12,235 skills found · Page 178 of 408
FreedomIntelligence / bio-causal-genomics-fine-mappingIdentify likely causal variants within GWAS loci using SuSiE for sum of single effects regression and FINEMAP for shotgun stochastic search. Computes posterior inclusion probabilities and credible sets to prioritize variants for functional follow-up
FreedomIntelligence / bio-causal-genomics-mediation-analysisDecompose genetic effects into direct and indirect paths through mediating variables using the mediation R package. Tests whether gene expression, methylation, or other molecular phenotypes mediate the effect of genetic variants on disease
FreedomIntelligence / bio-causal-genomics-mendelian-randomizationEstimate causal effects between exposures and outcomes using genetic variants as instrumental variables with TwoSampleMR. Implements IVW, MR-Egger, weighted median, and MR-PRESSO methods for robust causal inference from GWAS summary statistics
FreedomIntelligence / bio-causal-genomics-pleiotropy-detectionDetect and correct for horizontal pleiotropy in Mendelian randomization analyses using MR-PRESSO for outlier removal, MR-Egger regression for directional pleiotropy, and Steiger filtering for variant directionality
FreedomIntelligence / bio-chipseq-differential-bindingDifferential binding analysis using DiffBind. Compare ChIP-seq peaks between conditions with statistical rigor. Requires replicate samples. Outputs differentially bound regions with fold changes and p-values
FreedomIntelligence / bio-chipseq-motif-analysisDe novo motif discovery and known motif enrichment analysis using HOMER and MEME-ChIP. Identify transcription factor binding motifs in ChIP-seq, ATAC-seq, or other genomic peak data
FreedomIntelligence / bio-chipseq-peak-annotationAnnotate ChIP-seq peaks to genomic features and genes using ChIPseeker. Assign peaks to promoters, exons, introns, and intergenic regions. Find nearest genes and calculate distance to TSS. Generate annotation plots and statistics
FreedomIntelligence / bio-chipseq-peak-callingChIP-seq peak calling using MACS3 (or MACS2). Call narrow peaks for transcription factors or broad peaks for histone modifications. Supports input control, fragment size modeling, and various output formats including narrowPeak and broadPeak BED files
FreedomIntelligence / bio-chipseq-qcChIP-seq quality control metrics including FRiP (Fraction of Reads in Peaks), cross-correlation analysis (NSC/RSC), library complexity, and IDR (Irreproducibility Discovery Rate) for replicate concordance. Use to assess experiment quality before downstream analysis
FreedomIntelligence / bio-chipseq-visualizationVisualize ChIP-seq data using deepTools, Gviz, and ChIPseeker. Create heatmaps, profile plots, and genome browser tracks. Visualize signal around peaks, TSS, or custom regions
FreedomIntelligence / bio-clinical-databases-somatic-signaturesExtract and analyze mutational signatures from somatic variants using SigProfiler or MutationalPatterns to characterize mutagenic processes
FreedomIntelligence / bio-copy-number-cnv-visualizationVisualize copy number profiles, segments, and compare across samples. Create publication-quality plots of CNV data from CNVkit, GATK, or other callers
FreedomIntelligence / bio-copy-number-cnvkit-analysisDetect copy number variants from targeted/exome sequencing using CNVkit. Supports tumor-normal pairs, tumor-only, and germline CNV calling
FreedomIntelligence / 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
FreedomIntelligence / bio-crispr-screens-batch-correctionBatch effect correction for CRISPR screens. Covers normalization across batches, technical replicate handling, and batch-aware analysis
FreedomIntelligence / bio-crispr-screens-crispresso-editingCRISPResso2 for analyzing CRISPR gene editing outcomes. Quantifies indels, HDR efficiency, and generates comprehensive editing reports
FreedomIntelligence / 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
FreedomIntelligence / 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
FreedomIntelligence / bio-crispr-screens-screen-qcQuality control for pooled CRISPR screens. Covers library representation, read distribution, replicate correlation, and essential gene recovery
FreedomIntelligence / bio-ctdna-mutation-detectionDetects somatic mutations in circulating tumor DNA using variant callers optimized for low allele fractions with UMI-based error suppression. Reliably detects mutations at VAF above 0.5 percent using consensus-based approaches
FreedomIntelligence / bio-data-visualization-specialized-omics-plotsThis skill provides reusable plotting functions for common omics visualizations that can be applied across different analysis types: - Volcano plots (any DE result) - MA plots (any log-fold-change data) - PCA plots (any high-dimensional data) - Enrichment dotplots (manual, not enrichplot) - Expressi…
FreedomIntelligence / 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
FreedomIntelligence / 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
FreedomIntelligence / 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
FreedomIntelligence / bio-differential-expression-batch-correctionRemove batch effects from RNA-seq data using ComBat, ComBat-Seq, limma removeBatchEffect, and SVA for unknown batch variables
FreedomIntelligence / bio-differential-expression-timeseries-deAnalyze time-series RNA-seq data using limma voom with splines, maSigPro, and ImpulseDE2. Identify genes with dynamic expression patterns
FreedomIntelligence / bio-differential-splicingDetects differential alternative splicing between conditions using rMATS-turbo (BAM-based) or SUPPA2 diffSplice (TPM-based). Reports events with FDR-corrected significance and delta PSI effect sizes
FreedomIntelligence / bio-epidemiological-genomics-amr-surveillanceDetect and track antimicrobial resistance genes using AMRFinderPlus and ResFinder with epidemiological context. Monitor resistance trends and identify emerging resistance patterns
FreedomIntelligence / bio-epidemiological-genomics-pathogen-typingPerform multi-locus sequence typing (MLST), core genome MLST, and SNP-based strain typing for bacterial isolate characterization using mlst and chewBBACA
FreedomIntelligence / bio-epidemiological-genomics-phylodynamicsConstruct time-scaled phylogenies and infer evolutionary dynamics using TreeTime and BEAST2 for outbreak analysis. Estimate divergence times, molecular clock rates, and ancestral states
