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Programmatically query public single-cell study metadata from the Broad Institute Single Cell Portal REST API when you need to search and filter datasets by organism, tissue, disease, or cell type without an API key.
Use when identifying stable sample subtypes from bulk expression matrices with ConsensusClusterPlus, including PAC-based model selection and consensus matrix/CDF visualization. NOT for: differential expression analysis, single-cell clustering workflows, or non-expression tables.
Use when filtering genes with high missingness and then imputing missing values in a bulk expression matrix with group-aware KNN through DMwR2, where donor samples are restricted by one annotation column before imputation. For strata with 10 or fewer samples, the script falls back to row-wise dir...
Use Bio.Entrez to access NCBI databases (e.g., PubMed/GenBank) for searching, fetching summaries, and downloading records when your workflow needs to call the NCBI E-utilities API over the network.
Search, retrieve metadata, and download PDFs for bioRxiv preprints; use when you need to discover biology preprints by keywords/authors/date ranges and programmatically fetch their details.
Use this skill to run GSVA or ssGSEA pathway-level differential analysis from a bulk expression matrix and a sample group file, then generate a heatmap from the saved GSVA result object. Trigger keywords: GSVA, ssGSEA, pathway enrichment, KEGG pathway analysis, MSigDB. NOT for: gene-level differe...
Access the European Nucleotide Archive (ENA) via REST APIs and FTP/Aspera to search and retrieve sequences, raw reads (FASTQ), assemblies, and metadata when you have accession IDs or need metadata-driven discovery for genomics pipelines.
Generate R/Python code for volcano plots from DEG (Differentially Expressed Genes) analysis results. Triggered when user needs visualization of gene expression data, p-value vs fold-change scatter plots, publication-ready figures for bioinformatics analysis.
Access Ensembl REST API for vertebrate genomic data; use when you need gene/ID lookups, sequence retrieval, variant effect prediction (VEP), or homology/assembly coordinate mapping.
Unified CLI/Python interface for querying genomic, proteomic, structure, and expression data across 20+ bioinformatics databases; use when you need fast, scriptable retrieval by gene/protein IDs or keywords.
Query the NHGRI-EBI GWAS Catalog to retrieve SNP–trait associations, study metadata, and (when available) summary statistics when you need evidence for a variant, trait/disease, gene, or genomic region.
Query the NCBI Gene database via E-utilities and the NCBI Datasets API; use it when you need to search genes by symbol/ID and retrieve annotations (RefSeq, GO, location, phenotype) for single or batch gene lists.
Use when running prognostic survival analysis on a clinical cohort with time-to-event data to estimate univariate and multivariable Cox proportional hazards models, export result tables, and generate forest plots. NOT for: nomogram construction, calibration curves, time-dependent ROC analysis, or...
Access JASPAR database for transcription factor binding profiles (matrices), collections, and species via REST API. Use when user wants to search for transcription factors, retrieve matrix details (PFM/PWM), infer profiles from protein sequences, or explore JASPAR collections.
Access the STRING database to map identifiers, retrieve protein–protein interaction networks, and run functional/PPI enrichment when you need interaction context for a gene/protein set.
Advanced Biopython modules for motifs, population genetics, sequence utilities, restriction analysis, clustering, and GenomeDiagram visualization; use when you need extended bioinformatics analysis beyond basic sequence I/O and alignment.
Sequence alignment and alignment file processing with Biopython (Bio.Align/Bio.AlignIO), triggered when you need global/local pairwise alignment, MSA read/write/format conversion, or alignment statistics/filtering.
Constraint-based reconstruction and analysis (COBRA) for metabolic models; use when you need to simulate growth/production, analyze flux ranges, or run knockout and medium studies from SBML/JSON/YAML models.
Parse Flow Cytometry Standard (FCS) files v2.0–3.1 and extract events/metadata for preprocessing workflows (e.g., when you need NumPy arrays, channel info, or CSV/DataFrame export from cytometry files).
ETE (Environment for Tree Exploration) toolkit for phylogenetic and hierarchical tree analysis; use it when you need to parse/manipulate Newick/NHX trees, detect duplication/speciation events, integrate NCBI taxonomy, and render publication-quality figures.
A high-performance Rust toolkit (with Python bindings and a CLI) for genomic interval analysis; use it when you need fast overlap queries, coverage track generation, genomic tokenization for ML, reference sequence verification, or fragment processing.
Use when analyzing transcription factor (TF) regulatory networks using Dorothea database. Input gene list, identify regulating transcription factors, generate TF-Target network visualization. For: transcription factor enrichment analysis, gene regulatory network research.
Use when performing GO and KEGG enrichment on a gene list from bulk RNA-seq or microarray studies, then generating a combined GO/KEGG dot chart. NOT for single-cell RNA-seq, methylation data, or non-expression data.
Generate leave-one-out sensitivity analysis plots for meta-analysis. Input is a CSV file containing meta-analysis data; outputs are a sensitivity forest plot (PNG) and a sensitivity data table (CSV) showing pooled effect estimates after excluding each study in turn.
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