gptomics/bioskills
160 skills · 533 total installs
$npx skills add gptomics/bioskillsSkillInstalls
bioskillsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-genome-tracksa set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-multipanel-figuresa set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-specialized-omics-plotsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-epitranscriptomics-merip-preprocessinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-metagenomics-krakena set of SKILLS.md for doing bioinformatics with agents like claude codebio-read-qc-fastp-workflowa set of SKILLS.md for doing bioinformatics with agents like claude codebio-single-cell-batch-integrationa set of SKILLS.md for doing bioinformatics with agents like claude codebio-workflows-microbiome-pipelinea set of SKILLS.md for doing bioinformatics with agents like claude codebio-workflows-scrnaseq-pipelinea set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-circos-plotsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-color-palettesa set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-ggplot2-fundamentalsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-heatmaps-clusteringa set of SKILLS.md for doing bioinformatics with agents like claude codebio-de-deseq2-basicsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-de-visualizationa set of SKILLS.md for doing bioinformatics with agents like claude codebio-epitranscriptomics-m6a-differentiala set of SKILLS.md for doing bioinformatics with agents like claude codebio-epitranscriptomics-m6a-peak-callinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-epitranscriptomics-modification-visualizationa set of SKILLS.md for doing bioinformatics with agents like claude codebio-expression-matrix-metadata-joinsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-genome-assembly-contamination-detectiona set of SKILLS.md for doing bioinformatics with agents like claude codebio-genome-intervals-gtf-gff-handlinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-longread-alignmenta set of SKILLS.md for doing bioinformatics with agents like claude codebio-methylation-bismark-alignmenta set of SKILLS.md for doing bioinformatics with agents like claude codebio-microbiome-diversity-analysisa set of SKILLS.md for doing bioinformatics with agents like claude codebio-pathway-enrichment-visualizationa set of SKILLS.md for doing bioinformatics with agents like claude codebio-pathway-go-enrichmenta set of SKILLS.md for doing bioinformatics with agents like claude codebio-pathway-reactomea set of SKILLS.md for doing bioinformatics with agents like claude codebio-reporting-rmarkdown-reportsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-alignment-filteringa set of SKILLS.md for doing bioinformatics with agents like claude codebio-alignment-pairwisea set of SKILLS.md for doing bioinformatics with agents like claude codebio-atac-seq-atac-peak-callinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-atac-seq-footprintinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-batch-processinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-bedgraph-handlinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-chip-seq-super-enhancersa set of SKILLS.md for doing bioinformatics with agents like claude codebio-clinical-databases-dbsnp-queriesa set of SKILLS.md for doing bioinformatics with agents like claude codebio-clinical-databases-variant-prioritizationa set of SKILLS.md for doing bioinformatics with agents like claude codebio-clip-seq-clip-peak-callinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-copy-number-gatk-cnva set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-interactive-visualizationa set of SKILLS.md for doing bioinformatics with agents like claude codebio-de-edger-basicsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-de-resultsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-differential-expression-batch-correctiona set of SKILLS.md for doing bioinformatics with agents like claude codebio-differential-expression-timeseries-dea set of SKILLS.md for doing bioinformatics with agents like claude codebio-entrez-linka set of SKILLS.md for doing bioinformatics with agents like claude codebio-epitranscriptomics-m6anet-analysisa set of SKILLS.md for doing bioinformatics with agents like claude codebio-expression-matrix-counts-ingesta set of SKILLS.md for doing bioinformatics with agents like claude codebio-expression-matrix-gene-id-mappinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-expression-matrix-sparse-handlinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-format-conversiona set of SKILLS.md for doing bioinformatics with agents like claude codebio-gatk-variant-callinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-genome-assembly-scaffoldinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-genome-intervals-bigwig-tracksa set of SKILLS.md for doing bioinformatics with agents like claude codebio-geo-dataa set of SKILLS.md for doing bioinformatics with agents like claude codebio-imaging-mass-cytometry-cell-segmentationa set of SKILLS.md for doing bioinformatics with agents like claude