Pavel-Kravchenko/Bioinformatics

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Basecall ONT POD5 with Dorado, align with Minimap2, assemble with Flye/Hifiasm, call SVs with Sniffles2. Use when basecalling nanopore reads, doing long-read assembly, SV calling, or ONT methylation/isoform analysis.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Parse LC-MS mzML with pyOpenMS, PQN/LOESS-normalize feature tables, match m/z to HMDB/GNPS by ppm, run COBRApy FBA. Use when doing metabolomics preprocessing, metabolite ID, feature QC, MSEA enrichment, or flux modeling.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Compute 16S/ITS amplicon diversity (Shannon, Simpson, Bray-Curtis, UniFrac), PCoA/NMDS ordination, PERMANOVA on OTU/ASV tables from QIIME2/DADA2. Use for 16S microbiome analysis.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Run Bowtie2 decontamination, Kraken2/Bracken classification, HUMAnN3 pathways, and MEGAHIT/MetaBAT2/CheckM MAG recovery on shotgun metagenomes. Use for WMS/WGS metagenomics, microbiome profiling, or MAG binning.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Build PPI networks from STRING with NetworkX, find hub genes via centrality, detect Louvain modules, infer GRNs with GENIE3. Use for protein interaction networks, hub/bottleneck genes, network communities, GRN inference.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Detect and correct for population stratification and cryptic relatedness in genotype data using PCA, kinship/IBD estimation, and genomic inflation factor (lambda) diagnostics before running a GWAS. Use when doing ancestry PCA, checking sample relatedness, computing genomic inflation, or QC'ing genotype data for…

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Embed proteins with ESM2, predict structure via ESMFold, zero-shot score mutations with ESM-1v, or design sequences via ESM-IF1 (fair-esm). Use for protein embeddings, MSA-free structure, DMS/VUS scoring, fixed-backbone design.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Write Python decorators/context managers/dataclasses and query gene/variant tables with sqlite3/pandas SQL (JOIN, GROUP BY, HAVING). Use for retry/caching/validation wrappers or SQL against Ensembl/UCSC-style schemas.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Build Python classes for Gene/DNA/RNA/Protein records with eq/lt/hash, @property validation, ABCs, and @classmethod parsers (fromfastastring). Use when modeling genes/FASTA/GFF as objects or asked about Python OOP, inheritance, dataclasses.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Write Python comprehensions/generator expressions to filter, transform, count DNA/RNA/protein sequences (GC%, codons, k-mers, ORFs). Use when refactoring loop-heavy sequence code or streaming FASTA/FASTQ memory-efficiently.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Build Python context managers (enter/exit, @contextmanager, sqlite3) for safe FASTA I/O, temp cleanup, DB transactions. Use for leaked file handles, temp files surviving crashes, or with-compatible readers/writers.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Write if/elif/for/while loops over DNA/RNA/protein strings: codon iteration, stop-codon/motif scanning, GC-content classification. Use when looping over sequences, extracting codons, or debugging an off-by-one loop.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Use Python's int, float, str, bool, and None types to represent and validate biological data (sequence lengths, GC content, DNA/RNA strings, missing annotations) and convert between them when parsing text records. Use when writing beginner Python for bioinformatics, explaining type() output, fixing float-equality bugs…

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Build volcano/MA plots, clustermap heatmaps, and multi-panel GridSpec figures with matplotlib/seaborn. Use when plotting DE results, expression data, or QC distributions, or fixing savefig, log-axis, colormap bugs.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Clean/reshape bio pandas tables — impute NaNs, dedupe replicates, coerce clinical strings to numeric/categorical, melt/pivot wide-long, regex-parse GTF attrs. Use for cleaning expr/clinical dataframes or reshaping.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Write @decorators (functools.wraps, @lrucache, factories) to time, validate, and memoize bio functions. Use for pipeline timing/logging, DNA/protein alphabet checks, caching codon/alignment calls, or decorator stacking.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Use Python dict/defaultdict/Counter/set to translate codons, count k-mers, group genes by chromosome, and compare gene lists (union/intersection). Use when translating DNA, counting k-mers, or comparing gene sets.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Handle malformed FASTA/GFF via try/except/else/finally, custom exceptions, raise-from chaining. Use for parsers crashing on bad input, strict vs lenient FASTA parsing, KeyError/IndexError/ValueError, or batches skipping bad records.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Use Python arithmetic and comparison operators to compute GC content, codon/frame math, protein MW, and primer Tm. Use when calculating GC%, codon counts, reading frames, or fixing operator-precedence bugs in bio scripts.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Read/write FASTA, FASTQ, CSV/TSV (BED), JSON, and pickle files in Python using open()/context managers, csv.DictReader/DictWriter, and streaming generators for large genomics files. Use when parsing a FASTA/FASTQ file, writing sequences back out with line wrapping, reading/writing gene expression CSV or BED/TSV files…

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Write Python def functions for bio scripts — ORF finders, reverse-complement, Hamming distance, args/kwargs, @lrucache. Use for a mutable-default-argument bug, args/kwargs signatures, or reusable sequence helpers.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Write Python generators (yield, itertools) for streaming FASTA/FASTQ readers, sliding-window GC/k-mer scans, and lazy translation pipelines that skip loading whole files into memory. Use for large FASTA/FASTQ parsing or MemoryError on genomic data.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Stream FASTA/FASTQ and generate k-mers/codons lazily with Python generators, custom iter/next classes, and itertools. Use when parsing multi-GB sequence files without loading them fully into RAM or chaining filter-trim-translate pipelines.

Pavel-Kravchenko/Bioinformatics

Skill Claude CodeCodex

Split CDS into codons, extract k-mers, sort sequences by GC%/length, and pack gene coordinates into tuples/namedtuples. Use when looping over genes/codons/SNPs/BED intervals, computing sliding-window GC%, or detecting gene overlaps in Python.