bio-workflows-proteomics-pipeline
End-to-end proteomics workflow from MaxQuant output to differential protein abundance. Orchestrates data import, normalization, imputation, and statistical testing with MSstats or limma.
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。
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。
End-to-end proteomics workflow from MaxQuant output to differential protein abundance. Orchestrates data import, normalization, imputation, and statistical testing with MSstats or limma.
Navigate protein structure hierarchy using Biopython Bio.PDB SMCRA model. Use for accessing models, chains, residues, and atoms, iterating over structure levels, extracting sequences, identifying residue types,...
Create genome browser-style visualizations showing multiple data tracks (coverage, peaks, genes) using pyGenomeTracks, Gviz, and IGV. Use when visualizing genomic data at specific loci with multiple aligned tra...
Visualize ChIP-seq data using deepTools, Gviz, and ChIPseeker. Create heatmaps, profile plots, and genome browser tracks. Visualize signal around peaks, TSS, or custom regions.
Align RNA-seq reads with STAR (Spliced Transcripts Alignment to a Reference). Use for RNA-seq data requiring splice-aware alignment. Supports two-pass mode for novel splice junction discovery.
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。