Data & Analytics

Data analysis, BI, visualization, datasets, statistics, and ML workflows

skills in category: 12,629
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Showing 12,097–12,120 of 12,629 skills

Bioinformatics SinglecellA--> --- name: bio-bioinformatics-singlecell description: Single-cell and multi-omic analysis for hematology, oncology, and translational biology. Use when working with scRNA-seq, CITE-seq, scATAC-seq, multiome, trajectory analysis, batch correction, cell typing, differential expression, or publication-ready figures in Scanpy, scvi-tools, Seurat, or MuData workflows. tool_type: mixed primary_tool: Unknown measurable_outcome: Execute skill workflow successfully with valid output within 15 minut...datagoshellVotes: 0GitHub stars: 32
Splicing PipelineAEnd-to-end alternative splicing analysis from FASTQ to differential splicing results. Aligns with STAR 2-pass mode, performs junction QC, runs rMATS-turbo for differential analysis, and generates sashimi visualizations. Use when performing comprehensive splicing analysis from raw RNA-seq data.datapythonbashVotes: 0GitHub stars: 32
Proteomics PipelineAEnd-to-end proteomics workflow from MaxQuant output to differential protein abundance. Orchestrates data import, normalization, imputation, and statistical testing with MSstats or limma. Use when processing mass spectrometry proteomics.datatestingperformanceVotes: 0GitHub stars: 32
Outbreak PipelineAEnd-to-end outbreak investigation from pathogen isolates to transmission networks. Orchestrates MLST typing, AMR surveillance, phylodynamic dating, and transmission inference with TransPhylo. Use when investigating disease outbreaks or tracking pathogen transmission chains.datapythongoVotes: 0GitHub stars: 32
Metagenomics PipelineAEnd-to-end metagenomics workflow from FASTQ to taxonomic and functional profiles. Covers Kraken2 classification, Bracken abundance estimation, and HUMAnN functional profiling. Use when profiling metagenomic samples.datapythonbashVotes: 0GitHub stars: 32
Metabolomics PipelineAEnd-to-end metabolomics workflow from raw MS data to pathway analysis. Orchestrates XCMS preprocessing, annotation, normalization, statistical analysis, and pathway mapping. Use when processing LC-MS metabolomics data.datatestingdatabaseVotes: 0GitHub stars: 32
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Metabolic Modeling PipelineAEnd-to-end genome-scale metabolic modeling from genome sequence to flux predictions. Covers automated reconstruction with CarveMe, model validation with memote, FBA/FVA analysis, and gene essentiality prediction. Use when building metabolic models or predicting metabolic phenotypes from genomic data.datapythonbashVotes: 0GitHub stars: 32
Imc PipelineAEnd-to-end imaging mass cytometry workflow from raw acquisitions to spatial cell analysis. Orchestrates image preprocessing, segmentation, phenotyping, and spatial statistics. Use when analyzing imaging mass cytometry data end-to-end.datapythonbashVotes: 0GitHub stars: 32
Chipseq PipelineAEnd-to-end ChIP-seq workflow from FASTQ files to annotated peaks. Covers QC, alignment, peak calling with MACS3, and peak annotation with ChIPseeker. Use when processing ChIP-seq data from alignment through peak annotation.datagobashVotes: 0GitHub stars: 32
Mirge3 AnalysisAFast miRNA quantification with isomiR detection and A-to-I editing analysis using miRge3. Use when quantifying known miRNAs quickly or analyzing isomiR variants and RNA editing.datapythonbashVotes: 0GitHub stars: 32
Tximport WorkflowAImport transcript-level quantifications from Salmon/kallisto into R for gene-level analysis with DESeq2/edgeR using tximport or tximeta. Use when importing transcript counts into R for DESeq2/edgeR.dataexpressapiVotes: 0GitHub stars: 32
Translation EfficiencyACalculate translation efficiency (TE) as the ratio of ribosome occupancy to mRNA abundance. Use when comparing translational regulation between conditions or identifying genes with altered translation independent of transcription.datapythonexpressVotes: 0GitHub stars: 32
Sparse HandlingAWork with sparse matrices for memory-efficient storage of count data. Use when dealing with single-cell data or large bulk RNA-seq datasets where most values are zero.datapythonexpressVotes: 0GitHub stars: 32
Metadata JoinsAMerge sample metadata with count matrices and add gene annotations. Use when preparing data for differential expression analysis or visualization.datapythonexpressVotes: 0GitHub stars: 32
Gene Id MappingAConvert between gene identifier systems including Ensembl, Entrez, HGNC symbols, and UniProt. Use when mapping IDs for pathway analysis or matching different data sources.datapythongoVotes: 0GitHub stars: 32
Counts IngestALoad gene expression count matrices from various formats including CSV, TSV, featureCounts, Salmon, kallisto, and 10X. Use when importing quantification results for downstream analysis.datapythonexpressVotes: 0GitHub stars: 32
Flux Balance AnalysisAPerform flux balance analysis (FBA) and flux variability analysis (FVA) on genome-scale metabolic models using COBRApy. Predict growth rates, metabolic fluxes, and optimal resource utilization. Use when predicting metabolic phenotypes or optimizing flux distributions.datapythonreactVotes: 0GitHub stars: 32
Context Specific ModelsABuild tissue and condition-specific metabolic models using GIMME, iMAT, and INIT algorithms with expression data constraints. Create models that reflect cell-type specific metabolism. Use when building tissue-specific metabolic models or integrating transcriptomics with FBA.datapythongoVotes: 0GitHub stars: 32
Modern Structure PredictionAPredict protein structures using modern ML models including AlphaFold3, ESMFold, Chai-1, and Boltz-1. Use when predicting structures for novel proteins, protein complexes, or when comparing predictions across multiple methods.datapythonbashVotes: 0GitHub stars: 32
Geometric AnalysisAPerform geometric calculations on protein structures using Biopython Bio.PDB. Use when measuring distances, angles, and dihedrals, superimposing structures, calculating RMSD, or computing solvent accessible surface area (SASA).datapythongoVotes: 0GitHub stars: 32
Alphafold PredictionsAAccess and analyze AlphaFold protein structure predictions. Use when predicted structures are needed for proteins without experimental structures, or for confidence scores (pLDDT).datapythongoVotes: 0GitHub stars: 32
Python Pandas Best PracticesAStandards for efficient, readable, and performant data manipulation using Python''s Pandas library.datapythongoVotes: 0GitHub stars: 32
Restriction SitesAFind restriction enzyme cut sites in DNA sequences using Biopython Bio.Restriction. Search with single enzymes, batches of enzymes, or commercially available enzyme sets. Returns cut positions for linear or circular DNA. Use when finding restriction enzyme cut sites in sequences.datapythondatabaseVotes: 0GitHub stars: 32
Restriction MappingACreate restriction maps showing enzyme cut positions on DNA sequences using Biopython Bio.Restriction. Visualize cut sites, calculate distances between sites, and generate text or graphical maps. Use when creating or analyzing restriction maps.datapythonVotes: 0GitHub stars: 32