GitHub
bio-chip-seq-motif-analysis
De 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.
☆ 300Voir le skill
GPTomics AI Skills
GitHub ↗Explorez les skills IA publiés de GPTomics et consultez leurs instructions source.
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Skills indexés
269Étoiles des dépôts des skills indexés
80,661Forks du dépôt
13,719Moyenne des étoiles par skill indexé
300Les étoiles d’un dépôt peuvent se répéter entre ses skills.
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GitHub
bio-phylo-tree-visualization
Draw and export phylogenetic trees using Biopython Bio.Phylo with matplotlib. Use for creating publication-quality tree figures, customizing colors and labels, and exporting to various image formats.
☆ 300Voir le skill
GitHub
bio-differential-expression-batch-correction
Remove batch effects from RNA-seq data using ComBat, ComBat-Seq, limma removeBatchEffect, and SVA for unknown batch variables.
☆ 300Voir le skill
GitHub
bio-workflows-methylation-pipeline
End-to-end bisulfite sequencing workflow from FASTQ to differentially methylated regions. Covers Bismark alignment, methylation calling, and DMR detection with methylKit.
☆ 300Voir le skill
GitHub
bio-single-cell-multimodal-integration
Analyze multi-modal single-cell data (CITE-seq, Multiome, spatial). Use when working with data that measures multiple modalities per cell like RNA + protein or RNA + ATAC.
☆ 300Voir le skill
GitHub
bio-crispr-screens-mageck-analysis
MAGeCK (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 ta...
☆ 300Voir le skill
GitHub
bio-multi-omics-mofa-integration
Multi-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...
☆ 300Voir le skill
GitHub
bio-atac-seq-atac-qc
Quality control metrics for ATAC-seq data including fragment size distribution, TSS enrichment, FRiP, and library complexity. Use when assessing ATAC-seq library quality before or after peak calling to identify...
☆ 300Voir le skill
GitHub
bio-variant-calling-filtering-best-practices
Comprehensive variant filtering including GATK VQSR, hard filters, bcftools expressions, and quality metric interpretation for SNPs and indels.
☆ 300Voir le skill
GitHub
bio-flow-cytometry-doublet-detection
Detect and remove doublets from flow and mass cytometry data. Covers FSC/SSC gating and computational doublet detection methods. Use when filtering out cell aggregates before clustering or quantitative analysis...
☆ 300Voir le skill
GitHub
bio-microbiome-differential-abundance
Differential 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 fo...
☆ 300Voir le skill
GitHub
bio-data-visualization-heatmaps-clustering
Create clustered heatmaps with row/column annotations using ComplexHeatmap, pheatmap, and seaborn for gene expression and omics data visualization. Use when visualizing expression patterns across samples or ide...
☆ 300Voir le skill
GitHub
bio-variant-normalization
Normalize indel representation and split multiallelic variants using bcftools norm. Use when comparing variants from different callers or preparing VCF for downstream analysis.
☆ 300Voir le skill
GitHub
bio-microbiome-amplicon-processing
Amplicon sequence variant (ASV) inference from 16S rRNA or ITS amplicon sequencing using DADA2. Covers quality filtering, error learning, denoising, and chimera removal. Use when processing demultiplexed amplic...
☆ 300Voir le skill
GitHub
bio-workflows-microbiome-pipeline
End-to-end 16S amplicon workflow from FASTQ reads to differential abundance. Orchestrates DADA2 ASV inference, taxonomy assignment, diversity analysis, and compositional testing with ALDEx2.
☆ 300Voir le skill
GitHub
bio-metagenomics-kraken
Taxonomic classification of metagenomic reads using Kraken2. Fast k-mer based classification against RefSeq database. Use when performing initial taxonomic classification of shotgun metagenomic reads before abu...
☆ 300Voir le skill
GitHub
bio-genome-intervals-interval-arithmetic
Core interval arithmetic operations including intersect, subtract, merge, complement, map, and groupby using bedtools and pybedtools. Use when finding overlapping regions, removing overlaps, combining adjacent...
☆ 300Voir le skill
GitHub
bio-alignment-indexing
Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific genomic regions.
☆ 300Voir le skill
GitHub
bio-read-alignment-bowtie2-alignment
Align short reads using Bowtie2 with local or end-to-end modes. Use for ChIP-seq, ATAC-seq, or when you need flexible alignment modes. Supports gapped alignment.
☆ 300Voir le skill
GitHub
bio-microbiome-taxonomy-assignment
Taxonomic classification of ASVs using reference databases like SILVA, GTDB, or UNITE. Covers naive Bayes classifiers (DADA2, IDTAXA) and exact matching approaches. Use when assigning taxonomy to ASVs after DAD...
☆ 300Voir le skill
GitHub
bio-atac-seq-nucleosome-positioning
Extract nucleosome positions from ATAC-seq data using NucleoATAC, ATACseqQC, and fragment analysis. Use when analyzing chromatin organization, identifying nucleosome-free regions at promoters, or characterizing...
☆ 300Voir le skill
GitHub
bio-differential-expression-timeseries-de
Analyze time-series RNA-seq data using limma voom with splines, maSigPro, and ImpulseDE2. Identify genes with dynamic expression patterns.
☆ 300Voir le skill
GitHub
bio-proteomics-proteomics-qc
Quality control and assessment for proteomics data. Covers sample quality metrics, missing value patterns, replicate correlation, batch effect detection, and intensity distribution checks.
☆ 300Voir le skill
GitHub
bio-crispr-batch-correction
Batch effect correction for CRISPR screens. Covers normalization across batches, technical replicate handling, and batch-aware analysis. Use when combining screens from multiple batches or correcting systematic...
☆ 300Voir le skill
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