GitHub
bio-workflows-atacseq-pipeline
End-to-end ATAC-seq workflow from FASTQ files to differential accessibility and TF footprinting. Covers alignment, peak calling with MACS3, QC metrics, and optional TOBIAS footprinting.
☆ 300查看技能
GPTomics AI Skills
GitHub ↗浏览 GPTomics 维护的已发布 AI 技能，比较用途与说明，并通过来源仓库了解安装方式。
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已收录技能
269收录技能的仓库 Stars 合计
80,661仓库 Forks
13,719平均每个技能的仓库 Stars
300同一仓库中的多个技能可能共享 Stars，合计包含重复仓库数据。
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GitHub
bio-multi-omics-mixomics-analysis
Supervised and unsupervised multi-omics integration with mixOmics. Includes sPLS for pairwise integration and DIABLO for multi-block discriminant analysis.
☆ 300查看技能
GitHub
bio-population-genetics-association-testing
Genome-wide association studies (GWAS) with PLINK. Perform case-control and quantitative trait association testing using logistic/linear regression with covariates, generate Manhattan and QQ plots for result vi...
☆ 300查看技能
GitHub
bio-phasing-imputation-imputation-qc
Quality control of phasing and imputation results. Filter by INFO scores, assess accuracy, and prepare imputed data for downstream analysis. Use when filtering low-quality imputed variants or validating imputat...
☆ 300查看技能
GitHub
bio-variant-calling
Call SNPs and indels from aligned reads using bcftools mpileup and call. Use when detecting variants from BAM files or generating VCF from alignments.
☆ 300查看技能
GitHub
bio-workflows-multi-omics-pipeline
End-to-end multi-omics integration workflow. Orchestrates data harmonization, MOFA/mixOmics integration, factor interpretation, and downstream analysis across transcriptomics, proteomics, metabolomics, and othe...
☆ 300查看技能
GitHub
bio-rna-quantification-tximport-workflow
Import transcript-level quantifications from Salmon/kallisto into R for gene-level analysis with DESeq2/edgeR using tximport or tximeta.
☆ 300查看技能
GitHub
bio-flow-cytometry-clustering-phenotyping
Unsupervised clustering and cell type identification for flow/mass cytometry. Covers FlowSOM, Phenograph, and CATALYST workflows. Use when discovering cell populations in high-dimensional cytometry data without...
☆ 300查看技能
GitHub
bio-alignment-statistics
Generate alignment statistics using samtools flagstat, stats, depth, and coverage. Use when assessing alignment quality, calculating coverage, or generating QC reports.
☆ 300查看技能
GitHub
bio-longread-medaka
Polish assemblies and call variants from Oxford Nanopore data using medaka. Uses neural networks trained on specific basecaller versions. Use when improving ONT-only assemblies or calling variants from Nanopore...
☆ 300查看技能
GitHub
bio-phasing-imputation-reference-panels
Download, prepare, and manage reference panels for phasing and imputation. Covers 1000 Genomes, HRC, and TOPMed panels. Use when setting up imputation infrastructure or selecting appropriate reference panels fo...
☆ 300查看技能
GitHub
bio-read-qc-fastp-workflow
All-in-one read preprocessing with fastp including adapter trimming, quality filtering, deduplication, base correction, and HTML report generation. Use when preprocessing Illumina data and wanting a single fast...
☆ 300查看技能
GitHub
bio-alignment-filtering
Filter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific reads, removing low-quality alignments, or subsetting to target regions.
☆ 300查看技能
GitHub
bio-reference-operations
Generate consensus sequences and manage reference files using samtools. Use when creating consensus from alignments, indexing references, or creating sequence dictionaries.
☆ 300查看技能
GitHub
bio-imc-interactive-annotation
Interactive cell type annotation for IMC data. Covers napari-based annotation, marker-guided labeling, training data generation, and annotation validation. Use when manually annotating cell types for training c...
☆ 300查看技能
GitHub
bio-workflows-chipseq-pipeline
End-to-end ChIP-seq workflow from FASTQ files to annotated peaks. Covers QC, alignment, peak calling with MACS3, and peak annotation with ChIPseeker.
☆ 300查看技能
GitHub
bio-single-cell-trajectory-inference
Infer developmental trajectories and pseudotime from single-cell RNA-seq data using Monocle3, Slingshot, and scVelo for RNA velocity analysis.
☆ 300查看技能
GitHub
bio-methylation-dmr-detection
Differentially methylated region (DMR) detection using methylKit tiles, bsseq BSmooth, and DMRcate. Use when identifying contiguous genomic regions with methylation differences between experimental conditions o...
☆ 300查看技能
GitHub
bio-flow-cytometry-cytometry-qc
Comprehensive quality control for flow cytometry and CyTOF data. Covers flow rate stability, signal drift, margin events, dead cell exclusion, and batch QC. Use when assessing acquisition quality or identifying...
☆ 300查看技能
GitHub
bio-expression-matrix-sparse-handling
Work with sparse matrices for memory-efficient storage of count data. Use when dealing with single-cell data or large bulk RNA-seq datasets where most values are zero.
☆ 300查看技能
GitHub
bio-copy-number-gatk-cnv
Call copy number variants using GATK best practices workflow. Supports both somatic (tumor-normal) and germline CNV detection from WGS or WES data. Use when following GATK best practices or integrating CNV call...
☆ 300查看技能
GitHub
bio-multi-omics-similarity-network
Similarity Network Fusion (SNF) for patient stratification using multi-omics data. Integrates multiple data types into a unified patient similarity network.
☆ 300查看技能
GitHub
bio-genome-intervals-proximity-operations
Find nearest features, search within windows, and extend intervals using closest, window, flank, and slop operations. Use when performing TSS proximity analysis, assigning enhancers to genes, defining promoter...
☆ 300查看技能
GitHub
bio-chip-seq-super-enhancers
Identifies super-enhancers from H3K27ac ChIP-seq data using ROSE and related tools. Use when studying cell identity genes, cancer-associated regulatory elements, or master transcription factor binding regions t...
☆ 300查看技能
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。