian Optimize

Optimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.

Use this skill when working with Brain Imaging Data Structure (BIDS) datasets: organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives.

Master binary analysis patterns including disassembly, decompilation, control flow analysis, and code pattern recognition. Use when analyzing executables, understanding compiled code, or performing static analysis on binaries.

"End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate.

"Guidance for choosing the right protein binder design tool. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types.

Guidance for SPR and BLI binding characterization experiments. Use when: (1) Planning binding kinetics experiments, (2) Troubleshooting poor/no binding signal, (3) Interpreting kinetic data artifacts, (4) Choosing between SPR vs BLI platforms.

Annotate CLIP-seq peaks or crosslink sites to RNA features (5'UTR, CDS, 3'UTR, intron, splice junction, snoRNA, tRNA, ncRNA, repeat elements) with ChIPseeker, RCAS, RBP-Maps (Yeo splicing regulatory maps), and bedtools, applying feature-priority hierarchies, transcript-context resolution, and metagene aggregation. Use when characterizing where in transcripts an RBP binds, comparing peak distribution across regions, generating splicing-regulatory maps relative to alternative-splicing events, o...

Generate alignment statistics using samtools flagstat, stats, depth, and coverage. Use when assessing alignment quality, calculating coverage, or generating QC reports.

Filter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific reads, removing low-quality alignments, or subsetting to target regions.

Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific genomic regions.

Sort alignment files by coordinate or read name using samtools and pysam. Use when preparing BAM files for indexing, variant calling, or paired-end analysis.

Validate alignment quality with insert size distribution, proper pairing rates, GC bias, strand balance, and other post-alignment metrics. Use when verifying alignment data quality before variant calling or quantification.

Download large datasets from NCBI efficiently using history server, batching, and rate limiting. Use when performing bulk sequence downloads, handling large query results, or production-scale data retrieval.

Create, manipulate, and convert bedGraph files for genome browser visualization. Covers bedGraph format, conversion to/from bigWig, normalization, and signal processing. Use when handling coverage and signal tracks from ChIP-seq, ATAC-seq, or RNA-seq.

Run remote BLAST searches against NCBI databases using Biopython Bio.Blast. Use when identifying unknown sequences, finding homologs, or searching for sequence similarity against NCBI's nr/nt databases.

Annotate CLIP-seq binding sites to genomic features including 3'UTR, 5'UTR, CDS, introns, and ncRNAs. Use when characterizing where an RBP binds in transcripts.

Align CLIP-seq reads to the genome with crosslink site awareness. Use when mapping preprocessed CLIP reads for peak calling.

Identify enriched sequence motifs at CLIP-seq binding sites for RBP binding specificity. Use when characterizing the sequence preferences of an RNA-binding protein.

Call protein-RNA binding site peaks from CLIP-seq data using CLIPper, PureCLIP, or Piranha. Use when identifying RBP binding sites from aligned CLIP reads.

Preprocess CLIP-seq data including adapter trimming, UMI extraction, and PCR duplicate removal. Use when preparing raw CLIP, iCLIP, or eCLIP reads for peak calling.

Analyze codon usage, calculate CAI (Codon Adaptation Index), and examine synonymous codon bias using Biopython. Use when analyzing coding sequences for expression optimization or evolutionary analysis.

Reconstruct ancestral sequences at phylogenetic nodes using PAML and IQ-TREE marginal likelihood methods. Infer ancient protein sequences and trace evolutionary trajectories through sequence history. Use when inferring ancestral states for protein resurrection or tracing evolutionary history.

Detect horizontal gene transfer events using HGTector, compositional analysis, and phylogenetic incongruence methods. Identify foreign genes in bacterial and archaeal genomes from anomalous composition or unexpected phylogenetic placement. Use when searching for horizontally transferred genes or analyzing genome evolution in prokaryotes.

Infer orthologous gene groups across species using OrthoFinder and ProteinOrtho. Identify orthologs, paralogs, and co-orthologs for comparative genomics and functional annotation transfer. Use when identifying gene orthologs across species or building orthogroups for evolutionary analysis.

Detect positive selection using dN/dS (omega) tests with PAML codeml and HyPhy. Identify sites and branches under adaptive evolution through codon models and branch-site tests. Use when testing for adaptive evolution in gene families or identifying positively selected sites.

Analyze genome collinearity and syntenic blocks using MCScanX, SyRI, and JCVI for comparative genomics. Detect conserved gene order, chromosomal rearrangements, and whole-genome duplications. Use when comparing genome structure between species or identifying conserved genomic regions.

Create circular genome visualizations with Circos and pyCircos. Display multi-track data including ideograms, genes, variants, CNVs, and interaction arcs. Use when creating circular genome visualizations.

Select and apply colorblind-friendly palettes for scientific figures using viridis, RColorBrewer, and custom color schemes. Use when selecting colorblind-friendly palettes for figures.

Generate genome browser visualizations using pyGenomeTracks or IGV batch scripting for publication figures. Use when creating publication figures of genomic regions with multiple data tracks.

Create genome browser-style visualizations showing multiple data tracks (coverage, peaks, genes) using pyGenomeTracks, Gviz, and IGV. Use when visualizing genomic data at specific loci with multiple aligned tracks.

Create publication-quality scientific figures with ggplot2 including scatter plots, boxplots, heatmaps, and multi-panel layouts. Use when creating static figures for papers, presentations, or reports in R.

Create clustered heatmaps with row/column annotations using ComplexHeatmap, pheatmap, and seaborn for gene expression and omics data visualization. Use when visualizing expression patterns across samples or identifying co-expressed gene clusters.

Create interactive HTML plots with plotly and bokeh for exploratory data analysis and web-based sharing of omics visualizations. Use when building zoomable, hoverable plots for data exploration or web dashboards.

Combine multiple plots into publication-ready multi-panel figures using patchwork, cowplot, or matplotlib GridSpec with shared legends and panel labels. Use when combining multiple plots into publication figures.

Reusable plotting functions for common omics visualizations. Custom ggplot2/matplotlib implementations of volcano, MA, PCA, enrichment dotplots, boxplots, and survival curves. Use when creating volcano, MA, or enrichment plots.

Create UpSet plots to visualize set intersections as an alternative to Venn diagrams using UpSetR or upsetplot. Use when comparing overlapping gene sets, peak sets, or sample groups with more than 3 sets.

Create publication-ready volcano plots with custom thresholds, gene labels, and highlighting using ggplot2, EnhancedVolcano, or matplotlib. Use when visualizing differential expression or association results with gene annotations.

Mark and remove PCR/optical duplicates using samtools fixmate and markdup. Use when preparing alignments for variant calling or when duplicate reads would bias analysis.

Retrieve records from NCBI databases using Biopython Bio.Entrez. Use when downloading sequences, fetching GenBank records, getting document summaries, or parsing NCBI data into Biopython objects.

Find cross-references between NCBI databases using Biopython Bio.Entrez. Use when navigating from genes to proteins, sequences to publications, finding related records, or discovering database relationships.

Search NCBI databases using Biopython Bio.Entrez. Use when finding records by keyword, building complex search queries, discovering database structure, or getting global query counts across databases.

Identify differential m6A methylation between conditions from MeRIP-seq. Use when comparing epitranscriptomic changes between treatment groups or cell states.