GitHub
bio-geo-data
Query NCBI Gene Expression Omnibus (GEO) for expression datasets using Biopython Bio.Entrez. Use for finding microarray/RNA-seq datasets, downloading expression data, and linking GEO to SRA.
☆ 299Voir le skill
Skills IA databases bioinformatics
Découvrez les skills databases bioinformatics, comparez leurs dépôts et consultez leurs instructions.
Catégories: databases bioinformatics
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GitHub
bio-chipseq-peak-annotation
Annotate 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 p...
☆ 299Voir le skill
GitHub
bio-longread-alignment
Align long reads using minimap2 for Oxford Nanopore and PacBio data. Supports various presets for different read types and applications. Use when aligning ONT or PacBio reads to a reference genome for variant c...
☆ 299Voir le skill
GitHub
bio-microbiome-qiime2-workflow
QIIME2 command-line workflow for 16S/ITS amplicon analysis. Alternative to DADA2/phyloseq R workflow with built-in provenance tracking. Use when preferring CLI over R, needing reproducible provenance, or workin...
☆ 299Voir le skill
GitHub
bio-hi-c-analysis-contact-pairs
Process Hi-C read pairs using pairtools. Parse alignments, filter duplicates, classify pairs, and generate contact statistics from Hi-C sequencing data.
☆ 299Voir le skill
GitHub
bio-sra-data
Download sequencing data from NCBI SRA using the SRA toolkit. Use for downloading FASTQ files from SRA accessions, prefetching large datasets, validating downloads, and configuring SRA toolkit.
☆ 299Voir le skill
GitHub
bio-primer-design-qpcr-primers
Design qPCR primers and TaqMan/molecular beacon probes using primer3-py. Configure probe Tm, primer-probe spacing, and hydrolysis probe constraints for real-time PCR assays.
☆ 299Voir le skill
GitHub
bio-workflows-genome-assembly-pipeline
End-to-end genome assembly workflow from reads to polished assembly with QC. Supports short reads (SPAdes), long reads (Flye), and hybrid approaches.
☆ 299Voir le skill
GitHub
bio-batch-downloads
Download large datasets from NCBI efficiently using history server, batching, and rate limiting. Use for bulk sequence downloads, large query results, and production-scale data retrieval.
☆ 299Voir le skill
GitHub
bio-microbiome-functional-prediction
Predict metagenome functional content from 16S rRNA marker gene data using PICRUSt2. Infer KEGG, MetaCyc, and EC abundances from ASV tables. Use when functional profiling is needed from 16S data without shotgun...
☆ 299Voir le skill
GitHub
bio-pathway-kegg-pathways
KEGG pathway and module enrichment analysis using clusterProfiler enrichKEGG and enrichMKEGG. Tests whether KEGG pathways are over-represented in a gene list. Supports 4000+ organisms via KEGG online database.
☆ 299Voir le skill
GitHub
bio-phylo-distance-calculations
Compute evolutionary distances and build phylogenetic trees using Biopython Bio.Phylo.TreeConstruction. Use for creating distance matrices from alignments, building NJ/UPGMA trees, parsimony analysis, and gener...
☆ 299Voir le skill
GitHub
bio-read-qc-contamination-screening
Detect sample contamination and cross-species reads using FastQ Screen. Screen reads against multiple reference genomes to identify bacterial, viral, adapter, or sample swap contamination. Use when suspecting c...
☆ 299Voir le skill
GitHub
bio-codon-usage
Analyze codon usage, calculate CAI (Codon Adaptation Index), and examine synonymous codon bias using Biopython. Use when analyzing coding sequences for expression optimization or evolutionary analysis.
☆ 299Voir le skill
GitHub
bio-read-qc-quality-reports
Generate and interpret quality reports from FASTQ files using FastQC and MultiQC. Assess per-base quality, adapter content, GC bias, duplication levels, and overrepresented sequences. Use when performing initia...
☆ 299Voir le skill
GitHub
bio-copy-number-cnvkit-analysis
Detect copy number variants from targeted/exome sequencing using CNVkit. Supports tumor-normal pairs, tumor-only, and germline CNV calling. Use for WES or targeted panel sequencing.
☆ 299Voir le skill
GitHub
bio-workflows-crispr-screen-pipeline
End-to-end CRISPR screen analysis from FASTQ to hit genes. Orchestrates guide counting, QC, statistical analysis with MAGeCK, and hit calling with multiple methods.
☆ 299Voir le skill
GitHub
bio-primer-design-primer-basics
Design PCR primers for a target sequence using primer3-py. Specify target regions, product size, melting temperature, and other constraints. Returns ranked primer pairs with quality metrics.
☆ 299Voir le skill
GitHub
bio-crispr-screens-crispresso-editing
CRISPResso2 for analyzing CRISPR gene editing outcomes. Quantifies indels, HDR efficiency, and generates comprehensive editing reports. Use when analyzing amplicon sequencing data from CRISPR editing experiment...
☆ 299Voir le skill
GitHub
bio-fastq-quality
Work with FASTQ quality scores using Biopython. Use when analyzing read quality, filtering by quality, trimming low-quality bases, or generating quality reports.
☆ 299Voir le skill
GitHub
bio-spatial-transcriptomics-spatial-preprocessing
Quality control, filtering, normalization, and feature selection for spatial transcriptomics data. Calculate QC metrics, filter spots/cells, normalize counts, and identify highly variable genes.
☆ 299Voir le skill
GitHub
bio-data-visualization-circos-plots
Create circular genome visualizations with Circos and pyCircos. Display multi-track data including ideograms, genes, variants, CNVs, and interaction arcs.
☆ 299Voir le skill
GitHub
bio-workflows-hic-pipeline
End-to-end Hi-C analysis workflow from contact pairs to compartments, TADs, and loops. Covers cooler matrices, cooltools analysis, and visualization.
☆ 299Voir le skill
GitHub
bio-de-results
Extract, 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 r...
☆ 299Voir le skill
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.