codebio-imaging-mass-cytometry-phenotypinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-long-read-sequencing-clair3-variantsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-longread-qca set of SKILLS.md for doing bioinformatics with agents like claude codebio-metabolomics-statistical-analysisa set of SKILLS.md for doing bioinformatics with agents like claude codebio-metabolomics-xcms-preprocessinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-methylation-callinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-methylation-dmr-detectiona set of SKILLS.md for doing bioinformatics with agents like claude codebio-methylation-methylkita set of SKILLS.md for doing bioinformatics with agents like claude codebio-paired-end-fastqa set of SKILLS.md for doing bioinformatics with agents like claude codebio-pathway-gseaa set of SKILLS.md for doing bioinformatics with agents like claude codebio-pathway-kegg-pathwaysa set of SKILLS.md for doing bioinformatics with agents like claude codebio-pathway-wikipathwaysa set of SKILLS.md for doing bioinformatics with agents like claude codebio-pdb-geometric-analysisa set of SKILLS.md for doing bioinformatics with agents like claude codebio-pdb-structure-ioa set of SKILLS.md for doing bioinformatics with agents like claude codebio-population-genetics-association-testinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-population-genetics-linkage-disequilibriuma set of SKILLS.md for doing bioinformatics with agents like claude codebio-population-genetics-plink-basicsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-population-genetics-population-structurea set of SKILLS.md for doing bioinformatics with agents like claude codebio-population-genetics-scikit-allel-analysisa set of SKILLS.md for doing bioinformatics with agents like claude codebio-population-genetics-selection-statisticsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-proteomics-dia-analysisa set of SKILLS.md for doing bioinformatics with agents like claude codebio-proteomics-proteomics-qca set of SKILLS.md for doing bioinformatics with agents like claude codebio-proteomics-quantificationa set of SKILLS.md for doing bioinformatics with agents like claude codebio-proteomics-spectral-librariesa set of SKILLS.md for doing bioinformatics with agents like claude codebio-read-alignment-bowtie2-alignmenta set of SKILLS.md for doing bioinformatics with agents like claude codebio-read-alignment-bwa-alignmenta set of SKILLS.md for doing bioinformatics with agents like claude codebio-read-alignment-hisat2-alignmenta set of SKILLS.md for doing bioinformatics with agents like claude codebio-read-alignment-star-alignmenta set of SKILLS.md for doing bioinformatics with agents like claude codebio-read-qc-adapter-trimminga set of SKILLS.md for doing bioinformatics with agents like claude codebio-read-qc-contamination-screeninga set of SKILLS.md for doing bioinformatics with agents like claude codebio-read-qc-quality-filteringa set of SKILLS.md for doing bioinformatics with agents like claude codebio-read-qc-quality-reportsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-read-qc-umi-processinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-reporting-figure-exporta set of SKILLS.md for doing bioinformatics with agents like claude codebio-reporting-quarto-reportsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-restriction-enzyme-selectiona set of SKILLS.md for doing bioinformatics with agents like claude codebio-restriction-fragment-analysisa set of SKILLS.md for doing bioinformatics with agents like claude codebio-restriction-mappinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-experimental-design-multiple-testinga set of SKILLS.md for doing bioinformatics with agents like claude codebio-reporting-automated-qc-reportsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-reporting-jupyter-reportsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-genome-browser-tracksa set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-upset-plotsa set of SKILLS.md for doing bioinformatics with agents like claude codebio-data-visualization-volcano-customizationa set of SKILLS.md for doing bioinformatics with agents like claude codeadmet-predictionPredicts ADMET properties using ADMETlab 3.0 (119 platform features, including 77 prediction models with modeled-endpoint uncertainty), ADMET-AI, DeepChem MolNet, and chemprop D-MPNN with explicit hanalignment-amplicon-clippingTrim PCR primers from aligned reads in amplicon-panel BAMs using samtools ampliconclip. Use when processing SARS-CoV-2 ARTIC, hereditary cancer panels, ctDNA hot-spot panels, or any amplicon assay whealignment-filteringFilter 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.alignment-indexingCreate 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.alignment-ioRead, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and other alignment formats for phylogenetics and conservatioalignment-sortingSort alignment files by coordinate or read name using samtools and pysam. Use when preparing BAM files for indexing, variant calling, or paired-end analysis.alignment-trimmingTrim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues balignment-validationValidate 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 callallele-specific-accessibilityDetect allele-specific chromatin