Data & Analytics

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

skills in category: 12,629
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Showing 12,121–12,144 of 12,629 skills

Figure ExportAExports publication-ready figures in various formats with proper resolution, sizing, and typography. Use when preparing figures for journal submission, creating vector graphics for presentations, or ensuring consistent figure styling across analyses.datapythonVotes: 0GitHub stars: 32
Enrichment VisualizationAVisualize enrichment results using enrichplot package functions. Use when creating publication-quality figures from clusterProfiler results. Covers dotplot, barplot, cnetplot, emapplot, gseaplot2, ridgeplot, and treeplot.datagonodeVotes: 0GitHub stars: 32
Data AnalysisARun the cross-language data analysis workflows (Python, R, SQL, Tableau/Power BI) described in this module to clean, analyze, and visualize biomedical datasets end-to-end.datapythonsqlVotes: 0GitHub stars: 32
Spectral LibrariesABuild, manage, and search spectral libraries for proteomics. Use when creating or working with spectral libraries for DIA analysis. Covers DDA-based library generation, predicted libraries (Prosit, DeepLC), and library formats.datapythonbashVotes: 0GitHub stars: 32
Ptm AnalysisAPost-translational modification analysis including phosphorylation, acetylation, and ubiquitination. Covers site localization, motif analysis, and quantitative PTM analysis. Use when analyzing phosphoproteomic data or other modification-enriched samples.datapythongoVotes: 0GitHub stars: 32
Peptide IdentificationAPeptide-spectrum matching and protein identification from MS/MS data. Use when identifying peptides from tandem mass spectra. Covers database searching, spectral library matching, and FDR estimation using target-decoy approaches.datapythongoVotes: 0GitHub stars: 32
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WsjCAccess business and financial news from The Wall Street Journal.datagobashVotes: 0GitHub stars: 207
Population StructureAAnalyze population structure using PCA and admixture analysis with PLINK and ADMIXTURE. Identify population clusters, assess ancestry proportions, visualize genetic structure, and choose optimal K for admixture models. Use when analyzing population stratification with PCA or admixture.datapythongoVotes: 0GitHub stars: 32
Linkage DisequilibriumACalculate linkage disequilibrium statistics (r², D'), perform LD pruning for population structure analysis, identify haplotype blocks, and visualize LD patterns using PLINK, scikit-allel, and LDBlockShow. Use when calculating LD or pruning variants.datapythonbashVotes: 0GitHub stars: 32
Association TestingAGenome-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.datapythongoVotes: 0GitHub stars: 32
Modern Tree InferenceABuild maximum likelihood phylogenetic trees using IQ-TREE2 and RAxML-ng. Use when inferring publication-quality trees with model selection, ultrafast bootstrap, or partitioned analyses from sequence alignments.datagobashVotes: 0GitHub stars: 32
Organoid Drug Response AgentAAI-powered analysis of patient-derived organoid (PDO) drug screening for personalized oncology treatment selection and biomarker discovery.datapythonbashVotes: 0GitHub stars: 32
Tumor Fraction EstimationAEstimates circulating tumor DNA fraction from shallow whole-genome sequencing using ichorCNA. Detects copy number alterations via HMM segmentation and calculates ctDNA percentage. Requires 0.1-1x sWGS coverage. Use when quantifying tumor burden from liquid biopsy or monitoring treatment response.datapythonshellVotes: 0GitHub stars: 32
Methylation Based DetectionAAnalyzes cfDNA methylation patterns for cancer detection using cfMeDIP-seq or bisulfite sequencing with MethylDackel. Identifies cancer-specific methylation signatures and performs tissue-of-origin deconvolution. Use when using methylation biomarkers for early cancer detection or minimal residual disease.datapythongoVotes: 0GitHub stars: 32
Longitudinal MonitoringATracks ctDNA dynamics over time for treatment response monitoring using serial liquid biopsy samples. Analyzes tumor fraction trends, mutation clearance kinetics, and defines molecular response criteria. Use when monitoring patients during therapy or detecting molecular relapse before clinical progression.datapythongitVotes: 0GitHub stars: 32
Fragment AnalysisAAnalyzes cfDNA fragment size distributions and fragmentomics features using FinaleToolkit or Griffin. Extracts nucleosome positioning patterns, fragment ratios, and DELFI-style fragmentation profiles for cancer detection. Use when leveraging fragment patterns for tumor detection or tissue-of-origin analysis.datapythonVotes: 0GitHub stars: 32
Cfdna PreprocessingAPreprocesses cell-free DNA sequencing data including adapter trimming, alignment optimized for short fragments, and UMI-aware duplicate removal using fgbio. Applies cfDNA-specific quality thresholds and fragment length filtering. Use when processing plasma cfDNA sequencing data before downstream analysis.datapythongoVotes: 0GitHub stars: 32
Mofa IntegrationAMulti-Omics Factor Analysis (MOFA2) for unsupervised integration of multiple data modalities. Identifies shared and view-specific sources of variation. Use when integrating RNA-seq, proteomics, methylation, or other omics to discover latent factors driving biological variation across modalities.datagoVotes: 0GitHub stars: 32
Mixomics AnalysisASupervised 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.datagoexpressVotes: 0GitHub stars: 32
Data HarmonizationAPreprocessing and harmonization of multi-omics data before integration. Covers normalization, batch correction, feature alignment, and missing value handling across data types. Use when preparing multi-omics datasets for integration analysis.dataexpressapiVotes: 0GitHub stars: 32
Differential AbundanceADifferential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of microbiome data.datagoexpressVotes: 0GitHub stars: 32
Normalization QcAQuality control and normalization for metabolomics data. Covers QC-based correction, batch effect removal, and data transformation methods. Use when correcting technical variation in metabolomics data before statistical analysis.dataexpressVotes: 0GitHub stars: 32
LipidomicsASpecialized lipidomics analysis for lipid identification, quantification, and pathway interpretation. Covers LC-MS lipidomics with LipidSearch, MS-DIAL, and LipidMaps annotation. Use when analyzing lipid classes, chain composition, or lipid-specific pathways.datapythondatabaseVotes: 0GitHub stars: 32
Probability StatisticsABayesian OptimizedatapythongoVotes: 0GitHub stars: 32