GitHub
bio-workflows-imc-pipeline
End-to-end imaging mass cytometry workflow from raw acquisitions to spatial cell analysis. Orchestrates image preprocessing, segmentation, phenotyping, and spatial statistics.
☆ 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-spatial-transcriptomics-spatial-visualization
Visualize spatial transcriptomics data using Squidpy and Scanpy. Create tissue plots with gene expression, clusters, and annotations overlaid on histology images.
☆ 300Voir le skill
GitHub
bio-workflows-scrnaseq-pipeline
End-to-end single-cell RNA-seq workflow from 10X Genomics data to annotated cell types. Covers QC, normalization, clustering, marker detection, and cell type annotation.
☆ 300Voir le skill
GitHub
bio-read-qc-umi-processing
Extract, process, and deduplicate reads using Unique Molecular Identifiers (UMIs) with umi_tools. Use when library prep includes UMIs and accurate molecule counting is needed, such as in single-cell RNA-seq, lo...
☆ 300Voir le skill
GitHub
bio-pathway-enrichment-visualization
Visualize enrichment results using enrichplot package functions. Covers dotplot, barplot, cnetplot, emapplot, gseaplot2, ridgeplot, and treeplot for clusterProfiler results.
☆ 300Voir le skill
GitHub
bio-phylo-tree-io
Read, write, and convert phylogenetic tree files using Biopython Bio.Phylo. Use for parsing Newick, Nexus, PhyloXML, and NeXML tree formats, converting between formats, and handling multiple trees in a single f...
☆ 300Voir le skill
GitHub
bio-workflows-longread-sv-pipeline
End-to-end workflow for detecting structural variants from long-read sequencing data. Covers ONT/PacBio alignment with minimap2 and SV calling with Sniffles or cuteSV.
☆ 300Voir le skill
GitHub
bio-phasing-imputation-haplotype-phasing
Phase genotypes into haplotypes using Beagle or SHAPEIT. Resolves which alleles are inherited together on each chromosome. Use when preparing VCF files for imputation, HLA typing, or population genetic analyses...
☆ 300Voir le skill
GitHub
bio-bedgraph-handling
Create, manipulate, and convert bedGraph files for genome browser visualization. Covers bedGraph format, conversion to/from bigWig, normalization, and signal processing. Use for handling coverage and signal tra...
☆ 300Voir le skill
GitHub
bio-rna-quantification-featurecounts-counting
Count reads per gene from aligned BAM files using Subread featureCounts. Use when you have BAM files from STAR/HISAT2 and need gene-level counts for DESeq2/edgeR.
☆ 300Voir le skill
GitHub
bio-expression-matrix-metadata-joins
Merge sample metadata with count matrices and add gene annotations. Use when preparing data for differential expression analysis or visualization.
☆ 300Voir le skill
GitHub
bio-batch-processing
Process multiple sequence files in batch using Biopython. Use when working with many files, merging/splitting sequences, or automating file operations across directories.
☆ 300Voir le skill
GitHub
bio-metagenomics-visualization
Visualize metagenomic profiles using R (phyloseq, microbiome) and Python (matplotlib, seaborn). Create stacked bar plots, heatmaps, PCA plots, and diversity analyses. Use when creating publication-quality figur...
☆ 300Voir le skill
GitHub
bio-paired-end-fastq
Handle paired-end FASTQ files (R1/R2) using Biopython. Use when working with Illumina paired reads, synchronizing pairs, interleaving/deinterleaving, or filtering paired data.
☆ 300Voir le skill
GitHub
bio-workflows-spatial-pipeline
End-to-end spatial transcriptomics workflow for Visium/Xenium data. Covers data loading, preprocessing, spatial analysis, domain detection, and visualization with Squidpy.
☆ 300Voir le skill
GitHub
bio-genome-intervals-bigwig-tracks
Create and read bigWig browser tracks for visualizing continuous genomic data. Convert bedGraph to bigWig, extract signal values, and generate coverage tracks using UCSC tools and pyBigWig. Use when preparing c...
☆ 300Voir le skill
GitHub
bio-single-cell-cell-communication
Infer cell-cell communication networks from scRNA-seq data using CellChat, NicheNet, and LIANA for ligand-receptor interaction analysis.
☆ 300Voir le skill
GitHub
bio-vcf-manipulation
Merge, concatenate, sort, intersect, and subset VCF files using bcftools. Use when combining variant files, comparing call sets, or restructuring VCF data.
☆ 300Voir le skill
GitHub
bio-crispr-library-design
CRISPR 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 sc...
☆ 300Voir le skill
GitHub
bio-workflows-multiome-pipeline
End-to-end multiome workflow for joint scRNA-seq + scATAC-seq analysis. Covers data loading, separate modality processing, and WNN integration with Seurat/Signac.
☆ 300Voir le skill
GitHub
bio-proteomics-quantification
Protein quantification from mass spectrometry data including label-free (LFQ, intensity-based), isobaric labeling (TMT, iTRAQ), and metabolic labeling (SILAC) approaches. Use when extracting protein abundances...
☆ 300Voir le skill
GitHub
bio-flow-cytometry-bead-normalization
Bead-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...
☆ 300Voir le skill
GitHub
bio-genome-assembly-assembly-qc
Assess genome assembly quality using QUAST for contiguity metrics and BUSCO for completeness. Essential for evaluating assembly success and comparing assemblers.
☆ 300Voir le skill
GitHub
bio-spatial-transcriptomics-image-analysis
Process and analyze tissue images from spatial transcriptomics data using Squidpy. Extract image features, segment cells/nuclei, and compute morphological features from H&E or IF images.
☆ 300Voir 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.