accessibility from ATAC-seq using WASP, GATK ASEReadCounter, or RASQUAL. Use when mapping cis-regulatory genetic variants from heterozygous SNPs, separating cis from tatac-peak-callingCall accessible chromatin regions from ATAC-seq BAM files using MACS3, MACS2, Genrich, or HMMRATAC. Use when identifying open chromatin from aligned ATAC-seq, choosing between point-source vs HMM peakatac-qcATAC-seq library quality control -- TSS enrichment, FRiP, fragment-size periodicity, library complexity (NRF/PBC1/PBC2), mitochondrial fraction, and ENCODE 4 thresholds. Use when assessing whether an bam-statisticsGenerate alignment statistics using samtools flagstat, stats, depth, coverage, and mosdepth. Use when assessing alignment quality, calculating coverage, or generating QC reports.bioskills-installerInstalls 425 bioinformatics skills covering sequence analysis, RNA-seq, single-cell, variant calling, metagenomics, structural biology, and 56 more categories. Use when setting up bioinformatics capabco-accessibilityInfer cis-regulatory connections (peak-to-peak co-accessibility) from scATAC-seq using Cicero, ArchR getCoAccessibility, or SCENIC+. Use when linking enhancer accessibility to promoter accessibility, colocalization-analysisTest whether two or more traits share a causal variant at a locus using Bayesian colocalization (coloc.abf, coloc.susie, HyPrColoc, moloc, eCAVIAR, SMR/HEIDI, PWCoCo, SharePro). Use when integrating Gconformer-generationGenerates 3D conformer ensembles using RDKit ETKDGv3 with knowledge-enhanced distance geometry, MMFF94/UFF force-field optimization, CREST + GFN2-xTB semi-empirical refinement, and macrocycle-aware toconsensus-peaksetBuild 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 ccovalent-designDesigns covalent inhibitors and warheads targeting cysteine, lysine, serine, threonine, tyrosine, and aspartate residues, with explicit handling of warhead reactivity (acrylamide, chloroacetamide, vindeep-learning-atacSequence-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 profidifferential-accessibilityIdentify differentially accessible chromatin regions across conditions using DiffBind, csaw, DESeq2, or edgeR. Use when comparing ATAC-seq accessibility between treatment groups, choosing between consdifferential-splicingDetects differential alternative splicing between conditions using rMATS-turbo (binomial LRT on junction counts), leafcutter (Dirichlet-multinomial GLM on intron clusters), MAJIQ V3 deltapsi/HET (Bayeduplicate-handlingMark and remove PCR/optical duplicates using samtools fixmate and markdup. Use when preparing alignments for variant calling or when duplicate reads would bias analysis.effector-gene-prioritizationMaps GWAS-implicated loci to candidate effector (causal) genes by integrating variant-to-gene (V2G) features via Open Targets L2G (Mountjoy 2021), MAGMA gene-based association (de Leeuw 2015), FUMA SNenhancer-gene-linkingPredict enhancer-gene regulatory connections from ATAC-seq using ABC, ENCODE-rE2G, HiChIP, or Cicero. Use when linking distal enhancers to target genes, choosing between contact-aware (ABC, ENCODE-rE2fine-mappingResolves GWAS associations to candidate causal variants and credible sets via SuSiE, susie_rss, FINEMAP, CAVIAR, DAP-G, PAINTOR, PolyFun, SuSiEx, MultiSuSiE, and FOCUS. Use when narrowing a GWAS lead footprintingDetect transcription factor binding footprints in ATAC-seq using TOBIAS, HINT-ATAC, Wellington, or scprinter. Use when identifying bound TF sites within accessible regions, correcting Tn5 insertion bifree-energy-calculationsPerforms alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicgenerative-designDesigns 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 explicigenetic-correlationEstimates bivariate genetic correlation (rg) between traits from GWAS summary statistics or individual-level genotypes using cross-trait LDSC, HDL, LAVA, rho-HESS, GREML-bivariate, Popcorn, and HDL-L.genomic-semFits structural equation models to GWAS summary statistics using GenomicSEM (Grotzinger 2019), including common-factor models, confirmatory factor models, ESEM, common-factor GWAS with Q_SNP heterogenheritability-partitioningEstimates SNP heritability and partitions it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes. Implements LDSC, stratified LDSC with the bisoform-switchingAnalyzes differential transcript usage (DTU) and isoform switches with functional consequence prediction (NMD via 50nt rule, ORF disruption, protein domain loss/gain, signal peptide changes, IDR alterlong-read-splicingAnalyzes alternative splicing from PacBio Iso-Seq (HiFi, Kinnex/MAS-Iso-seq) and Oxford Nanopore (direct cDNA, direct RNA, R10.4.1+) long-read RNA-seq with full-isoform resolution. Tools include FLAIRmediation-analysisDecompose total effects into direct and indirect paths through mediators using mediation, CMAverse 4-way, HIMA/HIMA2 high-dimensional, BAMA, two-step / MVMR mediation, or double-ML medDML. Use when temendelian-randomizationEstimate causal effects of an exposure on an outcome from GWAS summary statistics using genetic instruments. Implements IVW (fixed/random), MR-Egger, weighted median/mode, MR-RAPS, CAUSE, GSMR-HEIDI, ml-docking-rescoringPerforms ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity), Chai-1, AlphaFold3 ligand, EquiBind, TANKBind, Neurmolecular-descriptorsCalculates molecular fingerprints (ECFP/Morgan, FCFP, MACCS, RDKit, AtomPair, TopologicalTorsion, Avalon, MAP4, MHFP6) and physicochemical descriptors (Lipinski, QED, TPSA, Crippen LogP, 3D shape) witmolecular-ioReads, writes, and converts molecular file formats (SMILES, InChI, SDF V2000/V3000, MOL2, PDB, and BinaryCIF) using RDKit and Open Babel with rigorous handling of aromaticity perception, stereochemistmolecular-standardizationStandardizes molecular structures using the ChEMBL structure pipeline for normalization and parent selection plus RDKit rdMolStandardize for explicit custom steps such as tautomer canonicalization, samotif-deviationAnalyze TF motif accessibility variability across samples or single cells using chromVAR. Use when identifying TF motifs whose accessibility correlates with conditions, computing per-sample motif z-scmsa-parsingParse and analyze multiple sequence alignments using Biopython. Extract sequences, identify conserved regions, analyze gaps, work with annotations, and manipulate alignment data for downstream analysimsa-statisticsCalculate alignment statistics including sequence identity, conservation scores, substitution matrices, and similarity metrics. Use when comparing alignment quality, measuring sequence divergence, andmultiple-alignmentPerform multiple sequence alignment using MAFFT, MUSCLE5, ClustalOmega, or T-Coffee. Guides tool and algorithm selection based on dataset size, sequence divergence, and downstream application. Use whenucleosome-positioningMap nucleosome center positions, occupancy, and fuzziness from ATAC-seq fragment-size patterns using NucleoATAC, ATACseqQC, DANPOS3, or scprinter. Use when characterizing nucleosome organization at proutlier-splicing-detectionDetects aberrant splicing in single rare-disease patients vs a control panel using FRASER 2.0 (Bioconductor; Beta-binomial autoencoder on Intron Jaccard Index, default delta cutoff 0.1, q hyperparametpairwise-alignmentPerform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner. Use when comparing two sequences, finding optimal alignments, scoring similarity, and identifying local or global matchespharmacophore-modelingBuilds and applies 3D pharmacophore models using RDKit Pharm3D, the apo2ph4 receptor-based workflow (Heider et al. 2023), Pharmer / Pharmit for search, and PharmacoForge for protein-pocket-conditionedpileup-generationGenerate pileup data for variant calling using samtools mpileup and pysam. Use when preparing data for variant calling, analyzing per-position read data, or calculating allele frequencies.pleiotropy-detectionDetect and adjust for horizontal pleiotropy in two-sample Mendelian randomization by distinguishing uncorrelated (UHP) from correlated (CHP) pleiotropy and choosing among Egger, MR-PRESSO, MR-RAPS, CAproteome-mr-drug-targetRuns cis-pQTL Mendelian randomization for drug-target validation using UKB-PPP (Olink), deCODE (SomaScan), Fenland, INTERVAL, ARIC, and FinnGen-PPP proteomes plus colocalization triangulation, phenomereference-operationsGenerate consensus sequences and manage reference files using samtools. Use when creating consensus from alignments, indexing references, or creating sequence dictionaries.sam-bam-basicsView, convert, and understand SAM/BAM/CRAM alignment files using samtools and pysam. Use when inspecting alignments, converting between formats, or understanding alignment file structure.sashimi-plotsCreates sashimi-style plots showing RNA-seq read coverage and splice junction counts using ggsashimi (general-purpose, condition-grouped overlays), rmats2sashimiplot (rMATS-output-aware), MAJIQ-VOILA single-cell-atacProcess and analyze single-cell ATAC-seq data with Signac, ArchR, SnapATAC2, or Cell Ranger ATAC. Use when handling 10X scATAC or 10X Multiome (paired RNA+ATAC) data, performing per-cell QC, choosing single-cell-splicingAnalyzes alternative splicing at single-cell resolution. The first decision is library chemistry — 10X 3' is fundamentally limited (RT primes from poly-A, R2 falls in 3' UTR, <0.1 junction read per cesplice-variant-predictionPredicts whether a DNA variant alters mRNA splicing using sequence-based deep-learning tools — SpliceAI (10kb context dilated CNN, clinical default), Pangolin (multi-tissue), MMSplice (modular per-regsplicing-qcAssesses RNA-seq data quality specifically for alternative splicing analysis. QC layers include experimental design audit (library prep, read length, depth, replicates), STAR 2-pass cohort-style alignsplicing-quantificationQuantifies alternative splicing as PSI (percent spliced in) from RNA-seq using rMATS-turbo (BAM-based event), SUPPA2 (TPM-based event), MAJIQ V3 (LSV-based Bayesian), leafcutter (annotation-free introstructural-alignmentAlign protein structures using Foldseek 3Di, TM-align, US-align, DALI, or Foldmason for structural MSA. Predict, score, and superpose backbone coordinates when sequence identity is below the twilight transcriptome-wide-associationPerforms gene-level association from GWAS summary statistics via genetically predicted tissue expression using FUSION, PrediXcan, S-PrediXcan, S-MultiXcan, UTMOST, MOSTWAS, kTWAS, EpiXcan, TIGAR-V2, a