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Data analysis, BI, visualization, datasets, statistics, and ML workflows
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Showing 1,393–1,416 of 12,625 skills
- Bio Flow Cytometry Cytometry QcComprehensive quality control for flow cytometry and CyTOF data. Covers flow rate stability, signal drift, margin events, dead cell exclusion, and batch QC. Use when assessing acquisition quality or identifying problematic samples before analysis.Votes: 0GitHub stars: 2
- Bio Flow Cytometry Compensation TransformationSpillover compensation and data transformation for flow cytometry. Covers compensation matrix calculation, application, and biexponential/arcsinh transforms. Use when correcting spectral overlap between fluorophores or transforming data for analysis.Votes: 0GitHub stars: 2
- Bio Flow Cytometry Bead NormalizationBead-based normalization for CyTOF and high-parameter flow cytometry. Covers EQ bead normalization, signal drift correction, and batch normalization. Use when correcting instrument drift in CyTOF or harmonizing data across batches.Votes: 0GitHub stars: 2
- Bio Expression Matrix Gene Id MappingConvert between gene identifier systems including Ensembl, Entrez, HGNC symbols, and UniProt. Use when you need to map IDs for pathway analysis or to match different data sources.Votes: 0GitHub stars: 2
- Bio Epitranscriptomics M6anet AnalysisDetect m6A modifications from Oxford Nanopore direct RNA sequencing using m6Anet. Use when analyzing epitranscriptomic modifications from long-read RNA data without immunoprecipitation.Votes: 0GitHub stars: 2
- Bio Differential Expression Batch CorrectionRemove batch effects from RNA-seq data using ComBat, ComBat-Seq, limma removeBatchEffect, and SVA for unknown batch variables. Use when correcting batch effects in expression data.Votes: 0GitHub stars: 2
- Bio De ResultsExtract, filter, annotate, and export differential expression results from DESeq2 or edgeR. Use for identifying significant genes, applying multiple testing corrections, adding gene annotations, and preparing results for downstream analysis. Use when filtering and exporting DE analysis results.Votes: 0GitHub stars: 2
- Bio De Edger BasicsPerform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the quasi-likelihood F-test framework, creating DGEList objects, normalization, dispersion estimation, and statistical testing. Use when performing DE analysis with edgeR.Votes: 0GitHub stars: 2
- Bio De Deseq2 BasicsPerform differential expression analysis using DESeq2 in R/Bioconductor. Use for analyzing RNA-seq count data, creating DESeqDataSet objects, running the DESeq workflow, and extracting results with log fold change shrinkage. Use when performing DE analysis with DESeq2.Votes: 0GitHub stars: 2
- Bio Data Visualization Genome TracksCreate genome browser-style visualizations showing multiple data tracks (coverage, peaks, genes) using pyGenomeTracks, Gviz, and IGV. Use when visualizing genomic data at specific loci with multiple aligned tracks.Votes: 0GitHub stars: 2
- Bio Data Visualization Circos PlotsCreate circular genome visualizations with Circos and pyCircos. Display multi-track data including ideograms, genes, variants, CNVs, and interaction arcs. Use when creating circular genome visualizations.Votes: 0GitHub stars: 2
- Bio Crispr Screens Screen QcQuality control for pooled CRISPR screens. Covers library representation, read distribution, replicate correlation, and essential gene recovery. Use when assessing screen quality before hit calling or diagnosing poor screen performance.Votes: 0GitHub stars: 2
- Bio Crispr Screens Mageck AnalysisMAGeCK (Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout) for pooled CRISPR screen analysis. Covers count normalization, gene ranking, and pathway analysis. Use when identifying essential genes, drug targets, or resistance mechanisms from dropout or enrichment screens.Votes: 0GitHub stars: 2
- Bio Crispr Screens Jacks AnalysisJACKS (Joint Analysis of CRISPR/Cas9 Knockout Screens) for modeling sgRNA efficacy and gene essentiality. Use when analyzing multiple CRISPR screens simultaneously or when accounting for variable sgRNA efficiency across experiments.Votes: 0GitHub stars: 2
- Bio Crispr Screens Hit CallingStatistical methods for calling hits in CRISPR screens. Covers MAGeCK, BAGEL2, drugZ, and custom approaches for identifying essential and resistance genes. Use when identifying significant genes from screen count data after QC passes.Votes: 0GitHub stars: 2
- Bio Crispr Screens Crispresso EditingCRISPResso2 for analyzing CRISPR gene editing outcomes. Quantifies indels, HDR efficiency, and generates comprehensive editing reports. Use when analyzing amplicon sequencing data from CRISPR editing experiments to assess editing efficiency.Votes: 0GitHub stars: 2
- Bio Crispr Library DesignCRISPR library design for genetic screens. Covers sgRNA selection, library composition, control design, and oligo ordering. Use when designing custom sgRNA libraries for knockout, activation, or interference screens.Votes: 0GitHub stars: 2
- Bio Copy Number Gatk CnvCall copy number variants using GATK best practices workflow. Supports both somatic (tumor-normal) and germline CNV detection from WGS or WES data. Use when following GATK best practices or integrating CNV calling with other GATK variant pipelines.Votes: 0GitHub stars: 2
- Bio Copy Number Cnvkit AnalysisDetect 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.Votes: 0GitHub stars: 2
- Bio Clip Seq Clip Peak CallingCall protein-RNA binding site peaks from CLIP-seq data using CLIPper, PureCLIP, or Piranha. Use when identifying RBP binding sites from aligned CLIP reads.Votes: 0GitHub stars: 2
- Bio Clinical Databases Variant PrioritizationFilter and prioritize variants by pathogenicity, population frequency, and clinical evidence for rare disease analysis. Use when identifying candidate disease-causing variants from exome or genome sequencing.Votes: 0GitHub stars: 2
- Bio Clinical Databases Myvariant QueriesQuery myvariant.info API for aggregated variant annotations from multiple databases (ClinVar, gnomAD, dbSNP, COSMIC, etc.) in a single request. Use when annotating variants with clinical and population data from multiple sources simultaneously.Votes: 0GitHub stars: 2
- Bio Clinical Databases Gnomad FrequenciesQuery gnomAD for population allele frequencies to assess variant rarity. Use when filtering variants by population frequency for rare disease analysis or determining if a variant is common in the general population.Votes: 0GitHub stars: 2
- Bio Bedgraph HandlingCreate, manipulate, and convert bedGraph files for genome browser visualization. Covers bedGraph format, conversion to/from bigWig, normalization, and signal processing. Use when handling coverage and signal tracks from ChIP-seq, ATAC-seq, or RNA-seq.Votes: 0GitHub stars: 2