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SkillsMP は GPTomics/bioSkills から 562 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
GPTomics/bioSkills収集済み skill 562 件中 40 件を表示しています。
Orchestrates the end-to-end bulk RNA-seq differential-expression pipeline from FASTQ to an annotated DE gene table, chaining fastp QC/trim, Salmon (decoy-aware) or STAR+featureCounts quantification, tximport gene-level collapse, DESeq2/edgeR/limma-voom…
原文の言語: 英語
Orchestrates the end-to-end single-cell RNA-seq pipeline from 10x Cell Ranger output to annotated cell types, chaining ambient-RNA removal, doublet detection, MAD-adaptive QC, normalization, integration, clustering, marker annotation, and (separately)…
原文の言語: 英語
Orchestrates the end-to-end small RNA-seq pipeline from FASTQ to differential miRNAs and expression-filtered targets, chaining kit-aware cutadapt trimming (adapter on every read, UMI/4N handling), miRge3 known+isomiR quantification or miRDeep2 novel…
原文の言語: 英語
Orchestrates the end-to-end spatial transcriptomics pipeline from Space Ranger / vendor output to spatial domains and statistics, branching FIRST on platform class (imaging in-situ Xenium/MERFISH/CosMx vs sequencing/capture Visium/Visium HD/Slide-seq). Use…
原文の言語: 英語
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 +…
原文の言語: 英語
Orchestrates an end-to-end immune-repertoire pipeline from FASTQ to clonotypes, diversity, overlap, somatic hypermutation and lineages, routing on two forks. Use when deciding bulk vs single-cell (bulk amplicon/RNA-seq -> MiXCR analyze preset ->…
原文の言語: 英語
End-to-end bulk time-course analysis from an expression matrix to temporal gene modules and per-cluster pathway enrichment. Orchestrates temporal DE (limma splines or DESeq2 LRT), Mfuzz/tslearn soft clustering of expression-profile shapes, GAM trajectory…
原文の言語: 英語
Classify variant clinical significance with the ACMG/AMP germline framework and its 2018-2025 ClinGen refinements (graded PVS1 decision tree, PM2 downgraded to Supporting, PP5/BP6 retired, calibrated PP3/BP4, Bayesian points), the AMP/ASCO/CAP somatic tiers…
原文の言語: 英語
Generate consensus FASTA sequences by applying VCF variants onto a reference with bcftools consensus, or build viral/amplicon consensus with iVar. Use when reconstructing a sample-specific reference or haplotype, deciding -H haplotype vs IUPAC vs all-ALT…
原文の言語: 英語
Calls germline SNPs and indels with Google DeepVariant, which reframes variant calling as CNN image classification over multi-channel pileup tensors. Covers platform-specific model selection (WGS, WES, PACBIO, ONT_R104, HYBRID_PACBIO_ILLUMINA), one-shot…
原文の言語: 英語
Filters germline and somatic variant callsets at the site and genotype level with GATK VQSR (VQSLOD, truth-sensitivity tranches), VETS/ScoreVariantAnnotations, NVScoreVariants, hard filters with per-annotation thresholds, and bcftools/cyvcf2 expressions, plus…
原文の言語: 英語
Joint genotype a cohort of per-sample gVCFs with GATK (HaplotypeCaller -ERC GVCF -> GenomicsDBImport or CombineGVCFs -> GenotypeGVCFs) or GLnexus for DeepVariant gVCFs, producing a squared-off sample-by-site genotype matrix. Use when deciding between joint…
原文の言語: 英語
Call structural variants (>=50 bp deletions, insertions, inversions, duplications, translocations) from short- or long-read data by reconstructing four orthogonal signals (discordant pairs, split reads via the SA tag, read depth, local assembly). Covers…
原文の言語: 英語
Call germline SNPs and indels from a BAM/CRAM with bcftools mpileup and call, and select the right calling engine for the job. Use when generating a VCF from aligned reads, choosing between bcftools, GATK HaplotypeCaller, DeepVariant, and DRAGEN, setting…
原文の言語: 英語
Left-align and trim indels to parsimonious canonical form, decompose MNPs (atomize), and split multiallelic variants with bcftools norm. Use when comparing variants across callers or cohorts, preparing a VCF for database annotation or ClinVar/dbSNP matching,…
原文の言語: 英語
View, query, and interpret VCF/BCF variant files with bcftools and cyvcf2. Use when inspecting variants, extracting fields with query format strings, converting VCF/BCF, or correctly reading a field -- QUAL (site) vs GQ (genotype) vs PL/GL likelihoods, AD vs…
原文の言語: 英語
Combine, split, sort, intersect, and subset VCF/BCF files with bcftools merge, concat, isec, sort, view, and reheader. Use when merging different samples into a cohort VCF, concatenating per-chromosome or per-region call sets for the same samples,…
原文の言語: 英語
Compute and interpret VCF quality-control metrics (Ti/Tv, het/hom, novel/known, missingness, HWE, contamination, relatedness) with bcftools stats, vcftools, plot-vcfstats, and identity tools (somalier, peddy, KING). Use when judging whether a callset is…
原文の言語: 英語
Discovers a periodic signal of UNKNOWN period in time-series omics data and puts a defensible significance on it, especially when sampling is IRREGULAR (dropped timepoints, pooled harvests) so FFT/Welch/JTK are invalid. Estimates the dominant period with…
原文の言語: 英語
Clusters temporally variable genes by expression-profile SHAPE (not significance) using Mfuzz fuzzy c-means, TCseq, DEGreport degPatterns, and tslearn DTW/soft-DTW. Use when grouping pre-selected time-course genes into shared trajectory programs…
原文の言語: 英語
