10,220 skills found ¡ Page 151 of 341
FreedomIntelligence / bio-de-visualizationVisualize differential expression results using DESeq2/edgeR built-in functions. Covers plotMA, plotDispEsts, plotCounts, plotBCV, sample distance heatmaps, and p-value histograms
FreedomIntelligence / adhd-daily-plannerTime-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that
FreedomIntelligence / anndataThis skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets
FreedomIntelligence / bio-admet-predictionPredicts ADMET properties using ADMETlab 3.0 API or DeepChem models. Estimates bioavailability, CYP inhibition, hERG liability, and 119 toxicity endpoints with uncertainty quantification. Filters for PAINS and other structural alerts
FreedomIntelligence / bio-alignment-ioRead, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and other alignment formats for phylogenetics and conservation analysis
FreedomIntelligence / bio-alignment-msa-parsingParse and analyze multiple sequence alignments using Biopython. Extract sequences, identify conserved regions, analyze gaps, work with annotations, and manipulate alignment data for downstream analysis
FreedomIntelligence / bio-atac-seq-atac-qcQuality control metrics for ATAC-seq data including fragment size distribution, TSS enrichment, FRiP, and library complexity
FreedomIntelligence / bio-basecallingConvert raw Nanopore signal data (FAST5/POD5) to nucleotide sequences using Dorado basecaller. Covers model selection, GPU acceleration, modified base detection, and quality filtering
FreedomIntelligence / bio-causal-genomics-colocalization-analysisTest whether two traits share a causal variant at a genomic locus using Bayesian colocalization with coloc. Computes posterior probabilities for shared vs distinct causal variants between GWAS and eQTL signals
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-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
