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gptomics/bioskills

59 skills

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$npx skills add gptomics/bioskills
SkillInstalls
admet-predictionPredicts ADMET properties using ADMETlab 3.0 (119 platform features, including 77 prediction models with modeled-endpoint uncertainty), ADMET-AI, DeepChem…—alignment-amplicon-clippingTrim PCR primers from aligned reads in amplicon-panel BAMs using samtools ampliconclip.—alignment-filteringFilter alignments by flags, mapping quality, and regions using samtools view and pysam.—alignment-indexingCreate and use BAI/CSI indices for BAM/CRAM files using samtools and pysam.—alignment-ioRead, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO.—alignment-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.—alignment-validationValidate alignment quality with insert size distribution, proper pairing rates, GC bias, strand balance, and other post-alignment metrics.—allele-specific-accessibilityDetect allele-specific chromatin accessibility from ATAC-seq using WASP, GATK ASEReadCounter, or RASQUAL.—atac-peak-callingCall accessible chromatin regions from ATAC-seq BAM files using MACS3, MACS2, Genrich, or HMMRATAC.—atac-qcATAC-seq library quality control -- TSS enrichment, FRiP, fragment-size periodicity, library complexity (NRF/PBC1/PBC2), mitochondrial fraction, and ENCODE 4…—bam-statisticsGenerate alignment statistics using samtools flagstat, stats, depth, coverage, and mosdepth.—bioskills-installerInstalls 425 bioinformatics skills covering sequence analysis, RNA-seq, single-cell, variant calling, metagenomics, structural biology, and 56 more categories.—co-accessibilityInfer cis-regulatory connections (peak-to-peak co-accessibility) from scATAC-seq using Cicero, ArchR getCoAccessibility, or SCENIC+.—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,…—conformer-generationGenerates 3D conformer ensembles using RDKit ETKDGv3 with knowledge-enhanced distance geometry, MMFF94/UFF force-field optimization, CREST + GFN2-xTB…—consensus-peaksetBuild a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative overlap removal, fixed-width re-centering, and majority-rule…—covalent-designDesigns covalent inhibitors and warheads targeting cysteine, lysine, serine, threonine, tyrosine, and aspartate residues, with explicit handling of warhead…—deep-learning-atacSequence-based deep learning for ATAC-seq using chromBPNet, BPNet, scBasset, or Enformer.—differential-accessibilityIdentify differentially accessible chromatin regions across conditions using DiffBind, csaw, DESeq2, or edgeR.—differential-splicingDetects differential alternative splicing between conditions using rMATS-turbo (binomial LRT on junction counts), leafcutter (Dirichlet-multinomial GLM on…—duplicate-handlingMark and remove PCR/optical duplicates using samtools fixmate and markdup.—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…—enhancer-gene-linkingPredict enhancer-gene regulatory connections from ATAC-seq using ABC, ENCODE-rE2G, HiChIP, or Cicero.—fine-mappingResolves GWAS associations to candidate causal variants and credible sets via SuSiE, susie_rss, FINEMAP, CAVIAR, DAP-G, PAINTOR, PolyFun, SuSiEx, MultiSuSiE,…—footprintingDetect transcription factor binding footprints in ATAC-seq using TOBIAS, HINT-ATAC, Wellington, or scprinter.—free-energy-calculationsPerforms alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+,…—generative-designDesigns novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators…—genetic-correlationEstimates bivariate genetic correlation (rg) between traits from GWAS summary statistics or individual-level genotypes using cross-trait LDSC, HDL, LAVA,…—genomic-semFits structural equation models to GWAS summary statistics using GenomicSEM (Grotzinger 2019), including common-factor models, confirmatory factor models,…—heritability-partitioningEstimates SNP heritability and partitions it across functional annotations, cell types, and loci from GWAS summary statistics or individual-level genotypes.—isoform-switchingAnalyzes differential transcript usage (DTU) and isoform switches with functional consequence prediction (NMD via 50nt rule, ORF disruption, protein domain…—long-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…—mediation-analysisDecompose total effects into direct and indirect paths through mediators using mediation, CMAverse 4-way, HIMA/HIMA2 high-dimensional, BAMA, two-step / MVMR…—mendelian-randomizationEstimate causal effects of an exposure on an outcome from GWAS summary statistics using genetic instruments.—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,…—molecular-descriptorsCalculates molecular fingerprints (ECFP/Morgan, FCFP, MACCS, RDKit, AtomPair, TopologicalTorsion, Avalon, MAP4, MHFP6) and physicochemical descriptors…—molecular-ioReads, writes, and converts molecular file formats (SMILES, InChI, SDF V2000/V3000, MOL2, PDB, and BinaryCIF) using RDKit and Open Babel with rigorous handling…—molecular-standardizationStandardizes molecular structures using the ChEMBL structure pipeline for normalization and parent selection plus RDKit rdMolStandardize for explicit custom…—motif-deviationAnalyze TF motif accessibility variability across samples or single cells using chromVAR.—msa-parsingParse and analyze multiple sequence alignments using Biopython.—msa-statisticsCalculate alignment statistics including sequence identity, conservation scores, substitution matrices, and similarity metrics.—multiple-alignmentPerform multiple sequence alignment using MAFFT, MUSCLE5, ClustalOmega, or T-Coffee.—nucleosome-positioningMap nucleosome center positions, occupancy, and fuzziness from ATAC-seq fragment-size patterns using NucleoATAC, ATACseqQC, DANPOS3, or scprinter.—outlier-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,…—pairwise-alignmentPerform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner.—pileup-generationGenerate pileup data for variant calling using samtools mpileup and pysam.—pleiotropy-detectionDetect and adjust for horizontal pleiotropy in two-sample Mendelian randomization by distinguishing uncorrelated (UHP) from correlated (CHP) pleiotropy and…—proteome-mr-drug-targetRuns cis-pQTL Mendelian randomization for drug-target validation using UKB-PPP (Olink), deCODE (SomaScan), Fenland, INTERVAL, ARIC, and FinnGen-PPP proteomes…—reference-operationsGenerate consensus sequences and manage reference files using samtools.—sam-bam-basicsView, convert, and understand SAM/BAM/CRAM alignment files using samtools and pysam.—sashimi-plotsCreates sashimi-style plots showing RNA-seq read coverage and splice junction counts using ggsashimi (general-purpose, condition-grouped overlays),…—single-cell-atacProcess and analyze single-cell ATAC-seq data with Signac, ArchR, SnapATAC2, or Cell Ranger ATAC.—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…—splice-variant-predictionPredicts whether a DNA variant alters mRNA splicing using sequence-based deep-learning tools — SpliceAI (10kb context dilated CNN, clinical default), Pangolin…—splicing-qcAssesses RNA-seq data quality specifically for alternative splicing analysis.—splicing-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…—structural-alignmentAlign protein structures using Foldseek 3Di, TM-align, US-align, DALI, or Foldmason for structural MSA.—transcriptome-wide-associationPerforms gene-level association from GWAS summary statistics via genetically predicted tissue expression using FUSION, PrediXcan, S-PrediXcan, S-MultiXcan,…—