mobile
473
liquid-glass-developer
Context-aware routing to iOS 26 Liquid Glass implementation patterns. Use when working with glass effects, GlassEffectContainer, morphing transitions, or iOS 26 visual effects.
anyproto
development
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knowledge-base
473
claudemd-maintainer
Context-aware guidance for maintaining and improving CLAUDE.md files. Use when editing CLAUDE.md, discussing documentation structure for AI assistants, or optimizing project instructions.
anyproto
documentation
code-quality
473
self-review
Agent self-reviews its own diff against TASTE_INVARIANTS.md before presenting to user. Catches mechanical violations early.
anyproto
testing-security
data-analysis
471
bio-clinical-biostatistics-categorical-tests
Tests associations between categorical variables in clinical data using chi-square, Fisher's exact, and Cochran-Mantel-Haenszel tests. Computes effect sizes and post-hoc pairwise comparisons. Use when analyzing categorical outcomes or testing treatment-outcome independence in clinical trials.
GPTomics
data-ai
scientific-computing
471
bio-machine-learning-prediction-explanation
Explains machine learning predictions on omics data using SHAP values and LIME for feature attribution. Identifies which genes or features drive classifier decisions. Use when interpreting biomarker classifiers or understanding model predictions.
GPTomics
research
bioinformatics
471
bio-population-genetics-association-testing
Genome-wide association studies (GWAS) with PLINK. Perform case-control and quantitative trait association testing using logistic/linear regression with covariates, generate Manhattan and QQ plots for result visualization. Use when running GWAS or association tests.
GPTomics
research
data-engineering
471
bio-clinical-biostatistics-cdisc-data
Reads and prepares CDISC SDTM clinical trial data for analysis. Handles domain tables (DM, AE, EX, VS, LB), USUBJID-based joins, event-to-subject aggregation, and SUPPQUAL pivoting. Use when working with clinical trial datasets in CDISC/SDTM format or .xpt files.
GPTomics
data-ai
cicd
471
bio-workflow-management-nextflow-pipelines
Create scalable, containerized bioinformatics pipelines with Nextflow DSL2 supporting Docker, Singularity, and cloud execution. Use when building portable pipelines with container support, running workflows on cloud platforms (AWS, Google Cloud), or leveraging nf-core community pipelines.
GPTomics
devops
scientific-computing
471
bio-copy-number-cnvkit-analysis
Detect copy number variants from targeted/exome sequencing using CNVkit. Supports tumor-normal pairs, tumor-only, and germline CNV calling. Use when detecting CNVs from WES or targeted panel sequencing data.
GPTomics
research
bioinformatics
471
bio-gene-regulatory-networks-multiomics-grn
Build enhancer-driven gene regulatory networks by integrating single-cell RNA-seq and ATAC-seq data using SCENIC+ to identify eRegulons linking transcription factors to enhancers and target genes. Use when analyzing 10x multiome or paired scRNA+scATAC data to infer cis-regulatory GRNs.
GPTomics
research
bioinformatics
471
bio-multi-omics-mixomics-analysis
Supervised and unsupervised multi-omics integration with mixOmics. Includes sPLS for pairwise integration and DIABLO for multi-block discriminant analysis. Use when performing supervised multi-omics integration or identifying features that discriminate between groups.
GPTomics
research
bioinformatics
471
bio-genome-annotation-eukaryotic-gene-prediction
Predict protein-coding genes in eukaryotic genomes using BRAKER3 for combined RNA-seq and protein evidence, or GALBA for protein-only evidence. Runs Augustus with trained parameters for accurate gene models. Use when annotating a newly assembled eukaryotic genome or improving existing gene predictions.
GPTomics
research
bioinformatics
471
bio-spatial-transcriptomics-spatial-domains
Identify spatial domains and tissue regions in spatial transcriptomics data using Squidpy and Scanpy. Cluster spots considering both expression and spatial context to define anatomical regions. Use when identifying tissue domains or spatial regions.
GPTomics
research
bioinformatics
471
bio-metagenomics-functional-profiling
Profile functional potential of metagenomes using HUMAnN3 and similar tools. Use when obtaining pathway abundances, gene family counts, or functional annotations from metagenomic data.
GPTomics
research
computational-chemistry
471
bio-rna-structure-secondary-structure-prediction
Predicts RNA secondary structures using minimum free energy folding and partition function analysis with ViennaRNA (RNAfold, RNAalifold, RNAcofold). Computes base-pair probabilities, centroid structures, and consensus structures from alignments. Use when predicting RNA folding, evaluating structural stability, or comparing structures across homologs.
GPTomics
research
computational-chemistry
471
bio-rna-structure-ncrna-search
Searches for non-coding RNA homologs and classifies RNA families using Infernal covariance model searches against the Rfam database. Identifies structured RNAs by sequence and secondary structure conservation. Use when querying sequences against Rfam, building custom covariance models for novel RNA families, or classifying non-coding transcripts by family.
GPTomics
research
bioinformatics
471
bio-epidemiological-genomics-pathogen-typing
Perform multi-locus sequence typing (MLST), core genome MLST, and SNP-based strain typing for bacterial isolate characterization using mlst and chewBBACA. Use when identifying strain types, tracking outbreak clones, or characterizing bacterial isolates.
GPTomics
research
bioinformatics
471
bio-epidemiological-genomics-transmission-inference
Infer pathogen transmission networks and identify likely transmission pairs using TransPhylo and outbreak reconstruction algorithms. Estimate who-infected-whom from genomic and epidemiological data. Use when investigating outbreak transmission chains or identifying superspreaders.
GPTomics
research
bioinformatics
471
bio-paired-end-fastq
Handle paired-end FASTQ files (R1/R2) using Biopython. Use when working with Illumina paired reads, synchronizing pairs, interleaving/deinterleaving, or filtering paired data.
GPTomics
research
bioinformatics
471
bio-causal-genomics-colocalization-analysis
Test whether two traits share a causal variant at a genomic locus using Bayesian colocalization with coloc. Computes posterior probabilities for shared vs distinct causal variants between GWAS and eQTL signals. Use when determining if a GWAS signal and an eQTL share the same causal variant.
GPTomics
research