Infers directed, time-delayed gene regulatory edges from BULK time-series expression using Granger causality (statsmodels VAR F-test), dynGENIE3 (tree ensembles regressing ODE-derived derivatives; Random Forests by default, Extra-Trees optional), and dynamic…
原文の言語: 英語
Models continuous temporal trajectories from BULK or time-resolved omics where the x-axis is measured experimental time: penalized GAMs (mgcv) for smooth trends and changepoint detection (segmented, ruptures) for abrupt regime shifts. Use when deciding…
原文の言語: 英語
Align V(D)J reads and assemble TCR/BCR clonotypes with MiXCR, driven by a chemistry-matched preset. Use when choosing/auditing the preset for a library (5'RACE/template-switch vs multiplex-primer amplicon -> rigid vs floating boundaries; RNA vs gDNA ->…
原文の言語: 英語
Draws TCR/BCR repertoire figures - V-J chord/circos, CDR3 spectratype, clonal-space stratification, clonal tracking across timepoints, rarefaction/extrapolation curves, overlap heatmaps, and clonotype-similarity networks - and encodes how to read them. Use…
原文の言語: 英語
Integrates single-cell paired TCR/BCR (10x VDJ, AIRR, dandelion, BD Rhapsody) with gene expression in an AnnData/MuData object using scirpy - chain-pairing QC, clonotype definition, clonal expansion, diversity, repertoire overlap, V(D)J usage, and VDJdb…
原文の言語: 英語
Maps TCR/BCR receptor sequences toward candidate antigen specificity and clusters repertoires by shared-specificity signal, while enforcing that a database match or a cluster label is a HYPOTHESIS, not a specificity call. Use when deciding among database…
原文の言語: 英語
Computes immune-repertoire diversity, clonal structure, overlap, and segment usage from TCR/BCR clonotype tables with VDJtools (immunarch as the modern R alternative). Use when deciding which diversity estimator answers a question (q=0 observed…
原文の言語: 英語
Authors reproducible Nextflow DSL2 pipelines built on reactive dataflow, where processes communicate only through channels and execution order is not guaranteed. Use when deciding channel/dataflow (Nextflow) vs rule-based (Snakemake) authoring; wiring queue…
原文の言語: 英語
Runs and configures curated nf-core community Nextflow pipelines (rnaseq, sarek, atacseq, methylseq, ampliseq, taxprofiler, fetchngs) reproducibly, pinning the pipeline revision with -r and selecting a container engine and institutional config via -profile.…
原文の言語: 英語
Authors reproducible bioinformatics pipelines with Snakemake - rules wired by output-file pattern, wildcards and expand() for sample fan-out, checkpoints for runtime-unknown outputs, resource/retry escalation, and conda/container software deployment on HPC…
原文の言語: 英語
Authors bioinformatics pipelines in WDL (Workflow Description Language) run by Cromwell or miniwdl, targeting the GATK/Broad and Terra/AnVIL/BioData Catalyst cloud ecosystem, with tasks, workflows, scatter-gather parallelism, structs, and a runtime block that…
原文の言語: 英語
Builds and simulates multi-species metabolic community models from member genome-scale models, using MICOM for abundance-weighted steady-state community FBA and cooperative tradeoff, SMETANA for cross-feeding and competition scoring, and SteadyCom/COMETS for…
原文の言語: 英語
Builds tissue-, cell-type-, and condition-specific metabolic models by integrating transcriptomic or proteomic data into a generic genome-scale model, using extraction algorithms (GIMME, iMAT, INIT/tINIT, MADE, E-Flux, CORDA, FASTCORE) via troppo and corda in…
原文の言語: 英語
Performs flux balance analysis (FBA), flux variability analysis (FVA), parsimonious FBA (pFBA), loopless FBA, flux sampling, and production envelopes on genome-scale metabolic models with COBRApy, solving the biomass-maximization linear program under a…
原文の言語: 英語
Performs in-silico single and double gene deletions, condition-dependent essentiality, and synthetic-lethality screens on genome-scale metabolic models with COBRApy, evaluating gene-protein-reaction rules and comparing FBA re-optimization against MOMA/ROOM…
原文の言語: 英語
Builds draft genome-scale metabolic models from an annotated genome using CarveMe (top-down carving of a BiGG universal model) or gapseq (bottom-up pathway-evidence reconstruction), then loads and sanity-checks the draft in COBRApy. Use when creating a model…
原文の言語: 英語
Validates, gap-fills, and standardizes genome-scale metabolic models using memote for consistency and annotation scoring and COBRApy for manual curation, including mass/charge balance, energy-generating-cycle detection, dead-end resolution, GPR fixes, and…
原文の言語: 英語
Computes metabolic-engineering strain designs on genome-scale models with StrainDesign (OptKnock, RobustKnock, minimal cut sets, OptCouple) and cameo (heuristic knockout and FSEOF over/under-expression targets), finding gene/reaction interventions that couple…
原文の言語: 英語
Assigns isolate identity at the right resolution for the question -- ANI/Mash species triage, 7-locus MLST historical comparability, cgMLST/wgMLST outbreak resolution (chewBBACA, BIGSdb, Ridom SeqSphere, EnteroBase HierCC), in-silico serotyping…
原文の言語: 英語
Estimates time-scaled phylogenies, molecular-clock rates, effective reproduction number R_e, and population dynamics from dated pathogen genomes using TreeTime (maximum-likelihood) and BEAST2 (Bayesian; strict/relaxed clocks; coalescent, Bayesian-Skyline,…
原文の言語: 英語